Declaration and Undertaking by the Candidate

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1 Declaration and Undertaking by the Candidate I, Kumari Shahnaz D/o Mr. Himayatulla Khan Certify the work embodied in thesis entitled Characterization and Quantitative Analysis in Aromatic Rice Germplasm is my own first hand bonafide work carried out by me under the guidance of Dr. D. K. Mishra at Department of Plant Breeding and Genetics, College of Agriculture, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur during The matter embodied in the thesis has not been submitted for the award of any other degree/diploma. Due credit has been made to all the assistance and help. I, undertake the complete responsibility that any act of misinterpretation, mistakes, errors of fact are entirely of my own. I, also abide myself with the decision taken by my advisor for the publication of material extracted from the thesis work and subsequent improvement, on mutually beneficial basis, provided the due credit is given, thereof. Place: Jabalpur Date : Kumari Shahnaz

2 Copyright Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh, Copyright Transfer Certificate Title of the Thesis : Characterization and Quantitative Analysis in Aromatic Rice Germplasm Name of the candidate : Kumari Shahnaz Subject : Genetics and Plant Breeding Department : Plant Breeding and Genetics College : College of Agriculture, JNKVV, Jabalpur Year of thesis submission: 2014 Copyright Transfer The undersigned Kumari Shahnaz assigns to the Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh, all rights under Copyright Act, that may exists in and for the thesis entitled, Characterization and Quantitative Analysis in Aromatic Rice Germplasm submitted for the award of M.Sc. (Ag.) degree. Date : Place : Jabalpur Dr. D.K. Mishra (Major Advisor) Kumari Shahnaz (Student)

3 ACKNOWLEDGEMENT First of all, I would like to Thanks Almighty Allah for giving me this opportunity to express my heart full gratitude to all the dedicated people whose support and kind co-operation encouraged me during the course of investigation. It is a matter of great jubilance and privilege to express my deepest sense of indebtness and reverence to venerable Dr. D.K. Mishra, Director of Farms, Professor and Head, Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, chairman of my advisory committee and most efficient, punctual and sagacious personality. I am highly thankful to him for keeping my moral high, being attentive and providing valuable suggestions. Without his help it would not have been possible to complete this bothersome work of investigation. I wish to express deep sense of gratitude to Dr. V.S. Tomar, honorable Vice-Chancellor, Dr. S. S. Tomar, Director Research Services, Dr. S.K. Rao, Dean Faculty of Agriculture, Dr. S.K. Shrivastava, Director of instruction and Dr. R. V. Singh, Dean, College of Agriculture, J.N.K.V.V., Jabalpur for providing necessary facilities for my thesis work. I am deeply obliged to all the members of my advisory committee namely, Dr. G.K. Koutu Principal Scientist, Department of Plant Breeding and Genetics, Dr. S.S. Shukla Senior Scientist, Department of Plant Breeding and Genetics and Dr. H.L Sharma, Head of the Department, Department of Mathematics & Statistics, JNKVV, Jabalpur for their valuable guidance and timely help during the course of this investigation. I express my warmest feelings with deep sense of gratitude and regards to all respected teachers of my department Dr. A.K. Mehta, Dr. P.K. Moitra, Dr. Dhirendra Khare, Dr. A.N. Shrivastava, Prof. V.K. Gour, Dr. R.S. Shukla, Dr. R.K. Dubey, Dr. S.K. Bilaiya, Dr. M.K. Shrivastava, Dr. (Mrs.) Anita Babbar, Dr. S.K.Singh and Sunita Pandey without whose benevolent guidance and constant motivation it would not have been possible to complete this project.

4 I would like to mention and express my special thanks to Dr. Sharad Tiwari, Head of the Department, Molecular Biology and Biotechnology, Dr. Ashish Gupta (Department of Plant Pathology, Rewa), Dr. Priya Nair, Mrs. Meghna and Vijay prakash Bansal for rendering me support and helping me in my work. I am deeply obliged to Shri Kishori, Shri Manoj, Shri Brijesh and Shri Rammu of Rice Improvement Project, Seed Breeding Farm, JNKVV, Jabalpur for the help rendered to carry out the experiment. I express my sincere thanks to my seniors Arpita Shrivastava, Niharika Shukla, Monika Singh, Mrs. Neha Sohegaura, Namita Pal, Swati Sharma and Avinash Jha, my friends Ashita, Mohini, Sheetal, kandla, Neelam, Shamma, Meena, Mukesh, Nikhil, Abhishek, Rajkumar, Ajay, Jitendra, Lokesh, Pranay and Santosh. I have no words to express my feelings of humble gratitude for my sweet sister Gulnaz Khan and my parents Mr. Himayatulla Khan and Mrs. Maimun Nisha, My younger brothers and sister whose cheerful presence and contact filled with joy and energy, was of great value in my study as well as throughout my life. Finally, I am thankful to Almighty Allah for his heavenly blessing which has enabled me to achieve this seemingly dauntless task. Place : Jabalpur Date : July, 2014 (KUMARI SHAHNAZ)

5 INTRODUCTION Rice [Oryza sativa (L.)] (2n=24), belongs to the Family Graminae, Sub family Bumbosideae, Tribe Oryzeae and sub tribe oryzineae. This tribe has 11 genus of which Oryza is the only one with cultivated species. Oryza has two cultivated species and twenty two wild species. Among the two cultivated species, Oryza sativa, the Asian rice is grown worldwide whereas, Oryza glaberrima the African rice, is cultivated on limited scale in West Africa. Harlan and De Wet (1971) proposed classifying the wild relatives of a crop species into three categories on the basis of isolation barriers and the ease of gene transfer to the cultivated species. The pattern of variation among species examined through methods of numerical taxonomy, however, is helpful. A variation study of 16 species based on 42 morphological traits, reported by Morishima and Oka (1960) suggested that Oryza species can be divided into three main groups: (1) O. sativa and its relatives, (2) O. officinalis and its relatives and (3) other more distantly related species. In recent years efforts have been made to introgress useful genes from wild species to cultivated rice through interspecific hybridization (Brar et al. 1996; Jena and Khush 1990; Multani et al. 1994). On the basis of ease of gene transfer, the primary gene pool comprises the wild species O. rufipogon, O. nivara, O. glamapatula, O. meridionalis, O. breviligulata, O. longistaminata and the cultivated species O. sativa and O. glaberrima. Rice is the world s single most important crop and a primary food source for half of the world s population. Out of total 49% calories consumed by the human population comes from rice, wheat and maize, 23% are provided by rice, 17% by wheat and 9% by maize. Thus, almost one fourth of the calories consumed by the entire world population comes from rice (Subudhi et al., 2006). In India, during the period , rice is cultivated in an area of 44 m ha with production of m tonns thereby contributes 22.88% to the world s total production of 456 m tonns. It is estimated that, by 2030 at least m tonns of milled rice is to be produced in India. 1

6 Yield is a complex character, which is highly influenced by the environment. Hence, direct selection for yield may limit the selection efficiency and ultimately resulted into limited success in yield improvement. Thus, effective improvement in yield may be brought through selection of yield component characters. Besides yield, quality is another important aspect, which is to be enhanced in rice. Quality of rice may be considered from the view point of size, shape and appearance of grain, milling quality and cooking qualities (Dela Cruz and Khush., 2000). One of its important qualities is aroma which, along with fine grains, is an increasing demand for exports. India which is endowed with a great diversity of rice germplasm in its vast territorial land area is also known for a large number of cultivated varietal types. Amongst them, a variety of special quality rice is of great significance which deserve better premium in the domestic as well as export market. So far, only basmati and long grain non-basmati varieties of rice have succeeded in the export market. Recently, after realizing the export potentiality and also the domestic demand of basmati varieties, more attention has been given to increase the yield of basmati varieties in the country. India is, however, endowed with a varieties possessing short, slender aromatic rice which are popular in different traditional rice growing pockets and commend premium not less than the traditional basmati rice. Bringing such varieties to the knowledge of consumers abroad would certainly find small but assured market for them (Siddiq, 2002). However, attempts have been made for the improvement of such rice genotypes. Therefore, it is very much essential to assess the extent of genetic diversity present in the aromatic rice lines of our country in order to undertake further crop improvement programmes. However, rice plays an important role both economically and in terms of food security (Timmer, 2010). Aromatic rice is one of the major types of rice. It is a medium to long-grained rice. It is known for its aroma and taste. Aromatic rice emits specific aroma in fields, at harvesting, in storage, during milling, cooking and eating. Aroma development is influenced by both genetic factors and environment. It is known that aroma is best developed when aromatic rice is grown in areas where temperature is cooler during maturity. Aroma is due to certain chemicals present in the endosperm. The biochemical basis of aroma 2

7 was identified as 2-acetyl-1-pyrroline. The compound is known to be present in raw grain as well as in plant. In addition to 2-acetyl-1-pyrroline, there were about 100 other volatile compounds, including 13 hydrocarbons, 14 acids, 13 alcohols, 16 aldehydes, 14 ketones, 8 esters, 5 phenols and some other compounds, which are associated with the aroma development in rice. In recent years, aromatic rice has been introduced to the global market. Aromatic rice is also named as fine rice, scented rice or fragrance rice. It is very popular in Asia as well as Southeast Asia and has recently gained wider acceptance in the United States, Europe (Weber et al., 2000), the Middle East (Shobha et al., 2006) and Australia (Blakeney, 1992). Because of its natural chemical compounds which gives it a distinctive scent or aroma when cooked, aromatic rice commands a higher price than non-aromatic rice. Thus, aromatic or scented rice plays a vital role in global rice trading. Aromatic rice constitutes small but a special group of rice, considered as of best quality. Majority of the indigenous aromatic rice cultivars are small and medium grained (Singh et al. 2000a). Aromatic rice varieties in general are tall statured, possess fewer number of panicles, high stem weight, lower yields and susceptible in lodging. Therefore, for improvement of aromatic rice a special strategy needs to be designed by taking into consideration the correlation between the factors that are contributing in total yield. In aromatic rice breeding programme, besides the evaluation of the presence or absence of aroma, the total yield of aromatic rice is the second important selection criteria. A hybridization technique has been developed to assist in producing a high yielding aromatic rice variety (HYV) with better grain quality (Singh et al., 2000b). This is because aromatic or scented cultivars have often been associated with undesirable agronomic characters, such as low yield, susceptibility to pests and diseases and strong shedding. So, breeders wish to develop aromatic varieties with high yield and good resistance to pests (Bemer & Hoff, 1986). In this regard, the first high yielding aromatic rice variety was developed in the Indian Subcontinent in 1925 (Azeez & Shafi, 1966) and was followed by others. Most of these were from direct crosses and subsequent generations were handled by pedigree method of selection. 3

8 Because of rice s global importance, small genome size and genetic relatedness to other major cereals, efforts were undertaken to sequence the entire genomes of the two subspecies of rice indica and japonica. Genome sequence drafts were completed for both subspecies in 2002 and a highquality and annotated version of the japonica species was completed in 2005, which represent landmark achievements in biological research. One practical output from genomics research was the development of DNA markers (or molecular markers) in the late 1980s and 1990s. Markerassisted selection (MAS) in which DNA markers are used to infer phenotypic or genotypic data for breeding material is widely accepted to have great potential to improve the efficiency and precision of conventional plant breeding, which may ultimately lead to the accelerated release of new crop varieties and in case of rice, SSR markers are extensively used for molecular work. Single Sequence Repeats are most promising molecular markers. Because of PCR based methods, it is readily automated and requires a small amount of DNA and facilitated many QTL mapping studies in crop plants. QTL affecting a wide range of traits in rice have been identified and mapped (Yang et al.,2006 and Yu et al.,2006). In the present investigation, 149 Aromatic Network Project lines will be used for dissecting yield, yield related inter-componental traits and quality attributes to obtain precise information. To achieve such goals an investigation will be conducted with following objectives: To characterize aromatic lines of rice based on morphological traits To estimate genetic variability for yield and quality related traits in aromatic lines To study genotypic and phenotypic association among traits To estimate direct and indirect effects of yield and quality attributing traits on seed yield To identify superior aromatic lines based on yield and quality traits To validate the SSR markers for yield and yield related traits 4

9 REVIEW OF LITERATURE The present investigation entitled Characterization and Quantitative Analysis in Aromatic Rice Germplasm was carried out during the Kharif season of The review of the work done earlier is reviewed here at two major levels: (A) (B) Field level Molecular level The nature and extent of genetic variability present in the population is the basic requirement for any crop improvement programme. The large spectrum of genetic variability in segregating populations depends on the level of genetic diversity present among genotypes which offers better scope for selection. Success of any crop improvement programme through recombination breeding depends largely on genetic constitution of parents and important pattern of the traits. The development of a new variety in any crop species mainly depends on the availability of genetic variability which is of greatest interest to the plant breeder as it plays a vital role in planning a successful breeding programme. (A) FIELD LEVEL: 2.1 Characterization Germplasm provides the base material for crop improvement. A need for germplasm collection, evaluation and cataloguing is of utmost importance to have a dynamic crop improvement programme. Characterization of cultivars is based on different agro-morphological traits which is the most important step in the genetic improvement of varieties. Motiramani et al. (2001) characterized 480 accessions of early duration rice germplasm of Madhya Pradesh and Chhattisgarh for 15 morphological and 12 quantitative characters. A good amount of variation was observed for all the characters studied. 5

10 Rao et al. (2001) studied 123 native cultivars and landraces from Bastar region for 11 morphological and 9 agronomic traits. A majority of cultivars were found to possess green basal leaf sheath, green leaf blade, light green auricle, straw coloured apiculus, white stigma, panicle exertion and open type of panicle and horizontal flag leaf are other traits that were encountered in majority of cultivars. Characterization was done for one twenty New Plant Type lines as described by CRRI descriptor based on UPOV guidelines. Certain traits like presence of awns and distribution of awns were found to be unstable reported by Behla and Allah (2007). Parikh et al. (2012) studied seventy one native landrace and some of which are cultivated by tribal community of Madhya Pradesh and Chhattisgarh region. Twelve morphological characters were recorded for seventy-one accessions. Out of which basal leaf sheath colour, leaf blade colour, ligule colour, plant habit, apicutus colour and awning showed variation among the genotypes and the rest 6 was found in two classes of different genotypes. Sarawgi et al. (2012) characterized forty six aromatic rice accessions of Dubraj group from Chhattisgarh and Madhya Pradesh for twenty morphological, six agronomical and eight quality characters. The specific accessions D: 1137, D: 812, D: 950, D: 959, D: 925, D: 1008, D: 939, D: 666I and D: 1090 were identified for quality and agronomical characteristics. Subudhi et al. (2012) collected 55 germplasm accessions of aromatic short grain rice and recorded analysis of variance for 16 quantitative morphoagronomic characters. The study revealed that the leaf length varied from 30.7 cm (Kanika) to 73.6 cm (Bishnubhog). The culm height varied from 90.5 cm (Thakurbhog) to cm (Jabaphool). Culm number is also high and ranged from 8.9 (Dhusara) to 20.0 (Vasumati). The panicle length varied from 22.2 cm (Banspatri) to cm (Kalajeera) with mean length, 27.3 cm. The good yielders are Chhotbasmati, Pimpudibas, Lajkuri, Jaigundi, Kanika and Bishnubhog. These landraces can be popularized among the farmers and can be used as donor in varietal development programme. 6

11 2.2 Genetic variability The genetic variability in any breeding material is a prerequisite as it provides not only a basis for selection but also some valuable information regarding selection of diverse parents for use in hybridization programme. Variability in rice, before it became a subject of study by plant breeder was the concern of taxonomists such as Linnaeus (who gave the generic name Oryza ), Mastura (1933), Porters (1956) and Ghosh et al. (1981). Sadhukhan and Chattopadhyay (2000) studied twenty six aromatic genotypes of rice and observed high genotypic coefficient of variation for grains panicle -1, plant height and kernel length. Chakraborty et al. (2001) studied to access the genetic variability, correlation and co-heritability for eight morph-physiological characters like days to 50% flowering, plant height, flag leaf length, flag leaf breadth, effective branch, tillers per hill, panicle length, sterility percentage and grain yield per hill. Very small difference between GCV and PCV was observed for the characters like days to 50% flowering. Wide difference between GCV and PCV was observed for the characters like plant height, flag leaf length, effective branch tillers per hill, panicle length, sterility percentage and yield per plant. Moderate phenotypic and genotypic coefficients of variation were observed for panicle length and 1000 grain weight reported by Singh et al. (2002). Nayak et al. (2002) obtained high estimates of genotypic and phenotypic coefficients of variation for number of panicles, spikelets panicle -1, grains panicle -1 and grain yield plant -1. Chand et al. (2004) showed that all genotypes differed significantly with respect to plant height, number of tillers hill -1, days to maturity, panicle length, filled grains panicle -1, 1000 seed weight, effective tillers plant -1, grain length, grain breadth and grain yield plant -1. Genotypic and phenotypic coefficient of variation were high for grains panicle -1 and grain yield plant -1. Hasib et al. (2004) reported good correspondence between phenotypic and genotypic coefficient of variation in plant height, tillers plant -1, panicle length, filled grains panicle -1, grain length, 1000 seed weight and grain yield plant -1. 7

12 Bhaskar (2006) observed low magnitudes of PCV and GCV for plant height, days to 50% flowering, grain length/width ratio, panicle length, 100 grain weight and panicle index. Padmaja et al. (2008) revealed highly significant differences for all the characters except leaf width and 1000 seed weight among the genotypes. The estimates of genotypic and phenotypic coefficients of variation were high for all the characters except days to fifty per cent flowering and panicle length. Sahidullah et al. (2009) observed enormous variations in majority of characters viz., grain length, grain breadth, kernel weight, milling yield, kernel length and L/B ratio of kernel. Muhammad et al. (2010) found that additive, dominance and epitasis components of genetic variation for yield and some yield related traits were assessed through modified triple test cross technique in Basmati rice for the traits like plant height, tillers per plant, secondary branches per panicle, grains per panicle, 1000-grain weight and yield per plant except primary branches per panicle and panicle length. Selvaraj et al. (2011) revealed considerable variability among genotypes for characters like, plant height, number of tillers, number of productive tillers, panicle length, filled grains per panicle and test weight. Krishnamurthy et al. (2012) studies on genetic variability and character association of kernel and cooking quality traits in 67 indigenous aromatic rice cultivars revealed significant genotypic variation for most of the characters. The magnitude of difference between phenotypic coefficient of variation and genotypic coefficient of variation was relatively low for all the traits indicating less environmental influence. Hulling (%), milling (%) and head rice recovery (%) indicating importance of these traits in the inclusion under breeding for quality in rice. 2.3 Heritability Heritability in broad sense refers to the ratio of genotypic variance to the total phenotypic variance. The estimates of heritability help the plant breeders in selection of elite genotypes from diverse genetic population and also a good index of the transmission of characters from parents to their offspring. Brief reviews of heritability for different characters by various workers are as under. 8

13 High heritability for grain yield plant -1 was reported by Durai et al. (2001), Mishra and Verma (2002), Elayaraja et al. (2004), Hasib et al. (2004), Madhavilatha et al. (2005), Panwar (2005), Girish et al. (2006), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Kole et al. (2008) and Selvaraj et al. (2011). High heritability for number of effective tillers plant -1 was reported by Mishra and Verma (2002), Muthuswamy and Ananda Kumar (2006a), Narinder (2006), Bhagat (2007), Nandan et al. (2010) and Selvaraj et al. (2011). High heritability for Biological yield plant -1 was observed by Thakur et al. (2000), Narinder (2006), Girish et al. (2006) and Abdul Fiyaz et al. (2011). However, high heritability for sterility % and spikelet density was elucidated by Mishra and Verma (2002) while, the same for days to maturity was reported by Narinder (2006). Chaudhary et al. (2003) reported high heritability for kernel length, kernel length breadth ratio, kernel length after cooking, length breadth ratio of cooked rice, head rice recovery, milling percentage, panicle length, effective tillers plant -1, biological yield, harvest index and grain yield in fifty four aromatic rice accessions. High heritability for panicle length was observed by Mishra and Verma (2002), Hasib et al. (2004), Saxena et al. (2005), Ananthi et al. (2006), Narinder (2006) and Muthuswamy and Ananda Kumar (2006), for number of grains panicle -1 by Durai et al. (2001), Saxena et al. (2005), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Bhagat (2007), Kole et al. (2008), Chandra et al. (2009) and Nandan et al. (2010). Similarly, high heritability for days to 50 % flowering was also reported by Durai et al. (2001), Ananthi et al. (2006) and Narinder (2006). High heritability for 1000 grain weight was recorded by Mishra and Verma (2002), Narinder (2006), Kole et al. (2008), Nandan et al. (2010) and Abdul Fiyaz et al. (2011) while, the same for plant height was reported by Mishra and Verma (2002), Elayaraja et al. (2004), Sinha et al. (2004), Girish et al. (2006), Narinder (2006), Kole et al. (2008), Chandra et al. (2009) and Selvaraj et al. (2011). 9

14 High heritability for total number of spikelets per panicle was observed by Saxena et al. (2005), Girish et al. (2006), Narinder (2006), Bhagat (2007) and Abdul Fiyaz et al. (2011), same for number of filled grains panicle -1 with high heritability by Mishra and Verma (2002), Hasib et al. (2004), Panwar (2005), Narinder (2006) and Bhagat (2007) and for grain width by Mishra and Verma (2002) and Hasib et al. (2004). The entire yield contributing characters showed high heritability was elucidated by Tyagi et al. (2004) and Narinder (2006). High heritability for harvest index was observed by Elayaraja et al. (2004), Madhavilatha et al. (2005) and Girish et al. (2006) while, high heritability for spikelet fertility % was reported by Madhavilatha et al. (2005). Selvaraj et al. (2011) reported high heritability coupled with high genetic advance and high genotypic variation for number of tillers, number of productive tillers per plant, plant height and grain yield per plant. Hosseini et al. (2012) reported high heritability estimates associated with high genetic advance for height, root dry weight and shoot length characters and concluded that heritability estimates have been understood to be useful in indicating the relative value of selection based on phenotypic expression of different characters. Reddy et al. (2013) studied the genetic parameters i.e. variability, heritability and genetic advance cross-wise in aromatic rice. A critical examination of genetic parameters in each cross in F 2 generation revealed the presence of wider range of variability for both yield and quality traits. Estimates of heritability in broad sense and genetic advance were high for number of grains per panicle, grain yield per plant and kernel length whereas, the estimates were relatively low-moderate for the remaining characters. Keeping in view the gene action known from the genetic parameters, selection on important yield components viz., number of grains per panicle and grain yield per plant and the quality trait, kernel length was suggested to bring out further improvement in aromatic rice. 10

15 Rafii et al. (2014) studied a total of 17 rice genotypes consisted of 12 F 1 progenies and five parental lines which were evaluated for performance of grain qualities, yield and yield components and vegetative traits and reported highest heritability for plant height followed by panicle length and grain shape which could be successfully inherited to the next generations. However, in the quantitative traits such as grain qualities and yield components, they are usually difficult to inherit to the next generation due to low heritability values. 2.4 Genetic Advance Genetic advance refers to the improvement in the genetic value of the selected single plants over the base population. Heritability estimates along with genetic advance are normally more helpful in predicting the gain under selection from heritability alone. In present investigation, high genetic advance for grain yield plant -1 was reported by Mishra and Verma (2002), Agrawal (2003), Chand et al. (2004), Chaudhary et al. (2004), Sinha et al. (2004), Sharma and Bhuyan (2004), Madhavilatha et al. (2005), Panwar (2005), Girish et al. (2006), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Chandra et al. (2009), Nandan et al. (2010) and Selvaraj et al. (2011). High genetic advance for 1000 grain weight was reported by Rao (2000), Sinha et al. (2004), Hasib et al. (2004), Nandan et al. (2010) and Abdul Fiyaz et al. (2011). Similarly, high genetic advance observed for plant height was reported by Mishra and Verma (2002), Elayaraja et al. (2004), Hasib et al. (2004), Saleem et al. (2008) and Selvaraj et al. (2011), for number of effective tillers plant -1 Mishra and Verma (2002), Chaudhary et al. (2004), Girish et al. (2006), Nandan et al. (2010) and Selvaraj et al. (2011) and for number of tillers plant -1 reported by Kumari et al. (2003) and Girish et al. (2006). In this investigation, high genetic advance in number of grains panicle -1 was reported by Rao (2000), Agrawal (2003), Kumari et al. (2003), Sharma and Bhuyan (2004), Panwar (2005), Madhavilatha et al. (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009) while, the same for panicle weight plant -1 was reported by Thakur et al. (2000) and Chand et al. (2004). 11

16 Low genetic advance for days to 50 % flowering and panicle length were reported by Agrawal (2003), Chand et al. (2004) and Padmaja et al. (2008) while, low genetic advance for number of tillers plant -1 was reported by Agrawal (2003) and Chand et al. (2004). Number of grains panicle -1, days to 50 % flowering and 1000 grain weight recorded low genetic advance was elucidated by Satyanarayana et al. (2005). However, Satyanarayana et al. (2005), Madhavilatha et al. (2005), Panwar (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009) recorded low genetic advance for spikelet fertility %. High genetic advance for panicle length was reported by Chaudhary et al. (2004) and Hasib et al. (2004), for harvest index by Elayaraja et al. (2004) and Girish et al. (2006) and for number of filled grains panicle -1 by Hasib et al. (2004). High genetic advance for characters viz., biological yield plant -1, dry weight plant -1, spikelet sterility %, number of filled grains panicle -1 and spikelet density were reported by Madhavilatha et al. (2005), Panwar (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009). Moderate genetic advance was advocated by Ananthi et al. (2006) for days to 50 % flowering, panicle length and 1000 grain weight. High genetic advance observed for grain length was reported by Chand et al. (2004) and Hasib et al. (2004), for biological yield plant -1 and harvest index by Chaudhary et al. (2004) and Saleem et al. (2008). Harvest index, grain yield panicle -1 and number of filled grains panicle -1 recorded high genetic advance were reported by Madhavilatha et al. (2005), Panwar (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009). Chaudhary et al. (2004) observed high genetic advance for kernel length, kernel length after cooking, length breadth ratio of cooked rice, head rice recovery and milling percentage in fifty four aromatic rice accessions. Narinder (2006) reported high genetic advance for grain yield per plant, biological yield per plant, panicle weight per plant, number of tillers per plant, number of productive tillers per plant, panicle length, number of spikelets per plant and filled grain per panicle. However, low genetic advance for plant height, L/B ratio of grain, days to maturity, 1000 grain weight and days to maturity was recorded. 12

17 Saleem et al. (2008) reported highest genetic advance for biological yield per plant followed by plant height, flag leaf area, yield plant -1, harvest index and panicle density while, Jayasudha and Sharma (2010) reported high heritability coupled with high genetic advance for spikelet fertility % followed by days to 50% flowering and grain yield per plant. High heritability associated with high genetic advance indicate considerable potential in the development of high yielding varieties through selection of desirable plants in succeeding generations. Akinwale et al. (2011) reported high to medium genetic advance for the number of grains per panicle, grain yield, panicle weight and the number of panicles per plant. Reddy et al. (2013) reported high genetic advance for number of grains per panicle, grain yield per plant and kernel length whereas, the estimates were relatively low-moderate for the remaining characters. Keeping in view the gene action known from the genetic parameters, selection on important yield components viz., number of grains per panicle and grain yield per plant and the quality trait, kernel length was suggested to bring out further improvement in aromatic rice. 2.5 Correlation coefficients Correlations indicate the magnitude of linear association between pairs of characters and form the basis of selection index, thereby aiding the breeder in crop improvement programmes. It will help to know how the improvement in one character will bring simultaneous changes in other characters. Yield is a polygenically inherited character and is highly influenced by environmental effects. Knowledge of genetic correlation among the factors contributing to yield leads to the most effective method of selection by the use of favourable combination of characters. Hence, direction and magnitude of component characters with yield serves as a prerequisite for successful breeding programmes. Correlation studies provide better pathway for yield improvement during selection (Robinson et al and Johnson et al. 1955). Rao (2000) reported that grain yield plant -1 was positively associated with panicles plant -1, panicle length and number of grains panicle

18 Tomar et al. (2000), Nayak et al. (2001), Shashidhar et al. (2005) and Sabu et al. (2009) reported that grain yield plant -1 was positively associated with plant height, number of effective tillers plant -1, panicle length, number of grains panicle -1, harvest index, biological yield plant -1 and days to 50 % flowering. While, Islam et al. (2002) found that grain yield plant -1 was positively correlated with plant height and grain weight plant -1 and negatively correlated with days to 50 % flowering. Rasheed et al. (2002) and Girish et al. (2006) reported the positive association of plant height with grain yield plant -1. Correlation of plant height with number of tillers plant -1 was positive reported by Rasheed et al. (2002). Samo et al. (2002) reported that grain yield plant -1 showed positive correlation with plant height, 1000 grain weight, number of panicles plant -1, panicle length and number of tillers plant -1. Chaudhary and Motiramani (2003) reported that grain yield plant -1 indicated significant positive correlation with number of effective tillers plant -1 and biological yield plant -1. While, Chand et al. (2004) observed significant positive correlations of grain yield plant -1 with grains panicle -1 and grain length. Tyagi et al. (2004) reported that the characters viz., number of effective tillers plant -1, panicle length, days to 50 % flowering and 100 seed weight showed significant and positive association with grain yield plant -1. Therefore, selection for these characters may be useful for developing improved varieties. A positive and significant correlation between grain length and grain yield per plant was reported by Chand et al. (2004) while, the same between grain breadth and grain yield was also reported by Girish et al. (2006). Grain yield plant -1 was observed to be positively associated with days to 50 % flowering, plant height, number of effective tillers plant -1, panicle length, number of grains panicle -1, harvest index and 1000 grain weight reported by Madhavilatha et al. (2005b). In another study, grain yield plant -1 was observed to be positively associated with spikelet fertility, panicle length, number of grains panicle -1 and number of effective tillers plant -1 reported by Satyanarayana et al. (2005). 14

19 Gazafrodi et al. (2006) reported significant and positive correlation between grain yield plant -1 and number of effective tillers plant -1 and also in between number of tillers plant -1 and number of grains panicle -1. A significant and positive correlation was present between plant height and number of grains panicle -1. However, a non-significant and negative association was observed between number of tillers plant -1 and grain yield plant -1 reported by Zahid et al. (2006). Grain yield plant -1 was significantly correlated with days to 50 % flowering, number of tillers plant -1, number of effective tillers plant -1, number of grains panicle -1, flag leaf length, flag leaf width and plant height reported by Agahi et al. (2007). Grain yield plant -1 was correlated significantly and positively with plant height, panicle length, flag leaf area, number of grains panicle -1. Correlation of plant height with number of tillers plant -1 was positive. Number of grains panicle -1 showed positive correlation with grain yield plant -1 reported by Khan et al. (2009). Nandan et al. (2010) in correlation studies revealed strong positive association of yield with days to 50 % flowering, plant height, number of grains per panicle, number of spikelets per panicle and spikelet fertility. Basavaraja et al. (2011) studied that the correlation analysis indicated that grain yield was significantly associated with panicle length, test weight, number of tiller per plant, number of productive tiller per plant, number of spikelet per panicle and per cent spikelet fertility. Nagaraju et al. (2013) studied correlation coefficient in six parents and their 15 F 1 crosses for eleven component characters including grain yield. The obtained results indicated that number of grains per panicle, total number of productive tillers per plant, harvest index, kernel L/B ratio, milling percentage and panicle length showed highly significant positive association with grain yield per plant. Suwarto et al. (2013) reported significant positive correlation in Green Super Rice Genotypes for plant height, number of grains per panicle, panicle length, flowering (days to 50% flowering) and grain yield per culm. The correlation and regression coefficient between F 1 and donor parent was significant for these characters. 15

20 2.6 Path coefficient analysis Path coefficient measures the direct and indirect contributions of independent variables on a dependent variable. Though the correlation coefficients depict the nature of association among the characters, it is the path analysis that splits the correlation coefficients into direct and indirect effects thus specifying the relative contribution of each character. It further reveals the different ways in which a particular character influences a dependent variable. A brief reviews has been summarized below. Janardhanam et al. (2000) revealed that, plant height, spikelets panicle -1 and grains panicle -1 had high direct effects on plant yield. The effects of these characters were further increased by positive indirect effect of plant height through spikelets and grains panicle -1, productive tillers plant -1, panicle length through plant height, spikelets panicle -1 and grains panicle -1, spikelets panicle -1 through plant height and grains panicle -1. The major yieldcontributing characters, based on indirect and direct effects, were plant height, spikelets panicle -1 and grains panicle -1. Highest positive direct effect towards grain yield plant -1 was contributed by 100 grain weight elucidated by Tomar et al. (2000), Gazafrodi et al. (2006) and Agahi et al. (2007), for plant height reported by Babu et al. (2002), Babar et al. (2007), for number of effective tillers plant -1 reported by Tomar et al. (2000) and Gazafrodi et al. (2006). Harvest index, flag leaf length and number of grains panicle -1 had larger direct effects on grain yield plant -1 reported by Tomar et al. (2000) and Gazafrodi et al. (2006). Nayak et al. (2002) revealed that, panicle number plant -1, grains panicle -1 and 1,000 seed weight contributed to the grain yield. Positive indirect effects were contributed by panicle length, number of grains panicle -1 and spikelet fertility as advocated by Babu et al. (2002). Flag leaf width followed by flag leaf length, spikelet density, harvest index, biological yield plant -1 and plant height had the greatest positive effect on grain yield plant -1 as advocated by Mishra and Verma (2002). A high direct effect on grain yield plant -1 was due to number of effective tillers plant -1 reported by Sinha and Banerjee (2002). 16

21 Khedikar et al. (2004) revealed that, 1000 seed weight had the highest positive direct effect on grain yield followed by spikelet density, effective tillers per plant, panicle length and days to fifty per cent flowering and hence direct selection through these characters would be more effective. Shanthala (2004) reported that spikelet density exhibited the highest direct effect on grain yield plant -1 followed by harvest index, 1000 grain weight and number of effective tillers plant -1. However plant height, panicle weight plant -1, panicle length and spikelet number recorded negative direct effect on grain yield plant -1. Thus, a selection for spikelet density, harvest index, 1000 grain weight and number of effective tillers plant -1 is beneficial for direct enhancement of grain yield. Agahi et al, (2007) reported that, the productive tillers plant -1 had the highest positive direct effect on grain yield plant -1 followed by the number of grains panicle -1 and 1000 seed weight respectively. Path coefficient analysis indicated highest direct effect of number of grains panicle -1 on grain yield plant -1 reported by Khan et al. (2009). Plant height and number of panicles plant -1 recorded the highest positive indirect effect on yield via harvest index whereas number of filled grains panicle -1 on grain yield plant -1 via harvest index and panicle length reported by Chakraborty et al. (2010). Nandan et al. (2010) observed path analysis indicated that the number of grains per panicle had maximum direct effect on grain yield per plant followed by days to 50 % flowering, hulling percentage, plant height and harvest index. Wattoo et al. (2010) in his path coefficient analysis study revealed that, days to maturity had the highest direct effect on grain yield per plant. In addition, the yield components had positive direct effect on grain yield except the days to heading. The order of yield components was the number of productive tillers per plant, flag leaf area and 1000 grain weight. The improvement in grain yield will be efficient if the selection is based on biological yield components, number of productive tillers per plant and flag leaf area. These traits may also be utilized in pure line selection. 17

22 Selvaraj et al. (2011) reported that path coefficient analysis for test weight exhibited maximum positive direct effect on grain yield per plant followed by filled grains per panicle, plant height, panicle length, number of tillers per plant and days to 50% flowering and they contributed primarily to yield and could be relied upon for selection of genotypes to improve genetic yield potential of rice. Basavaraja (2011) studied that path coefficient analysis revealed that days to 50% flowering, plant height, panicle length, panicle number, number of productive tiller per plant, percent spikelet fertility and amylose percent had positive direct effect on grain yield. Hence, selection based on these traits could help to bring simultaneous improvement of yield and yield attributes. Nagaraju et al., (2013) studied the path coefficient analysis in six parents and their 15 F 1 crosses for eleven component characters including grain yield and concluded number of grains per panicle and total number of productive tillers per plant as the main yield components because these traits showed the highest positive direct effects towards increasing grain yield. (B) MOLECULAR LEVEL ( Diversity Analysis) Molecular markers have proven to be powerful tools in assessment of genetic variation and in the elucidation of genetic relationships within and among species. Several molecular markers viz. SSRs (Levinson and Gutman, 1987), RAPD (Williams et al 1990; Tingey and Deltufo, 1993), RFLP (Paran and Michelmore, 1993; Becker et al., 1995), AFLP ( Mackill et al., 1996) ISSRs (Albani and Wilkinson, 1998; Blair et al., 1999) are presently available to assess the variability and diversity at molecular level (Joshi et al., 2000). SSR s markers have been used to analyze diversity and to locate genes (Temnykh et al., 2001) and QTLs on rice chromosomes using both intra and inter specific crosses (Bao et al., 2000 and Moncada et al., 2001).The utility of DNA markers has been suggested for precise and reliable characterization and discrimination of genotypes (Karkousis et al., 2003). Micro-satellite or simple sequence repeat (SSR) marker analysis was carried out to assess allelic diversity and prepare a DNA fingerprint database of 24 rice genotypes, including three premium traditional Basmati, 9 cross- 18

23 bred Basmati, a local scented selection, eight indica and three japonica rice cultivars. A total of 229 alleles were detected at the 50 SSR loci and 49 alleles were present in only one of the 24 cultivars. The size difference between the smallest and largest allele varied from 1 (RM333) to 82 (RM206). A number of SSRs have been identified, which can be used to differentiate the traditional Basmati cultivars and between traditional Basmati and other crossbred Basmati or long grain, non-basmati rice cultivars (Priyanka et al., 2004). Genetic diversity among 51 Sali rice accessions from Assam was characterized based on 72 RAPD markers (Dakshina and Sarma, 2004). 11 polymorphic primers showed a high degree of molecular variation with the range of polymorphic bands from 33 to 100%. The Jaccard's similarity coefficient (0.515) indicated high level of diversity. A total of 208 simple sequences repeat markers were used to identify 42 parental lines of hybrid rice. Genetic polymorphism was detected using 123 primers. Genetic diversity was higher in chromosome 9 and 10 whereas lower in chromosome 12 (Xiao-Xiao Yu, 2006). Twelve out of 10 primers showed polymorphism between parental lines. The seed purity of Dyou 527 was confirmed using the SSR primers RM337, RM244 and RM346. The lines Dyou 527 and Dyou 68 were distinguished using the SSR primers for Dyou 527. A study was conducted to differentiate Bario rice cultivars using SSRs markers well distributed on all 12 chromosomes to study rice diversity (Wong et al., 2009). A total of 31 alleles were generated by 12 polymorphic microsatellite loci among the cultivars with an average of 2.6 alleles per locus. Average PIC value obtained was An UPGMA dendogram based on SSR polymorphism indicated high variation among the rice varieties with the coefficient ranging from 0.16 and 0.92.Genetic diversity determination using cluster analysis showed differentiation of rice cultivars into 2 major groups and several sub-groups. Genetic diversity of 101 high quality conventional rice samples was analyzed with 16 pairs of SSR primers evenly distributed in 12 chromosomes of rice genome. All SSR primers showed polymorphism with 100% polymorphic locus rate. The 16 pairs of primers amplified polymorphic bands with 55 alleles, and the average alleles (Ap), effective alleles (Ae) and 19

24 polymorphism information content (PIC) were , , and , respectively. Cluster analysis indicated that the genetic similarity coefficients among 101 high quality conventional rice varieties ranged from to (XiLan et al., 2010). A set of 29 accessions of Indian popular rice varieties was subjected to diversity study using simple sequence repeat (SSRs), a total of 87 alleles were produced that were 100% polymorphic. Twelve sets of SSR primers amplified specific alleles in 14 genotypes. The PIC value ranged from 0.57 (RM 313) to 0.98 (RM 442 and RM 163) with average of 0.78 and average genetic similarity of 0.38 was observed among the popular varieties. The maximum similarity of 0.82 was observed between Jayshree and Sarjoo52 and minimum similarity of 0.05, between Jaya and Pusa Basmati 1. Based on ecologies and duration groups showed a maximum similarity of 0.34 between IRM and RSL groups and a minimum similarity of 0.18 between IRE and RSL groups. Out of 29 genotypes, 14 produced specific alleles, which can be used as molecular tags for particular genotypes when utilized along with the non polymorphic markers in this set of genotypes it produces bar-coded molecular tags for the identification of the valuable new plant lines. (Upadhyay et al., 2011). Chaudhari (2013) identified 25 QTLs to be associated with yield and yield attributing traits. Out of 40 SSR polymorphic markers, 13 showed association for yield and its attribute. The numbers of QTLs were 1 to 11 and mapped on chromosome 2, 3, 5, 7, 8, 10 and 11. Phenotypic variance ranged from 18.48% to 69.87%. Forty rice accessions were evaluated by means of 24 microsatellite markers distributed over the whole rice genome. A total of 66 alleles were detected at 24 SSR loci, and the number of alleles per marker ranged from 2 to 4, with an average of Polymorphism information content (PIC) value ranged from (RM315) to (RM252), with an average of per marker. The average genetic diversity over all SSR loci for the 40 genotypes was , ranging from to The dendogram based on the cluster analysis by microsatellite polymorphism, grouped 40 rice cultivars into three groups effectively differentiating basmati cultivars from non-basmati cultivars. (Shah et al., 2013). 20

25 MATERIAL AND METHOD The present investigation entitled Characterization and Quantitative Analysis in Aromatic Rice Germplasm was carried out during the Kharif season of The techniques followed and materials used during the course of investigation are presented in this chapter. 3.1 Experimental material and other details The experiment will be conducted at two major levels: (A) (B) (A) Field level Molecular level At Field level Experimental site The experiment was carried out at Seed Breeding Farm under Rice Improvement Project, Department of Genetics and Plant Breeding, College of Agriculture, J.N.K.V.V., Jabalpur (M.P.).The experimental area occupied was quite uniform in respect of topography and fertility Climate and weather Jabalpur is situated at N latitude and E longitudes at an altitude of m above the mean sea level. This region has subtropical, semi-arid climate with hot and dry summer and cold winter with occasional showers. The average rainfall is about mm, which is received mostly from July to September. Temperature vary from 6 0 C being minimum in January to 45 0 C being maximum in May and June. This area is under Kymore plateau and Satpura hills agro-climatic zone as per norms of National Agricultural Research Programme. This area as per National Bureau of Soil Science and Land Use Planning of ICAR comes under agro-ecological sub region number 10.1 named as sub-humid dry eco-region. The data related to weekly maximum and minimum temperature, relative humidity, wind velocity, rainfall, number of rainy days, sunshine hours and evaporation of entire crop growing period of experiment has been presented in appendix-1. 21

26 3.1.3 Experimental material The experimental material consists of 149 Aromatic Network Project lines from Seed Breeding Farm, JNKVV, Jabalpur. These lines were planted in randomized complete block design with three replications. A detail of these lines is given in table no.1. Table 1: Details of Aromatic Network Project lines (at JNKVV, Jabalpur) used in the study programme 1 ANP HUR -ASG-MJ R NDR NDR ANP BPT PTB 13 5 ACHARA MATI 27 PUSA SUGANDH -3 6 PUSA BASMATI 6 28 RD BASMATI RAVI 29 BASMATI TALL 8 BASMATI NAROT BASMATI BASMATI BASMATI 10 BASMATI MAHON BASMATI BASMATI BASMATI 370 B 12 BASMATI 1-1-A 34 BASMATI BASMATI BASMATI BASMATI BASMATI 372 A 15 BASMATI BASMATI Basmati BASMATI BASMATI SURKH BASMATI BASMATI BASMATI C BASMATI BASMATI BASMATI BASMATI BASMATI NEPAL 43 BASMATI BAS SUFAID BAS SURKH

27 45 BASMATI 127A 73 MAYUR KRANTI 46 TULSI MANJARI 74 KHASKANI 47 MOHAN BHOG 75 RANDHUNI PAGAL 48 DANAGURI 76 KALAMANIYA 49 BADSHA BHOG 77 BR KEDA GAURI 78 GAYASU 51 TULASIFUL 79 GOPAL BHOG 52 DUDHKHASA 80 KALIJOHA 53 KRISHNA KAMOD 81 BASMATI C-4-63-G 82 C-4-63-G 55 D DU THOM THAI BINH HAI PHONG 56 HUNG-MI-HSIANG-MA-TSAN 84 ANP KALIMOOCH 85 LUA NHE 58 MILFOR 6 86 MAJOR DJAMBON 59 NIAW PING 87 NEPALI JOHA 60 PADI BAWANG 88 XIANG GENG LI 61 BEGAMI T 1 89 BEGAMI S-7 62 BEGAMI DULHA BHOG 63 HBC HBC HBC HBC HAWM MALI 93 JAO MALI 66 MIL GROSA 94 IET IET BASMATI LAMO 68 CHANAN 96 HKR 240 IET JJ HARYANA GAURAV 70 IET MALAGKIT SUNG SONG 71 IR IR IR IR

28 101 IR IR IR IR IR SHARBATI 104 PUSA BARAH 105 KHAO DAWK MALI KALIA 106 KARPUR BHOG 131 RAMACHANDRA BOITA 107 KALA BHUTIA 132 BAHURUPI 108 DUDHSAR 133 NAGRA 109 RANI KAJAL 134 MACCHA KANTA 110 HALDI CHUDI 135 KOLIHA 111 HARI SHANKAR 136 LAL GORI 112 KUSUMA 137 GOVIND BHOG 113 LILAVATI 138 KERALA SUNDARI 114 PKV HMT 139 PKV MAKARAND 115 RAJENDRA SWETHA 140 MUGAD SUGANDHA 116 SUGANDA MATI 141 ACHARAMATI 117 BISHNU BHOGA 142 BASMATI BHOGA 118 CHATIANAKI 143 DHANA PRASAD 119 GANGA BALLI 144 HEERAKANI 120 JAIPULLA 145 ANP KARPURA BASA 146 LEELA BATI 122 TULSI PHOOLA 147 SARAGA DHULLI 123 MUIGAI 148 UPRBS 98/ UPRI UPR UPR

29 3.1.4 Experimental methods Experiment consisted of 149 Aromatic Network Project lines which were grown in randomized complete block design with three replications. Twenty one day old seedlings were transplanted in the experimental site with spacing of 15 cm between plant to plant and 20 cm between the rows keeping single seedling per hill. Gap filling was done within a week in order to maintain uniform plant population. Fertilizer dose of 120 kg N, 60 kg P 2 O 5, and 60 kg K 2 O was applied. Entire dose of P 2 O 5 and K 2 O along with half dose of N was applied as basal dose at the time of final field preparation, remaining amount of nitrogen was splitted in two equal splits and were applied at the time of active growth and grain filling stages. The standard agronomic practices were adopted for normal crop growth. Observations were recorded as per the DUS guidelines for rice. Observations were recorded on the basis of middle five random competitive plants selected from each line in every replication for the evaluation of yield and yield contributing traits. Mean of main, average and smallest panicle from each of the five randomly selected plants were used to record the observations of panicle traits Morphological characters Observations on all the morphological characters were recorded on the net plot basis Basal Leaf sheath color: It was observed at initial stage and classified as green, purple lines, light purple and purple Leaf: Pubescence of blade surface: This character was recorded prior to boot stage and classified as glabrous, intermediate and pubescent Leaf Auricle: This trait was observed at boot stage and classified as absent and present. 25

30 Auricle colour: It was observed at boot stage and classified as colorless, light purple and purple Ligule shape: In present investigation, this trait was recorded at boot stage and categorized as truncate, acute and split Ligule colour: This character was recorded at boot stage and classified as white, light purple and purple Flag Leaf: Attitude of blade- It was observed prior to boot stage and classified as erect, semi- erect, horizontal and drooping Spikelet: color of stigma- This trait was observed after panicle initiation and before milking stage and clasfied as white, light green, yellow, light purple and purple Stem: anthocyanin coloration of nodes- It was observed at milk stage and classified as present and absent Spikelet: density of pubescence- This character was observed during the ripening phase and classified as absent, weak, medium, strong and very strong Sterile lemma color: It was recorded during the ripening phase and classified as gold, straw, purple and red Spikelet: color of tip of lemma- This trait was recorded during the ripening phase and classified as white, yellowish, brown, red, purple and black Panicle: exsertion- This character was recorded during the ripening phase and classified as partly exserted, mostly exserted and well exserted. 26

31 Panicle: attitude of branches- It was recorded during the ripening phase and classified as erect, erect to semi-erect, semi-erect, semi-erect to spreading and spreading Panicle: awns- This trait was recorded during the ripening phase and classified as present and absent Panicle: distribution of awns- It was recorded during the ripening phase and classified as tip only, upper half only and whole length Panicle: color of awns- This character was observed during the ripening phase and classified as yellowish white, yellowish brown, brown, reddish brown, light red, red, light purple, purple and black Quantitative characters Days to 50 per cent flowering The number of days taken from sowing to heading in primary panicles in fifty percent plants was recorded Plant height (cm) Plant height was measured in centimeters from ground level to the tip of the panicle of the main culm excluding awns if any at the time of maturity. It can also be calculated from the following formula. Plant height (cm) = Culm length (cm) + Panicle length (cm) Number of tillers per plant Tillers were counted for each randomly selected five plants at the end of active tillering stage Number of effective tillers per plant Out of the total number of tillers per plant, ear-bearing tillers were counted at maturity Days to maturity The days from nursery to maturity is calculated. 27

32 Panicle length (cm) Panicle length was measured in centimeters from neck node of the panicle to the tip of the uppermost spikelet, excluding awns if any Average Panicle weight per plant (g). Total weight in grams of panicle was recorded after two days of sun drying Number of fertile spikelet per panicle One panicle from each plant was selected randomly and the total numbers of fertile/healthy spikelets were counted in number Number of sterile spikelet per panicle One panicle from each plant was selected randomly and the total numbers of sterile spikelets were counted in number Number of spikelet per panicle This was counted from main, average and smallest panicle for each of the plant selected Spikelet fertility per cent The fertility percentage will be calculated as follows: Total number of filled spikelets panicle -1 Fertility % = x 100 Total spikelets panicle Grain weight (g) One thousand sound filled grains were sun dried up to 12 % moisture level, were weighed in grams Spikelet density It is calculated by using the following formula: Total number of spikelets panicle -1 Spikelet density = Length of panicle (cm) 28

33 Biological yield per plant (g) Weight in grams of plants after harvesting from ground level (excluding roots) and sun drying was recorded in grams Grain yield per plant (g) Individual plant was hand threshed, cleaned, dried up to 12 % moisture level and weighed in grams Harvest Index (%) It was worked out by using the following formula: Seed yield plant -1 (g) Harvest index = x 100 Biological yield plant -1 (g) Panicle Index It was calculated by using the following formula: Grain yield plant -1 (g) Panicle index = x 100 Panicle weight plant -1 (g) Quality traits Observations on quality trait were recorded for all 149 lines Decorticated Seed length: Ten randomly selected grains were arranged from tip to tip on a graph paper and the total length in millimeter was recorded. Total length was divided by number of grains to calculate mean length of individual grain and classified as extra long (more than 8 mm), Medium ( mm) and Short (less than 5 mm) Decorticated Seed width: Ten randomly selected grains were arranged side by side on a graph paper and grain width was recorded in millimeter. Total width was divided by number of grains to calculate mean width of individual grain in millimeter and classified as bold (more than 2.5 mm), medium ( mm) and narrow (less than 2.00 mm). 29

34 Hulling percentage: Properly cleaned 100 g paddy sample was dehusked using a huller and weight of hulled rice was recorded. Hulling percentage = Milling percentage Weight of hulled kernel Weight of paddy x 100 Brown rice was put into standard miller for polishing and milled rice weight was recorded. Milling percentage = Weight of polished kernel Weight of paddy x Length and breadth ratio (L:B) It was calculated by the following formula L/B Ratio = Length of milled grain Breadth of milled grain 3.3 Statistical analysis The data in respect of various characters studied were subjected to the following analysis: Characterization of each genotype based on morphological observation Analysis of variance Estimation of mean, range, genotypic and phenotypic coefficient of variation, heritability, expected genetic advance and genetic advance as percentage of mean Estimation of phenotypic and genotypic correlations Path coefficient analysis. 30

35 3.3.1 Characterization of each genotype based on morphological observation All the qualitative characters showing discrete variation were analyzed and percentage frequency of different classes of characters was recorded, to know which particular trait was predominant amongst the lines studied. Genotypes will be characterized as per DUS guidelines Analysis of variance The data on quantitative characters were statistically analyzed on the basis of model described by Cochran and Cox (1950) for randomized complete block design. In order to test the significance of treatments Critical difference was computed (Fisher and Yates, 1963). Y ij = μ + b i + t j + e ij Where, Y ij Μ b i t j e ij = Performance of j th genotype in i th block = General mean = True effect of i th block = True effect of j th treatment = Random errors which are supposed to be identically and independently distributed with normal distribution having mean zero and variance σ 2 e Table 2: ANOVA table for Randomized Block Design Source of variation d.f. Sum of squares Mean squares Expected mean squares Replication (r-1) S.S. due to replication M 1 σ 2 e+ g σ 2 r Genotypes (g-1) S.S. due to genotypes M 2 σ 2 e+rσ 2 g Error (r-1)(g-1) S.S. due to error M 3 σ 2 e Total (rg-1) 31

36 1. Genotypic variance (σ 2 g) = 2. Phenotypic variance (σ 2 p) = + M 3 3. Environmental variance(σ 2 e) = Where, r = number of replications g = number of genotypes M 1 = mean square due to replication M 2 = mean square due to genotypes M 3 = mean square due to error Parameters of genetic variability Mean Mean is calculated by the following formula: Xi X= N Where, X = Sum of all the observations of i th traits N = Total number of observations Range Range is the difference between the smallest and the greatest term of a series of observation and thus provides the information about the variability present in the genotypes Genotypic and phenotypic coefficient of variation Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were calculated by the method suggested by Burton (1952). 32

37 Phenotypic coefficient of variation (PCV) σ 2 p = σ 2 g + σ 2 e P C V = (σ p / X ) x 100 where σ p = 2 p Genotypic coefficient of variation (GCV) G C V = (σ g / X ) x 100 where σ g = 2 g Where, σ 2 p σ p σ 2 g σ g σ 2 e X = Phenotypic variance = Phenotypic standard deviation = Genotypic variance = Genotypic standard deviation = Environmental variance = General Mean The estimates of PCV and GCV were classified as low, moderate and high according to Sivasubramanian and Madhavamenon (1973). < 10 per cent = low per cent = moderate > 20 per cent = high Heritability It is the ratio of genotypic variance to the total phenotypic variance. Heritability for the present study was calculated in broad sense by adopting the formula as suggested by Hanson et al., (1956). Where, h 2 (b) = Heritability in broad sense 2 g h 2 (bs) % = x p 2 g 2 p = Genotypic variance = Phenotypic variance 33

38 Expected genetic advance Improvement in the mean genotypic value of selected plants over the parental population is known as genetic advance. Expected genetic advance was calculated by the method suggested by Johnson et al., (1955). Where, GA = Genetic Advance G A = K. σ p. h 2. (bs) K = Constant (Standard selection differential) having the value of 2.06 at 5 per cent level of selection intensity h 2 = Heritability of the character σ p = Phenotypic standard deviation Genetic advance as percentage of mean It was calculated by the following formula: Genetic advance GA as percentage of mean = x 100 General mean GA was categorized as: < 10 per cent = low per cent = moderate >20 per cent = high Correlation coefficient Correlation coefficients were calculated for all quantitative characters combinations at phenotypic, genotypic and environmental level by the formula given by Miller et al., (1958). CovX X i j r XiXj= (VarX i ). (VarX j ) 34

39 Where, rx j X j = Coefficient of correlation between X th i and X th j traits Cov X i X j = Covariance between X th i and X th j traits Var X i = Variance of X th i trait VarX j = Variance of X th j trait Genotypic, phenotypic and environmental correlations were computed by substituting corresponding variance and covariance in the above formula. The estimation of covariance between two traits was derived in the same way as for corresponding variance components Path coefficient analysis The direct and indirect contribution of various characters to yield were calculated through path coefficient analysis as suggested by Wright (1921) and elaborated by Dewey and Lu (1959). The following set of simultaneous equations were formed and solved for estimating direct and indirect effects. r 1 Y = P 1 Y + r 12 P 2 Y + r 13 P 3 Y +. + r 1k P k Y r 2 Y = r 21 P 1 Y + P 2 Y + r 23 P 3 Y + + r 2k P k Y r k Y = r k1 P 1 Y + r k2 P 2 Y + r k3 P 3 Y +. + P k Y Where, r 1 Y to r k Y = Coefficients of correlation between causal factors 1 to k and independent character Y P 1 Y to P k Y r 12 to r k-1, 1 = Direct effects of characters 1 to k on character Y = Coefficient of correlation among causal factors The above equations were written in a matrix form as under A C B r Y k 1 r Y 1 r r r = r 1 r r p Y p Y k 2 r Y k r r r 1 k1 k2 k3 p Y k 35

40 Then, B=[C] 1.A Where, C C C C C k C C C C k Ck1 Ck2 Ck3 Ck k Then direct effects were calculated as follows -- P Y= k C r Y 1 1k k i=1 P Y= k C r Y 2 2k k i=1 P Y= k k i=1 C r Y ki k Residual effect was obtained as per for formula given below R= 1- dirij Where, d i = Direct effect of the i th character r ij = correlation coefficient of the i th character with j th character Later the path coefficients were rated based on the scales given below (Lenka and Mishra, 1973). >1.00 = Very high = High = Moderate = Low = Negligible 36

41 (B) At Molecular level Source of Biological Material For the molecular analysis, 15 lines of Aromatic Network Project lines were utilized in this programme selected on the basis of L/B ratio and all of the source materials were obtained from Seed Breeding Farm, JNKVV, Jabalpur. Table 3: Details of selected lines included for molecular analysis S. No. GENOTYPES 1 IR SUGANDA MATI 3 IR KRISHNA KAMOD 5 IET MUGAD SUGANDHA 7 IR UPR IR PUSA BASMATI 6 11 IET IR ANP BASMATI MOHAN IR Germination of Seeds for DNA Extraction Healthy seeds with identical dimensions were selected by visual observation and dipped in distilled water overnight. The floating, chaffy and nonviable light grains were sorted out and discarded. The healthy seeds were kept in distilled sterilized water and after that seeds were placed in petri plates and then kept in germinator at 35 C for germination. Watering was done twice a week for proper emergence of radical and plumule. After two weeks, the etiolated leaves were harvested using a sharp sterilized blade. Leaves surface were sterilized with 70% ethanol followed by sterilized water. 37

42 3.4.3 Collection of samples Green young and healthy leaves from ten plants of each line (Table3) were collected in the morning hours from the petri plates for extraction of DNA. The collected samples were placed in cooling pads to transfer and then stored at 80 0 C Isolation of DNA For genomic DNA extraction, the following chemicals were used with molecular biology grade or analytical grade (Promega Co. USA). Cetyl-trimethyl ammonium bromide (CTAB): C-TAB (2g) as detergent was used for 100ml DNA extraction buffer to break cell wall and remove impurities from leaf samples. 1M Trizma-base (ph 8.0):Trizma base 30.28g (MW = 121.1g) was dissolved in 200 ml of distilled water. The ph was adjusted to 8.0 with concentrated HCI. The final volume of the solution was made up to 250ml with distilled water before autoclaving. The solution was stored at room temperature (25 C) after autoclaving. Trizma-base ensures the ph of the buffer solution. 0.5M EDTA (Disodium ethylenediaminetetraacetate) (ph 8.0):EDTA (46.53g, MW = 372.2g) was added to 200ml of distilled water. It was stirred vigorously with a magnetic stirrer and maintained ph 8.0 using NaOH pallets and concentrated NaOH solution. The final volume of the solution was made up to 250ml with distilled water before autoclaving. The solution was stored at room temperature (25 C) before final adjustment of the ph after autoclaving. EDTA perform as chelating agent that help to remove several kinds of divalent metal cations such as Mg 2+ and Ca 2+ act as co-factor for the majority of DNases which degrades DNA. 5M NaCl:NaCl (73.05g,MW = 58.44g) was dissolved in 200ml and stirred vigorously with a magnetic stirrer. The final volume was adjusted to 250ml with distilled water before autoclaving. The solution was stored at room temperature (25 C) after autoclaving. NaCl is a salt 38

43 that increases the solubility of DNA in the buffer solution and also increases the osmotic ability of the buffer and hence facilitates the process of cell lysis. Chloroform: isoamyl alcohol mixture: This is used in the proportion of 24:1 to remove proteins by denaturing and they aggregate in the intermittent phase along with cell debris. Isopropanol: It is used in equal volume to DNA extraction buffer for DNA precipitation. RNase (10mg/ml): RNase (~100mg) was dissolved in 10ml of sterile distilled water in a sterile 15ml centrifuge tube. It was dispensed into sterile 1.5ml micro-centrifuge tubes and stored at 20 C. The RNA is removed by RNase treatment at 37 C.sss 70% ethanol: The pellet is washed with 70% ethanol for removing any salts retained after precipitation. DNA extraction buffer: The buffer was prepared as per specification given in the Table 4. Table 4: Composition of DNA extraction buffer (100ml) S. No. Chemicals Final Concentration Working volume 1. TrisHCl (ph 8.0), 1M 100mM 10ml 2. EDTA (ph 8.0), 0.5M 20mM 4ml 3. β Mercaptoethanol 0.1% 100µl 4. NaCl, 5M 1.4M 28ml 5. CTAB 2% 2g β-mercaptoethanol(100µl) was added just prior to placement of DNA extraction buffer in water bath for incubation. The technique of DNA isolation relied upon the fact that nucleic acid would form suitable complex with detergent cetyl trimethylammonium bromide (CTAB) under high salt concentration and when the concentration reaches 1.4M NaCl to form the CTAB-Na complex. Genomic DNA wasisolated using 39

44 Saghai-Maroof et al. (1984) method with some modifications.the methodutilized and described below gives a good quality and quantity of DNA. 1. Leaf sample (2g) was weighed and homogenized in 2ml CTAB buffer (preheated to 65 º C) using a pre-chilled pestle and a mortar. 2. The fine paste was transferred to a 2ml centrifuge tube and mixed thoroughly. 3. The samples were incubated in a water bath at 65 º C for 40 minutes. During incubation, the samples were gently shaked after every 10min. 4. After incubation the samples were taken out from the water bath and allowed to cool down at room temperature. 5. The sample tubes were then centrifuged for about 15min at 10,000rpm at room temperature. 6. Supernatant obtained and transferred to a 1.5ml fresh tube. 7. Then an equal (to supernatant) volume of chloroform: isoamyl alcohol (24:1 v/v) was added and mixed thoroughly but gently for not less than 5 min. 8. The mixture was then centrifuged for about 15 min at 10,000rpm at room temperature. 9. Supernatant again obtained and transferred to a 1.5ml fresh tube. 10. An equal (to supernatant) volume of pre-chilled isopropanol was added and mixed gently by inverting tubes and kept for 20 min undisturbed. 11. The DNA precipitate was then spooled out using 1ml cut tips and transferred to a 1.5ml micro-centrifuge tube. 12. DNA was again pelleted by centrifugation at 10,000rpm for 10min. 13. The supernatant was now discarded and pellet was washed twice with 70% ethanol. 14. The pellet was dried up at room temperature and dissolved in 200µl of M.Q (Milli Q) water for further use. 40

45 3.4.5 DNA purification The purification of DNA was carried out in order to remove the impurities like RNA, proteins and polysaccharides. These are considered as inhibitors in DNA amplification during PCR. 1. 5µl of RNAase (5mg.ml -1 ) was added to DNA extract, mixed well and incubated at 37 º C for 40 min. 2. This was followed by the addition of equal volumes of chloroform: isoamyl alcohol (24:1 v/v) and mixed vigorously. 3. The above mixture was centrifuged at 10,000rpm for 15 min. 4. Supernatant was transferred to a 1.5ml fresh micro-centrifuge tube and 1/10 volume of 3M sodium acetate (ph 5.4) was added followed by further addition of two volumes of pre-chilled isopropanol mixed gently for DNA precipitation. 5. The precipitated DNA was pelleted by centrifugation at 10,000 rpm for 15 min. 6. The pellet was dried at room temperature to completely remove ethanol and was then dissolved in 100µl of water (M.Q.) and stored at - 20 º C for further use Quantification of DNA Quality of DNA was determined by horizontal submarine gel electrophoresis on 0.8% agarose gel. Purity of DNA was checked by taking the ratio of optical density (OD) using spectrophotometer, at 260 nm to that of 280 nm. The samples with OD ratio (260nm/280nm) between were used in subsequent experiments. DNA samples showing the values beyond this range were re-purified. Isolated DNA was quantified in UV spectrophotometer at 260 and 280nm. 50ng/ml concentrated solution of double stranded DNA showed absorbance of 1 at 260nm. DNA concentration of sample was calculated as: OD 260 x 50 µg DNA/ ml x D.F. /

46 S. No. Table 5: List of sequences of ten SSR markers Marker Forward sequence Reverse sequence Character associated Chromoso me no. 1 RM201 5'-CTCGTTTATTACCTACAGTACC-3' 5'-CTACCTCCTTTCTAGACCGATA-3' Drought tolerance 9 2 RM223 5'-GAGTGAGCTTGGGCTGAAAC-3' 5'-GAAGGCAAGTCTTGGCACTG-3' Aroma 8 3 RM234 5'-ACAGTATCCAAGGCCCTGG-3' 5'-CACGTGAGACAAAGACGGAG-3' Grain protein 7 4 RM236 5'-GCGCTGGTGGAAAATGAG-3' 5'-GGCATCCCTCTTTGATTCCTC-3' Panicle number 11 5 RM256 5'-GACAGGGAGTGATTGAAGGC-3' 5'-GTTGATTTCGCCAAGGGC-3' Panicle length 8 6 RM259 5'-CCCTCCCTTCTGTAAGCTCC-3' 5'-GAAGAACAATGGGGTTCTGG-3' Grain length 1 7 RM276 5'-CTCAACGTTGACACCTCGTG-3' 5'-TCCTCCATCGAGCAGTATCA-3' Amylose content 6 8 RM42 5'-ATCCTACCGCTGACCATGAG-3' 5'-TTTGGTCTACGTGGCGTACA-3' Amylose content 6 9 RM468 5'-CCCTTCCTTGTTGTGGCTAC-3' 5'-TGATTTCTGAGAGCCACCCC-3' Kernel width 3 10 RM502 5'-CTGGTTCTGTATGGGAGCAG-3' 5'-CTGGCCCTTCACGTTTCAGTG-3' Plant height 8 42

47 3.4.7 Stock buffers were prepared with following concentrations (Table 6) Table 6. Reaction mixture for PCR to detect SSR markers S.No. Components Concentration Working volume 1 10X PCR buffer 2µl 2.0µl 2 MgCl 2 1.5mM 0.7µl 3 DNTPs 100µM 0.1µl 4 Primer 10pmol 1.0µl 5 Taq Polymerase 1unit 0.1µl 6 DD H 2 O - 5.1µl 7 DNA 50ng 1.0µl Table 7.Temperature profile used in PCR Amplification for SSR Steps Temperature Duration Cycles Activity º C 4min 1 Initial Denaturation º C 30sec Denaturation º C 30sec 35 Annealing º C 30sec Elongation º C 5min 1 Final elongation 6. 4ºC 1hrs Storage 43

48 3.4.8 Dilution of DNA The quantified DNA was diluted according to the DNA quantity in each sample for PCR amplification in sterile double distilled water. Dilutions were carried out according to the following formula: Dilution= Required concentration of DNA (ng/µl) X Total volume required (µl) Available concentration of DNA (ng/µl) DNA analysis of simple sequence repeats SSRs are co-dominant markers that target single loci in the genome and can easily and economically assay by PCR. In the present study, polymorphism was analyzed among rice cultivars using SSR markers Sources of SSR markers The sequences of a total of fifteen SSR primer pairs (Table 5) were synthesized from IDT USA (Promega) PCR condition for (SSR) markers PCR conditions were standardized considering different parameters viz. initial denaturation, denaturation, annealing, extension and final extension using Thermo Hybrid (Px2) PCR Machine. PCR profile was optimized for amplification by using primers of unique sequencewith higher GC ratio at high stringency. The optimized conditions are presents in the Table Data analysis The PCR products for SSR were resolved on agarose electrophoresis to generate microsatellite fingerprints. The products were stained by ethidium bromide and visualized under UV in Syngene Gel Documentation System. Band size was estimated using 100bp ladder. PowerMarker version 3.25 was used to calculate the average number of alleles, gene diversity, and polymorphic information content (PIC) values. Phlylogenetic tree was generated on the basis of neighbor-joining method implemented in PowerMarker. ( 44

49 RESULTS The present investigation was carried out on 149 genotypes of aromatic lines of rice to select the better lines, to know the genetics and for this morphological (seventeen), biometrical (eighteen) and quality (seven) traits are taken in randomized complete block design with three replications at Seed Breeding Farm, JNKVV, Jabalpur. To get a clear picture of variability in genotypes, the genetic parameters of variability were studied. Correlation analysis was performed to find out the degree of relationship between characters. Path analysis was conducted to know the direct and indirect effects of various independent characters on dependent one. The ANP lines were characterized based on the classical taxonomical approach; involving detailed observations on morphological description of seeds, flowers and inflorescence. The experimental results of the present investigation have been given under the following heads: 4.1 Characterization 4.2 Analysis of variance 4.3 Parameters of genetic variability Range and mean performance for different characters Genotypic and phenotypic coefficient of variation Heritability and Genetic advance 4.4 Correlation analysis 4.5 Path coefficient analysis 4.6 Molecular analysis 4.1 Characterization The frequency distributions of seventeen morphological characters (discontinuous variable) are summarized in Table 8. 45

50 Basal leaf sheath color: Genotypes were categorized based on basal leaf sheath color at vegetative phase and classified as Green, Purple lines, Light purple and Purple. Green color was observed in 88.59% of genotypes followed by purple lines (7.38%), light purple (2.01%) and purple (2.01%). Leaf: pubescence of blade surface: All the genotypes belonged to the glabrous category (100%). Table 8. Frequency Distribution of Morphological Characters in Rice Genotypes S. No. Character Classes 1 Basal leaf sheath color 2 Leaf: pubescence of blade surface 3 Leaf: auricles 4 Leaf: anthocyanin colouration of auricles 5 Leaf: shape of ligules 6 Leaf ligule color 7 Flag leaf: attitude of blade 8 Stem: anthocyanin coloration of nodes 9 Spikelet : color of stigma Number of entry /Frequency Percentage of entry (%) Green Purple lines Light purple Purple Glabrous Intermediate Pubescent Absent Present Colorless Light purple Purple Truncate Acute Split White Light purple Purple Erect Semi-erect Horizontal Drooping Absent Present White Light green Yellow Light purple

51 10 Spikelet : density of pubescence 11 Sterile lemma color 12 Spikelet: color of tip of lemma 13 Panicle: exsertion 14 Panicle: attitude of branches 15 Panicle: awns 16 Panicle: distribution of awns 17 Panicle: color of awns Purple Absent Weak Medium Strong Very strong Straw Gold Red Purple White Yellowish Brown Red Purple Black Partly exserted Mostly exserted Well exserted Erect Erect to semierect Semi-erect Semi-erect to spreading Spreading Absent Present Tip only Upper half Whole length Yellowish white Yellowish brown Brown reddish brown Light red Red Light purple Purple Black

52 Leaf: auricles: All the genotypes have auricles present (100%). Leaf: anthocyanin coloration of auricles: Most of the genotypes have colorless auricles i.e., (91.94%) followed by purple (6.71%) and light purple (1.34%). Leaf: shape of ligules: In all the genotypes, the shape of ligule was split (100%). Leaf ligule colour: Most of the genotypes (97.9%) consist of white ligule followed by purple (1.34%), thereby light purple (0.67%). Flag leaf: attitude of blade: Semi-Erect leaf angle was exhibited by 44.96% of genotypes followed by erect (42.28%), horizontal (9.39%) and drooping (3.35%). Stem: anthocyanin coloration of nodes: Most of the genotypes (95.9%) showed absence of nodes coloration and only 4.02% had anthocyanin coloration in nodes. Spikelet : colour of stigma: Maximum no. of genotypes (71.14%) had white color stigma followed by purple (12.75%), yellow (8.72%), light green (4.69%) and light purple (2.68%). Spikelet : density of pubescence: Most of the (44.29%) genotypes showed weak density of pubescence followed by medium (40.26%) and strong (14.09%), while 6% had very strong pubescent density and rest 6 per cent of genotypes had no pubescence. Sterile lemma colour: The genotypes (80.53%) exhibited straw color followed by purple (10.07%), gold (8.05%) and red (1.34%). Spikelet: colour of tip of lemma: White color was found in 56.37% of genotypes, followed by purple (18.12%), yellowish (14.09%), red (5.36%), brown (4.69%) and black (1.34%). Panicle: exsertion: Most of the genotypes had well exserted panicle (76.51%) followed by mostly exserted (18.79%) and partly exserted (4.69%). 48

53 Panicle: attitude of branches: Maximum genotypes (71.81%) showed erect to semi-erect type branches followed by semi-erect to spreading type (15.43%), erect (8.72%), semi-erect and spreading both, 2.01%. Panicle: awns: In 77.18% of genotypes awn was present, while rest of 22.82% showed absence of awns. Panicle: distribution of awns: The genotypes (61.07 %) had awns only at tip, 20.13% showed awns in whole length and rest of genotypes (18.79%) showed awns in upper half only. Panicle: colour of awns: Most genotypes (42.95%) exhibited yellowish white awns followed by reddish brown (20.13%), yellowish brown (9.39%), purple (8.72%), black (6.04%), red (5.36%) and brown (4.02%). 4.2 Analysis of variance: Analysis of variance refers to the observable differences in individuals for a particular trait. To know the extent of variation of observed characters among the 149 aromatic rice lines, analysis of variance was performed and presented in Table 9 and Table 10. Analysis of variance indicated that the mean sum of squares due to genotypes were significant for all the characters which revealed that there was considerable genetic variability amongst the material under study. Considerable amount of variability was observed for all the yield and quality attributing traits. Maximum variability was observed for total number of spikelet per panicle and lowest for decorticated seed width. The magnitude of variability in decreasing order for the traits i.e., number of spikelet per panicle, total filled spikelet per panicle, sterile spikelet per panicle, plant height, culm length, biological yield, panicle index, spikelet fertility per cent, days to 50% flowering, days to maturity, harvest index, panicle weight per plant, grain yield, 1000 grain wt., hulling per cent, milling per cent, total tillers per plant, productive tillers per plant, average panicle length, spikelet density, grain length, decorticated grain length, grain width and decorticated grain width. 49

54 Table 9. ANOVA for yield, yield and quality attributing traits in Aromatic Rice Lines S. Source of d.f. Mean sum of squares No variation ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL 1. Replication Genotypes Error S. Source of d.f. Mean sum of squares No. variation PH BYld PWt SD SF HI PI DTFF DTM H% M% GYld 1. Replication Genotypes Error

55 4.3 Parameters of genetic variability To predict genetic variability in the population, various parameters were estimated viz., range, mean, genotypic and phenotypic coefficient of variance, heritability, genetic advance for yield and quality attributing traits, are presented in table Range and mean performance of different characters studied The variation of different traits under study revealed the measure of free variability in the population of different genotypes which would reflect the unforeseen impact of potential variability on yield. The performance of the varieties was evaluated by the mean performance of the observed traits. It compares the varieties for specific characters. Mean performances of all the observed traits are presented in table 10. Culm length: It varied from 47.42cm to cm with a mean value of cm. Panicle length: The panicle length varied from 19.63cm to 32.63cm with a mean value of 26.69cm. Total number of tillers per plant: It varied from 6.17 to 30.00with a mean value of Total number of productive tillers per plant: This character varied from 6.16 to 25.67with a mean value of Total number of spikelet per panicle: It varied from to with a mean value of Total number of filled spikelet per panicle: This trait varied from to with a mean value of Total number of unfilled spikelet per panicle: It varied from 7.67 to with a mean value of

56 1000 grain weight: This character varied from 4.33g to 31.00g with a mean value of 19.85g. Seed length: This trait varied from 0.44 cm to 0.97cm with a mean value of 0.81cm. Seed width: It varied from 0.16cm to 0.34cm with a mean value of 0.23cm. Decorticated seed width: This character varied from 0.13cm to 0.34cm with a mean value of cm. Decorticated seed length: It varied from 0.24cm to 0.95cm with a mean value of 0.61cm. Plant height: This trait varied from 74.25cm to cm with a mean value of cm. Biological yield per plant: It varied from 30.26g to g with a mean value of 78.85g. Panicle weight: This character varied from 7.14g to 61.17g with a mean value of 27.30g. Spikelet density: It varied from 3.83 to with a mean value of Spikelet fertility per cent: This trait varied from 14.46% to 93.11% with a mean value of 73.05%. Harvest index: It varied from 4.57% to 97.12% with a mean value of 23.27%. Panicle index: Panicle index varied from 24.37% to 94.11% with a mean value of 65.80%. 52

57 Days to 50% flowering: In the present study this character varied from 78.00days to days with a mean value of days. Days to maturity: It varied from 111days to 160days with a mean value of days. Hulling per cent: This trait varied from 55.08% to 75.33% with a mean value of 65.50%. Milling per cent: This character varied from 51.06% to 67.49% with a mean value of 60.85%. Grain yield per plant: It varied from 3.38g to 50.21g with a mean value of 18.42g Genotypic and phenotypic coefficient of variation The phenotypic coefficient of variation was higher in magnitude than that of genotypic coefficient of variation for all the characters studied. Phenotypic variance refers to the total or observable variation in a population. It is the sum of genotypic and environmental variance. Genotypic variance is the heritable portion of total variance. It gives the variation between the genotypes. Environmental variance is the non-heritable portion of the total variance. It gives the variation within the genotypes. To get a clear picture of variability among the lines under study coefficient of variation was calculated. The ratio of standard deviation of a sample to its mean is expressed in percentage is called as coefficient of variation. Phenotypic coefficient of variation is phenotypic standard deviation into 100 divided by its mean. Genotypic coefficient of variation is genotypic standard deviation into 100 divided by its mean. The phenotypic coefficient of variation was higher in magnitude than that of genotypic coefficient of variation for all the characters under study. The genotypic and phenotypic coefficients of variation (%) for all the traits under study were analyzed and results are furnished in table

58 Culm length: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) observed for this trait were and , respectively. Panicle length: This character exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates of and , respectively. Total number of tillers per plant: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Total number of productive tillers per plant- This character shown genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Total number of spikelet per panicle- Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Total number of filled spikelet per panicle- It exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates of and , respectively. Total number of unfilled spikelet per panicle- Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively grain weight- This character shown genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) of and , respectively. 54

59 Seed length: In this study genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were , , respectively. Seed width: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Decorticated seed width- This character exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates of and , respectively. Decorticated seed length- Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Plant height- It exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates of and , respectively. Biological yield per plant- In this study genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed were and , respectively. Panicle weight- Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Spikelet density- This character exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) of and , respectively. Spikelet fertility per cent- In this study genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed were and , respectively. 55

60 Table 10 Genetic Parameters of Yield Attributing Characters of Aromatic Rice Lines S. Range Coefficient of variation h 2 (b) Genetic Genetic Advance Traits Mean No. Max. Min. GCV (%) PCV (%) ( %) Advance as % of Mean 1 ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL PH BYld PWt SD SF HI PI DTFF DTM H% M% GYld

61 Harvest index: This character exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates were and , respectively. Panicle index: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Days to 50% flowering: In this study genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Days to maturity: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Hulling per cent: It exhibited genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) of and , respectively. Milling per cent: Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates observed for this trait were and , respectively. Grain yield per plant: In this study genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) estimates were and , respectively Heritability and Genetic Advance Heritability measures the contribution of genetic variability to the phenotypic variability observed for quantitative traits and it is good index for the transmission of characters from parents to their offspring. The estimate of 57

62 heritability can be utilized for the prediction of genetic gain, which indicates the genetic improvement that would result from the selection of best individuals. Hence, estimate of heritability is an essential pre-requisite for formulation of an effective selection method for genetic improvement. The estimates of heritability in broad sense were found highest for No. of spikelet per panicle (99.91%) followed by very high estimates for fertile spikelet per panicle (99.90%), culm length (99.86%), sterile spikelet per panicle (99.80%), biological yield (99.71%), days to 50% flowering (99.52%), days to maturity (99.32%), panicle index (99.04%), spikelet fertility (98.98%), harvest index (98.23%), grain yield (97.45%), panicle weight (97.00%), test weight (97.10%), hulling % (95.70%), milling % (95.44%), panicle length (99.04%) and spikelet density (93.18%). The estimates of heritability were moderate for six characters i.e. Grain length (87.49%), decorticated grain length (87.49%), grain width (85.89%), decorticated grain width (85.89%), total tiller per plant (84.27%) and productive tiller per plant (83.00%) (Table no. 10). Genetic advance as percentage of mean were recorded for yield and quality traits. The estimate of genetic advance as percentage of mean at five per cent selection intensity as presented in table 10, record were highest for Sterile spikelet per panicle ( ) followed by harvest index ( ), grain yield ( ), panicle weight ( ), fertile spikelet per panicle ( ), biological yield ( ), spikelet density ( ), no. of spikelet per panicle ( ), total tiller per plant ( ), productive tiller per plant ( ), test weight ( ), culm length ( ), panicle index ( ). Moderate estimates of genetic advance were observed for Plant height ( ), spikelet fertility per cent ( ), grain length ( ), decorticated grain length ( ), decorticated grain width ( ), grain width ( ), days to 50% flowering ( ), panicle length ( ), days to maturity ( ). Remaining only two traits hulling per cent ( ) and milling per cent ( ) denoted low genetic advance as percentage of mean. (Table no. 10) 58

63 Heritability estimates along with genetic advance are normally more helpful in predicting the gain under selection than heritability estimates alone. However, it is not necessary that a character showing high heritability will also exhibit high genetic advance. The heritability estimates along with genetic advance, in present study, were categorized in table 11. Table 11. Heritability estimates with Genetic Advance Characteristics High Heritability with High Genetic Advance High Heritability with Moderate Genetic Advance High Heritability with Low Genetic Advance Moderate Heritability with High Genetic Advance Moderate Heritability with moderate Genetic Advance fertile spikelet per panicle, spikelet per panicle, culm length, harvest index, biological yield, panicle index, spikelet density, test weight Plant height, Spikelet fertility %, Days to 50% flowering, Panicle length, Days to maturity Hulling %, Milling % Total tiller per plant, Productive tiller per plant Grain length, Decorticated grain length, Grain width, Decorticated grain width In this study high heritability with high genetic advance was observed for the characters fertile spikelet per panicle, spikelet per panicle, culm length, harvest index, biological yield, panicle index, spikelet density and test weight. High heritability with moderate genetic advance was also found for plant height, spikelet fertility per cent, days to 50% flowering, panicle length and days to maturity. While high heritability with low genetic advance was noticed for the characters hulling per cent and milling per cent. Moderate heritability with high genetic advance was found for the characters total tillers per plant and productive tillers per plant. Whereas moderate heritability with moderate genetic advance was observed for the characters grain length, decorticated grain length, grain width and decorticated grain width. 59

64 4.4 Correlation analysis Phenotypic and genotypic correlations for various yield and quality attributing traits were estimated with grain yield per plant as dependent variable. The result revealed higher estimate of phenotypic correlation coefficient than genotypic correlation coefficient for almost all the characters studied. The findings of present investigation are furnished in table 12. Culm length: Culm length had significant positive association with plant height (0.9941), biological yield (0.3998), spikelet no. per panicle (0.3105), panicle length (0.2792), fertile spikelet no. per panicle (0.2066), sterile spikelet no. per panicle (0.1885), spikelet density (0.1654), grain width (0.1407), decorticated grain width (0.1407), days to 50 % flowering (0.0798), hulling % (0.0772), days to maturity (0.0564), panicle index (0.0489), milling% (0.0437), total tillers per plant (0.0433) and productive tillers per plant (0.0310). It also showed a significant and negative association with decorticated grain length ( ), grain length ( ), harvest index ( ), test weight ( ), panicle weight ( ) and spikelet fertility % ( ). Panicle length: It had significant positive association with plant height (0.3791), grain length (0.3539), decorticated grain length (0.3539), test weight (0.2847), culm length (0.2792), biological yield (0.2069), total tillers per plant (0.1552), productive tillers per plant (0.1375), spikelet fertility percentage (0.1236), panicle weight (0.1169), panicle index (0.1058) and fertile spikelet no. per panicle (0.0220). However, it showed a significant and negative association with spikelet density ( ), days to maturity ( ), days to 50% flowering ( ), grain width ( ), decorticated grain width ( ), milling % ( ), hulling % ( ), sterile spikelet no. per panicle ( ), spikelet no. per panicle ( ) and harvest index ( ). Total number of tillers per plant: This character had significant positive association with productive tiller per plant (0.9394), biological yield (0.5319), panicle weight (0.4172), panicle 60

65 length (0.1552) grain length (0.0622), decorticated grain length (0.0622), plant height (0.0578), spikelet fertility (0.0270), panicle index (0.0263), harvest index (0.0226), fertile spikelet no. per panicle (0.0177), test weight (0.0086), hulling % (0.0054), spikelet no. per panicle (0.0048) and milling % (0.0046). While it also showed a significant and negative association with spikelet density ( ), grain width ( ), decorticated grain width ( ), days to 50% flowering ( ), days to maturity ( ) and sterile spikelet no. per panicle ( ). Total number of productive tillers per plant: It showed significant positive association with total tillers per plant (0.9394), biological yield (0.5173), panicle weight (0.4857), panicle length (0.1375), grain length (0.0788), decorticated grain length (0.0788), harvest index (0.0551), plant height (0.0443), panicle index (0.0423), test weight (0.0285), fertile spikelet no. per panicle (0.0284), spikelet fertility (0.0216) and spikelet no. per panicle (0.0112). However, it showed a significant and negative association with grain width ( ), decorticated grain width ( ), days to maturity ( ), days to 50% flowering ( ), milling % ( ), hulling % ( ), sterile spikelet no. per panicle ( ) and spikelet density ( ). Total number of spikelet per panicle: Positive and significant association was observed with spikelet density (0.8847), fertile spikelet no. per panicle (0.7442), sterile spikelet no. per panicle (0.4660), culm length (0.3105), plant height (0.2894), days to maturity (0.2753), days to 50 % flowering (0.2703), biological yield (0.2430), milling % (0.1412), hulling % (0.1306), panicle weight (0.1133), panicle index (0.0441), grain width (0.0426) and decorticated grain width (0.0426). It also showed a significant and negative association with grain length ( ), decorticated grain length ( ), test weight ( ), spikelet fertility % ( ) and harvest index ( ). 61

66 Table 12 : Estimates of phenotypic correlation coefficient for various yield and quality attributing traits ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL ASL *** *** *** *** *** *** ** ** *** APL *** ** ** *** *** *** *** *** TT/P *** *** *** PT/P *** *** Sno./P *** *** *** *** *** FSno./P *** *** * * *** SSno./P *** *** *** TW *** ** ** *** GL * * *** GW *** * DGW * DGL PH BYld PWt SD SF HI PI DTFF DTM H% M% GYld *** *** *** * *** *** *** *** *** *** Significant at 5% and 1% level 62

67 Cont PH BYld PWt SD SF HI PI DTFF DTM H% M% ASL *** *** *** *** APL *** *** * *** ** * *** *** *** TT/P *** *** PT/P *** *** Sno./P *** *** * *** * *** *** ** ** FSno./P *** *** *** *** *** *** *** SSno./P *** *** *** *** *** *** *** *** *** *** TW *** *** *** *** *** ** *** *** * ** GL *** *** *** *** *** *** *** *** *** GW * * ** * DGW * * ** * DGL *** *** *** *** *** *** *** *** PH *** * *** BYld *** *** *** PWt *** *** *** ** * SD * *** *** ** *** SF *** *** *** *** ** ** HI *** *** *** * * PI *** ** *** *** DTFF *** * *** DTM ** H% *** M% GYld *** *** *** *** *** *** ***

68 Total number of filled spikelet per panicle: In present investigation, this character had significant positive association with spikelet no. per panicle (0.7442), spikelet density (0.6410), spikelet fertility % (0.5561), panicle weight (0.2853), panicle index (0.2422), biological yield (0.2207), culm length (0.2066), plant height (0.2010), harvest index (0.1703), grain width (0.0972), hulling % (0.0230), milling % (0.0201) and days to maturity (0.0078). However, It also showed a significant and negative association with sterile spikelet no. per panicle ( ), grain length ( ), decorticated grain length ( ), test weight ( ) and days to 50% flowering ( ). Total number of unfilled spikelet per panicle: This character exhibited significant positive association with spikelet no. per panicle (0.4660), spikelet density (0.4291), days to 50 % flowering (0.4005), days to maturity (0.3817), culm length (0.1885), milling % (0.1823), plant height (0.1682), hulling % (0.1624) and biological yield (0.0767). While, it also showed a significant and negative association with spikelet fertility % ( ), grain length ( ), decorticated grain length ( ), test weight ( ), harvest index ( ), panicle index ( ), fertile spikelet no. per panicle ( ), panicle weight ( ), panicle length ( ), grain width ( ) and decorticated grain width ( ) grain weight: This trait had significant positive association with grain length (0.5800), decorticated grain length (0.5800), harvest index (0.3310), biological yield (0.3222), panicle length (0.2847), spikelet fertility (0.2484), grain width (0.1287), decorticated grain width (0.1287), panicle index (0.1265) and plant height (0.0531). It also showed a significant and negative association with days to 50% flowering (0.4595), spikelet density (0.4114), days to maturity (0.4110), sterile spikelet no. per panicle ( ), spikelet no. per panicle ( ), culm length ( ), plant height ( ), milling % ( ) and hulling % ( ). 64

69 Seed length: Significant and positive association was observed with decorticated grain length (1.000), test weight (0.5800), panicle length (0.3539), spikelet fertility (0.2644), harvest index (0.2630), panicle weight (0.2022) and panicle index (0.0532). While, it showed a significant and negative association with spikelet density ( ), spikelet no. per panicle ( ), days to 50 % flowering ( ), sterile spikelet no. per panicle ( ), days to maturity ( ), culm length ( ), plant height ( ), milling % ( ), hulling % ( ), fertile spikelet no. per panicle ( ), grain width ( ), decorticated grain width ( ) and biological yield ( ). Seed width: This character had significant positive association with decorticated grain width (1.0000), hulling % (0.1486), culm length (0.1407), test weight (0.1287), milling % (0.1148), plant height (0.1141), spikelet density (0.0960), fertile spikelet no. per panicle (0.0960), spikelet fertility (0.0399), panicle index (0.0392), harvest index (0.0103), days to maturity (0.0076) and panicle weight (0.0025). It also showed a significant and negative association with total tillers per plant ( ), productive tillers per plant ( ), panicle length ( ), decorticated grain length ( ), days to 50 % flowering ( ) and biological yield ( ). Decorticated seed width: In the present investigation, this trait showed significant positive association with hulling % (0.1486), culm length (0.1407), sterile spikelet no. per panicle (0.1287), milling % (0.1141), panicle height (0.1141), fertile spikelet no. per panicle (0.0972), spikelet density (0.0960), spikelet fertility (0.0399), panicle index (0.0392), harvest index (0.0103), days to maturity (0.0076) and panicle weight (0.0025). While, it showed a significant and negative association with total tillers per plant ( ), productive tillers per plant ( ), panicle length ( ), decorticated grain length ( ), days to 50 % flowering ( ) and biological yield ( ). 65

70 Decorticated seed length: It had significant positive association with grain length (1.000), test weight (0.5800), panicle length (0.3539), spikelet fertility percentage (0.2644), harvest index (0.2630), panicle weight (0.2022) and panicle index (0.0532). However, a significant and negative association was also observed with spikelet density ( ), spikelet no. per panicle ( ), days to 50 % flowering ( ), sterile spikelet no. per panicle ( ), days to maturity ( ), culm length ( ), panicle height ( ), milling percentage ( ), hulling percentage ( ), fertile spikelet no. per panicle ( ) and grain width ( ). Plant height: Significant and positive association was observed with culm length (0.9941), biological yield (0.4075), panicle length (0.3791), spikelet no. per panicle (0.2894), fertile spikelet no. per panicle (0.2010), sterile spikelet no. per panicle (0.1682), grain width (0.1141) and spikelet density (0.1110). It also showed a significant and negative association with harvest index ( ), grain length ( ) and total tillers per plant ( ). Biological yield per plant: This character had significant positive association with total tillers per plant (0.5319), productive tillers per plant (0.5173), panicle weight (0.5063), sterile spikelet no. per panicle (0.4075), culm length (0.3998), spikelet no. per panicle (0.2430), fertile spikelet no. per panicle (0.2207), panicle length (0.2069) and spikelet density (0.1596). However, It showed a significant and negative association with harvest index ( ). Panicle weight: It exhibited significant positive association with biological yield (0.5063), productive tillers per plant (0.4857), total tillers per plant (0.4712), harvest index (0.4150), test weight (0.3222), fertile spikelet no. per panicle (0.2853), spikelet fertility percentage (0.2544), grain length (0.2022), panicle length (0.1169), spikelet no. per panicle (0.1133) and hulling percentage (0.1005).It also showed a significant and negative association with sterile spikelet no. per panicle ( ), days to 50 % flowering ( ) and days to maturity ( ). 66

71 Spikelet density: Spikelet density had significant positive association with spikelet no. per panicle (0.8847), fertile spikelet no. per panicle (0.6410), sterile spikelet no. per panicle (0.4291), days to maturity (0.3227), days to 50 % flowering (0.3173), culm length (0.1654), biological yield (0.1596), milling percentage (0.1560), hulling percentage (0.1474), panicle height (0.1110) and grain width (0.0960). While, it also showed a significant and negative association with grain length ( ), decorticated grain length ( ), panicle length ( ), test weight ( ) and spikelet fertility percentage ( ). Spikelet fertility per cent: In the present study, this trait showed significant positive association with fertile spikelet no. per panicle (0.5561), harvest index (0.3583), panicle index (0.3018), grain length (0.2644), decorticated grain length (0.2644), panicle weight (0.2544), test weight (0.2484) and panicle length (0.1236). It showed a significant and negative association with sterile spikelet no. per panicle ( ), days to 50 % flowering ( ), days to maturity ( ), milling percentage ( ), hulling percentage ( ), spikelet density ( ) and spikelet no. per panicle ( ). Harvest index: It had significant positive association with panicle index (0.4530), panicle weight (0.4150), spikelet fertility percentage (0.3583), test weight (0.3310), grain length (0.2630) and fertile spikelet no. per panicle (0.1703). However, It showed a significant and negative association with culm length ( ), sterile spikelet no. per panicle ( ), panicle height ( ), biological yield ( ), days to 50 % flowering ( ), days to maturity ( ), hulling percentage ( ) and milling percentage ( ). Panicle index: This character had significant positive association with harvest index (0.4530), spikelet fertility percentage (0.3018), fertile spikelet no. per panicle (0.2422), test weight (0.1265) and panicle length (0.1058). It showed a significant and negative association with sterile spikelet no. per panicle 67

72 ( ), hulling percentage ( ), milling percentage ( ), days to 50 % flowering ( ) and days to maturity ( ). Days to 50% flowering: It had significant positive association with days to maturity (0.9508), sterile spikelet no. per panicle (0.4005), spikelet density (0.3173), spikelet no. per panicle (0.2703), milling percentage (0.1625) and hulling percentage (0.1144). Significant and negative association was also observed with test weight ( ), grain length ( ), decorticated grain length ( ), spikelet fertility percentage ( ), panicle length ( ), harvest index ( ), panicle index ( ) and panicle weight ( ). Days to maturity: This trait exhibited significant positive association with days to 50 % flowering (0.9508), sterile spikelet no. per panicle (0.3817), spikelet density (0.3227), spikelet no. per panicle (0.2753) and milling percentage (0.1324). It also showed a significant and negative association with test weight ( ), grain length ( ), decorticated grain length ( ), spikelet fertility percentage ( ), panicle length ( ), harvest index ( ), panicle index ( ) and panicle weight ( ). Hulling per cent: This character had significant positive association with milling percentage (0.9455), sterile spikelet no. per panicle (0.1624), grain width (0.1486), decorticated grain width (0.1486), spikelet density (0.1474), days to 50 % flowering (0.1144), spikelet no. per panicle (0.1306) and panicle weight (0.1005). However, it showed a significant and negative association with panicle index ( ), grain length ( ), decorticated grain length ( ), panicle length ( ), spikelet fertility percentage ( ), test weight ( ) and harvest index ( ). Milling per cent: It had significant positive association with hulling percentage (0.9455), sterile spikelet no. per panicle (0.1823), days to 50 % flowering (0.1625), spikelet density (0.1560), spikelet no. per panicle (0.1412), days to maturity 68

73 (0.1324), grain width (0.1148) and decorticated grain width (0.1148). It also showed a significant and negative association with panicle index ( ), grain length ( ), decorticated grain length ( ), panicle length ( ), spikelet fertility percentage ( ), test weight ( ) and harvest index ( ). Grain yield per plant: In present investigation, this trait revealed significant positive association with panicle weight (0.7913), harvest index (0.5567), panicle index (0.4929), productive tillers per plant (0.4774), biological yield (0.4714), total tillers per plant (0.4478), spikelet fertility percentage (0.3590), fertile spikelet no. per panicle (0.3481), test weight (0.3470), grain length (0.2315), decorticated grain length (0.2315), panicle length (0.1667) and spikelet no. per panicle (0.1121). However, a significant and negative association was also observed with sterile spikelet no. per panicle ( ), days to 50 % flowering ( ) and days to maturity ( ). 4.5 Path coefficient analysis: It is a standardized partial regression coefficient, which splits the correlation coefficients into the measures of direct and indirect effects. It measures the direct and indirect contribution of various independent characters on a dependent character. For a replicated data, it is of three types, phenotypic, genotypic and environmental path coefficient. Phenotypic path coefficients are worked out from all possible phenotypic correlation coefficients among the various characters under study. Path coefficients that are worked out from all possible genotypic correlation coefficients of all the various characters under study constitute the genotypic path coefficients. Environmental path coefficients are worked out from all possible environmental correlation coefficients among various characters under study. Direct effect is the straightway effect of an independent character on a dependent one. Indirect effect is the effect of an independent character on the dependent one via other independent characters. Residual effect is the measure of the effect of other possible independent characters, which were not included in the study on the dependent character. 69

74 In general, the genotypic direct as well as indirect effects were higher in magnitude as compared to the phenotypic direct and indirect effects. The estimates of path coefficients for yield and quality attributing traits on grain yield are furnished in table 13. The result obtained from present investigation for direct and indirect effects are presented character wise as: Culm length: This character, under study, had positive direct effect on grain yield ( ), with positive indirect effect via decorticated grain length (9.3727), grain length (3.8727), harvest index (8.3731), panicle weight (1.3919) and spikelet fertility percentage (1.2104). Panicle length: Panicle length showed negative direct effect on milling percentage ( ), with positive indirect effect via spikelet density (0.2002), days to maturity (0.0990), days to 50 % flowering (0.0965), decorticated grain width (0.0937), grain width (0.0937), milling percentage (0.0778), hulling percentage (0.0731), sterile spikelet no. per panicle (0.0543), spikelet no. per panicle (0.0367) and harvest index (0.0093). Total number of tillers per plant: This trait had positive direct effect on grain yield (0.0361), with positive indirect effect via productive tillers per plant (0.0344), biological yield( ), panicle weight (0.0208), panicle length (0.0183), panicle height (0.0023), grain length (0.0022), decorticated grain length (0.0022), culm length (0.0017), spikelet fertility percentage (0.0011), panicle index (0.0011), harvest index ), fertile spikelet no. per panicle (0.0006), test weight (0.0005), milling percentage (0.0003), spikelet no. per panicle (0.0002) and hulling percentage (0.0002). Total number of productive tillers per plant: It had negative direct effect on grain yield ( ), with positive indirect effect via grain width (0.0206), decorticated grain width(0,0206), days to maturity (0.0071), days to 50% flowering (0.0066), hulling percentage (0.0019), milling percentage (0.0019), sterile spikelet no. per panicle (0.0012) and spikelet density (0.0003). 70

75 Table 13: Path Analysis of Yield Attributing and Quality Traits of Aromatic Rice Lines Cont. ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL PH BYld PWt SD SF HI PI DTFF DTM H% M% GYld

76 Cont PH BYld PWt SD SF HI PI DTFF DTM H% M% ASL APL TT/P PT/P Sno./P FSno./P SSno./P TW GL GW DGW DGL PH BYld PWt SD SF HI PI DTFF DTM H% M% GYld

77 Total number of productive tillers per plant: It had negative direct effect on grain yield ( ), with positive indirect effect via grain width(0.0206), decorticated grain width(0,0206), days to maturity (0.0071), days to 50 % flowering (0.0066), hulling percentage (0.0019), milling percentage (0.0019), sterile spikelet no. per panicle (0.0012) and spikelet density (0.0003). Total number of spikelet per panicle: In the present investigation, this trait showed negative direct effect on grain yield ( ), with positive indirect effect via grain length (1.9623), decorticated grain length (1.9623), test weight (1.3679), spikelet fertility percentage (0.3570), panicle length (0.3248) and harvest index (0.3198). Total number of filled spikelet per panicle: This character had negative direct effect on grain yield ( ), with positive indirect effect via sterile spikelet no. per panicle (0.0724), grain length (0.0683), decorticated grain length (0.0683), test weight (0.0273) and days to 50 % flowering (0.0046). Total number of unfilled spikelet per panicle: It had negative direct effect on grain yield ( ) with positive indirect effect via spikelet fertility percentage (0.3333), grain length (0.1707), decorticated grain length (0.1707), test weight (0.1469), harvest index (0.1347), panicle index (0.0925), fertile spikelet no. per panicle (0.0846), panicle weight (0.0779), panicle length (0.0478), grain width (0.0231), decorticated grain width (0.0231), productive tillers per plant (0.0052) and total tillers per plant (0.0045) grain weight: This trait had positive direct effect on grain yield (0.0324) with positive indirect effect via grain length (0.0205), decorticated grain length (0.0204), harvest index (0.0109), panicle weight (0.0108), panicle length (0.0095), spikelet fertility percentage (0.0082), grain width (0.0048), decorticated grain width (0.0047), panicle index (0.0042), biological yield (0.0018), productive tillers per plant (0.0012) and total tillers per plant (0.0005). 73

78 Seed length: Seed length showed negative direct effect on grain yield ( ) with positive indirect effect via spikelet density (0.0578), spikelet no. per panicle (0.0500), days to 50 % flowering (0.0440), days to maturity (0.0438), sterile spikelet no. per panicle (0.0437), culm length (0.0399), panicle height (0.0343), milling percentage (0.0222), hulling percentage (0.0219), fertile spikelet no. per panicle (0.0204), grain width (0.0127) and biological yield (0.0068). Seed width: It exhibited positive direct effect on grain yield (0.1486) with positive indirect effect via decorticated grain width (0.1486), hulling percentage (0.0243), culm length (0.0227), test weight (0.0218), milling percentage (0.0185), panicle height (0.0184), spikelet density (0.0159), fertile spikelet no. per panicle (0.0156), spikelet fertility percentage (0.0070), spikelet no. per panicle (0.0068), panicle index (0.0062), harvest index (0.0024), days to maturity (0.0015) and panicle weight (0.0001). Decorticated seed width: This trait had no direct or indirect effect on grain yield. Decorticated seed length: It had no direct or indirect effect on grain yield. Plant height: This character showed negative direct effect on grain yield ( ) with positive indirect effect via culm length ( ), biological yield (9.5580), panicle length (8.9976), spikelet no. per panicle (6.7800), fertile spikelet no. per panicle (4.7080), sterile spikelet no. per panicle (3.9418), grain width (2.8910), decorticated grain width (2.8910), total tillers per plant (1.4946) and productive tillers per plant (1.1648). Biological yield per plant: In this study, this trait had positive direct effect on grain yield (0.3700), with positive indirect effect via total tillers per plant (0.2132), productive tillers 74

79 per plant (0.2080), panicle weight (0.1899), panicle height (0.1512), culm length (0.1482), spikelet no. per panicle (0.0900), fertile spikelet no. per panicle (0.0818), panicle length (0.0788), spikelet density (0.0607), hulling percentage (0.0291), sterile spikelet no. per panicle (0.0284), panicle index (0.0276), milling percentage (0.0232), test weight (0.0204) and spikelet fertility percentage (0.0045). Panicle weight: It had positive direct effect on grain yield (0.2012), with positive indirect effect via productive tillers per plant (0.1058), biological yield (0.1033), total tillers per plant (0.1022), harvest index (0.0856), test weight (0.0672), fertile spikelet no. per panicle (0.0582), spikelet fertility percentage (0.0519), decorticated grain length ( , grain length (0.0442), panicle length (0.0245), spikelet no. per panicle (0.0232), hulling percentage (0.0213), milling percentage (0.0188), spikelet density (0.0174), panicle index (0.0099) and grain width (0.0001). Spikelet density: The spikelet density showed positive direct effect on grain yield ( ) with positive indirect effect via spikelet no. per panicle (4.4199), fertile spikelet no. per panicle (3.2021), sterile spikelet no. per panicle (2.1379), culm length (0.8290), biological yield (0.7921), panicle height (0.5526), grain width (0.5172), panicle weight (0.4172), hulling percentage (0.0213), harvest index (0.0856), spikelet fertility percentage (0.0519), spikelet density (0.0174), milling percentage (0.0188) and panicle index (0.0099). Spikelet fertility per cent: This character had negative direct effect on grain yield ( ) with positive indirect effect via sterile spikelet no. per panicle (0.1401), days to 50 % flowering (0.0518), days to maturity (0.0484), milling percentage (0.0232), hulling percentage (0.0210), spikelet density (0.0177), productive tillers per plant (0.0149), culm length (0.0084) and panicle height (0.0060). 75

80 Harvest index: Harvest index had positive direct effect on grain yield (0.5490) with positive indirect effect via panicle index (0.2513), panicle weight (0.2336), spikelet fertility percentage (0.1990), test weight (0.1854), grain length (0.1579), decorticated grain length (0.1579), fertile spikelet no. per panicle (0.0944), productive tillers per plant (0.0329), total tillers per plant (0.0125), grain width (0.0088) and decorticated grain width (0.0088). Panicle index: It had positive direct effect on grain yield (0.0959) with positive indirect effect via harvest index (0.0439), spikelet fertility percentage (0.0292), fertile spikelet no. per panicle (0.0234), test weight (0.0124), panicle length (0.0104), biological yield (0.0071), panicle height (0.0057), decorticated grain length (0.0054), culm length (0.0048), panicle weight (0.0047), productive tillers per plant (0.0044), spikelet no. per panicle (0.0043), grain width (0.0040), decorticated grain width (0.0040), total tillers per plant (0.0029) and spikelet density (0.0024). Days to 50% flowering: This character showed positive direct effect on grain yield (0.0125) with positive indirect effect via days to maturity (0.0205), sterile spikelet no. per panicle (0.0086), spikelet density (0.0070), spikelet no. per panicle (0.0058), milling percentage (0.0036), hulling percentage (0.0025), culm length (0.0017) and panicle height (0.0011). Days to maturity: In present investigation, this character showed negative direct effect on grain yield ( ) with positive indirect effect via grain length (0.0489), test weight (0.0451), culm length (0.0249), harvest index (0.0181), panicle index (0.0163), panicle weight (0.0159), productive tillers per plant (0.0085), biological yield (0.0084) and total tillers per plant (0.0082). Hulling per cent: This trait had negative direct effect on grain yield ( ) with positive indirect effect via panicle index (0.0603), grain length (0.0585), panicle length 76

81 (0.0440), spikelet fertility percentage (0.0342), test weight (0.0324), harvest index (0.0261) and productive tillers per plant (0.0055). Milling per cent: It had positive direct effect on grain yield (0.3708) with positive indirect effect via hulling percentage (0.3611), sterile spikelet no. per panicle (0.0692), days to 50 % flowering (0.0622), spikelet density (0.0620), spikelet no. per panicle (0.0535), days to maturity (0.0498), decorticated grain width (0.0461), panicle weight (0.0347), productive tillers per plant (0.0232), culm length (0.0163), panicle height (0.0086), fertile spikelet no. per panicle (0.0078) and total tillers per plant (0.0032). 4.6 Molecular Analysis Genetic diversity analysis was the first and foremost step in any crop improvement programme. However, to have a reliable estimate of genetic relationship and genetic diversity generally a large number of polymorphic markers are required. DNA markers represent very effective tool for analyzing genetic diversity in any crop improvement programme. A total of 149 genotypes (Table 1) were included in the present study. Out of which 15 contrasting lines are selected on the basis of L/B ratio for molecular analysis (Table 3) Molecular analysis using SSR marker During the present study, a total of ten SSR markers were used for genetic diversity analysis in rice. The study revealed that the average percentage of major allele frequency ranged between 20.00% (RM234) to 60.00% (RM259 and RM468). The mean of major allele frequency was found to be 20.00% (Table 14). Genetic diversity varied from (RM 259) to (RM234) with an average of (Table 14). The heterozygosity was found to be moderate with an average of Heterozygosity varied from to and highest heterozygosity was found for marker RM 276 and RM 502 (1.0000) (Table 14). 77

82 The genetic diversity for a specific locus/marker can be evaluated by the Polymorphic Information Content (PIC) value. The PIC value ranged between (RM 259) to (RM234) with a mean value of The highest PIC value was observed for the marker RM234 (0.8499) (Table 14). Table 14. Markers used along with the gene diversity, major allele frequency, heteozygosity and PIC values S. No. Marker Major Allele Frequency Gene Diversity Heterozygosity PIC 1 RM RM RM RM RM RM RM RM RM RM Mean It was found that all the ten markers used were polymorphic. The markers namely, RM256, RM259, RM42, RM276, RM201, RM468, RM502, RM236, RM223 and RM234 (Table 15) are associated with important qualitative and quantitative traits i.e. kernel length, grain length, amylose content, amylose content, drought tolerance, kernel width, plant height, 78

83 panicle number, aroma and grain protein, respectively. The total numbers of alleles amplified were 62 with a mean value of 6.2. The highest number of alleles were 9 amplified by marker RM276 and RM223 (Table 15) and unique alleles were amplified by four markers viz., RM256, RM276, RM236 and RM234 (Table 16). Allele size was found to be highest in RM256 (320bp) whereas lowest in RM236 (65bp) (Table 15). Table 15: Markers used with number of allele, polymorphic allele and allele size Marker Number of alleles Polymorphic allele Allele size range (bp) Polymorphic /Monomorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic RM Polymorphic Total Mean Marker RM256 amplified a total of 6 alleles out of which two were unique alleles amplified in the genotypes IR and IET with allele size of 290bp and 300bp. Marker RM276 amplified a total of nine alleles out of which one was unique allele in genotype Pusa Basmati 6 with an allele size of 240bp. RM236 amplified a total of five alleles, out of which one was unique allele in genotype ANP327 with an allele of 230bp and RM234 amplified total of six alleles out of which one was unique, found in genotype Suganda Mati (195bp). 79

84 Table 16: Markers amplified unique alleles, their size and genotype Markers Unique alleles Allele size (bp) Genotype RM IR IET RM Pusa Basmati 6 RM ANP327 RM Suganda Mati Cluster analysis of SSR markers: Based on the electrophoretic banding pattern of SSR primers, pair wise genetic similarity amongst fifteen genotypes of rice for genetic diversity were estimated and a dendogram (fig.1) was generated by neighbor-joining method implemented in PowerMarker version The cluster analysis revealed that the total 15 genotypes were divided into two major cluster groups I and II. Group I consists of lines IR and Suganda Mati which were highly diverse in relation to other genotypes. The major group II was further subdivided into two major sub groups A and B. The subgroup A comprises of three lines viz. Mugad Sugandha, IR and IET The subgroup B contained ten genotypes that was further sub divided into two subgroups C and D. subgroup C consists only ANP 327 and subgroup D was further subdivided into 2 subgroups E and F. Subgroup E consists of UPR and Pusa Basmati 6. Subgroup F was further subdivided into two subgroups 1 and 2.Subgroup 1 consists of IR and Krishna Kamod whereas subgroup 2 consists of IR , Basmati Mohan 381, IR , IR and IET

85 DISCUSSION Rice (Oryza sativa L.) is a primary food crop and has an important role both economically and in terms of food security. Aromatic rice varieties constitute a small but special group of rice and have gained greater importance with the worldwide increase in the demand for super rice. Not only is aroma, one of the most important characteristics for determining good quality rice but aromatic varieties have comparable or superior nutritional values and better amino acid profiles, for example, Basmati-370 rice having a higher lysine, phenylalanine, leucine and methionine content than nonaromatic varieties. Consumers will pay higher prices for fine-grained aromatic rice, because of which the sensory evaluation of grain quality has become an important consideration in rice breeding. In a rice improvement programme, it is the germplasm, which virtually determine the success and nature of end product. The development of superior rice population involved the intelligent use of available genetic variability both indigenous as well as exotic to cater the need of various farming situations of rice. The grain yield followed by grain quality is the primary trait targeted for improvement of rice productivity in both favourable and unfavourable environments from its present level. Knowledge on the genetic architecture of genotypes is necessary to formulate efficient breeding methodology. It is essential to find out the relative magnitude of additive and non additive genetic variances, heritability and genetic gain with regard to the characters of concern to the breeder. The systematic breeding programme involves the steps like creating genetic variability, practicing selection and utilization of selected genotypes to evolve promising varieties. The large spectrum genetic variability in segregating populations depends on the level of genetic diversity among genotypes offer better scope for selection. Heritability and genetic advance are other important selection parameters. The estimates of heritability help the plant breeder in determining the character for which selection would be rewarding. The breeders are interested in selection of superior genotypes based on their phenotypic expression. The major function of heritability estimates is to provide information on transmission of characters from the parents to the progeny. Heritability 81

86 estimates can anticipate improvement by selection of useful characters. Heritability estimates along with genetic advance are normally more helpful in predicting the gain under selection than heritability estimates alone. Therefore, estimates of GCV, PCV, heritability and genetic advance will play an important role in exploiting future research projections of rice improvement. The biometrical and molecular techniques applied in the analysis of the data in present investigation revealed conclusive findings. The merits of findings are discussed under the following heads in the light of the available literature. 5.1 Morphological Characterization 5.2 Genetic variability 5.3 Heritability 5.4 Genetic advance analysis 5.5 Correlation coefficient analysis 5.6 Path coefficient analysis 5.7 Molecular Analysis 5.1 Morphological Characterization Morphological characterization refers to the characterization of rice on the basis of its morphological characters that is appearance, viz. leaf sheath color, stigma color, awns, height, lodging incidence etc. In the present investigation rice genotypes under study were characterized for seventeen qualitative traits viz., Basal leaf sheath color, Leaf: pubescence of blade surface, Leaf: auricles, Leaf: anthocyanin coloration of auricles, Leaf: shape of ligules, Leaf ligule color, Flag leaf: attitude of blade, Stem: anthocyanin coloration of nodes, Spikelet: color of stigma, Spikelet: density of pubescence, Sterile lemma color, Spikelet: color of tip of lemma, Panicle: exsertion, Panicle: attitude of branches, Panicle: awns, Panicle: distribution of awns and Panicle: color of awns. All the characters under study showed considerable genetic variability. 82

87 A majority of cultivars were found to possess green basal leaf sheath, green leaf blade, light green auricle, straw colored apiculus, white stigma, well to moderate panicle exertion and horizontal flag leaf. Certain traits like presence of awns and distribution of awns were found to be unstable. Some of the genotypes were identified for excellent quality and agronomical characteristics. On the basis of morphological characterization and quantitative analysis varieties IR , SUGANDA MATI, IR , KRISHNA KAMOD, IET 12601, MUGAD SUGANDHA, IR , BASMATI MAHON 381, IR , UPR , IR , PUSA BASMATI 6, IET and IR were found to be excellent in phenotypic acceptability, vigour, panicle exsertion, yield and tolerance to lodging. The results found in present investigation were in agreement with that reported by Motiramani et al. (2001) and Parikh et al. (2012a). Similar results were reported by Rao et al. (2001), Behla and Allah (2007).This result was also in agreement with that reported by Sarawgi et al. (2012) and Subudhi et al. (2012). 5.2 Genetic variability Variability refers to the presence of phenotypic differences among the individuals of plant population. Variability results due to differences either in the genetic constitution of the individuals of a population or in the environment in which they grown. Magnitude of genetic variability present in a population was of paramount importance to a plant breeder for starting a judicious breeding programme. Selection was only effective when there was a genetic variability among the genotypes in a population. The genotypic coefficient of variation (GCV) measures the extent of genetic variability present in a crop species and also enables to quantify the extent of variability present in different characters. The phenotypic coefficient of variation (PCV) of a character was the manifestation of genotypes, environment and interaction between the genotypes and environment. Therefore, the total variance needs to be partitioned into heritable and non-heritable components to assess the true breeding nature of that particular trait. The results obtained from present investigation are discussed here for yield and quality traits in all the lines and parents. 83

88 Results of analysis of variance indicated that the mean sums of squares due to genotypes were highly significant for all the traits, suggesting presence of sufficient variation among the genotypes for these traits. Maximum variability was observed for total number of spikelet per panicle and lowest for decorticated seed width. Coefficient of variation truly provides a relative measure of variance among the different traits. GCV was found to be highest for number of unfilled spikelet per panicle followed by spikelet no. per panicle, harvest index, grain yield, panicle weight, fertile spikelet no. per panicle, biological yield, spikelet density, productive tillers per plant, total tillers per plant, decorticated grain length, test weight, Culm length, panicle index, plant height, spikelet fertility %, grain length, decorticated grain length, grain width, days to 50% flowering, panicle length, days to maturity, hulling % and smallest for milling %. Similar trend was also observed for PCV. Close relationship between GCV and PCV are found in all the traits. High GCV was observed for grains per panicle but moderate variability was recorded for plant height and kernel length which was in partial agreement with one reported by Sadhukan and Chattopadhyay (2000), Padmaja et al. (2008). Very small difference between GCV and PCV was observed for all the characters. This was not in agreement with the findings of Chakraborty et al. (2001) that reported wide difference between GCV and PCV was observed for the characters like plant height, flag leaf length, effective branch tillers per hill, panicle length, sterility percentage and yield per plant. Moderate phenotypic and genotypic coefficients of variation were observed for panicle length and 1000 grain weight, number of panicles, spikelet panicle -1, grains panicle -1 and grain yield plant -1 which was in agreement with one reported by Singh et al. (2002) and Nayak et al. (2002). Genotypic and phenotypic coefficient of variation were high for grains panicle -1 and grain yield plant -1. Similar findings were reported by Chand et al. (2004). 84

89 Good correspondence was observed between phenotypic and genotypic coefficient of variation in plant height, tillers plant -1, panicle length, filled grains panicle -1, grain length, 1000 seed weight and grain yield plant -1. These results were in conformity with the findings of Hasib et al. (2004). Moderate magnitudes of PCV and GCV was observed for plant height, days to 50% flowering, panicle length, 1000 grain weight and panicle index. These results were not in agreement with those reported by Bhaskar (2006) who reported high magnitudes of both. Enormous variations in majority of characters viz., grain length, grain breadth, milling yield, and kernel length were recorded. Similar findings were reported by Sahidullah et al. (2009). Considerable variability among genotypes for characters like, plant height, number of tillers, and number of productive tillers, panicle length, and filled grain per panicle and test weight was observed. This was in confirmation with Selvaraj et al. (2011). The magnitude of difference between phenotypic coefficient of variation and genotypic coefficient of variation was relatively low for all the traits indicating less environmental influence. Hulling (%) and milling (%) indicating importance of these traits in the inclusion under breeding for quality in rice. Similar findings were reported by Krishnamurthy et al. (2012) 5.3 Heritability Heritability in broad sense refers to the ratio of genotypic variance to the total phenotypic variance. The estimates of heritability help the plant breeders in selection of elite genotypes from diverse genetic population and also a good index of the transmission of characters from parents to their offspring. If high heritability is accompanied with high genetic advance, it indicates that the heritability is most likely be due to additive gene effect and selection may be effective, while high heritability in broad sense coupled with low genetic advance indicate predominance of non-additive gene action. 85

90 Heritability estimates along with genetic advance are normally more helpful in predicting the genetic gain under selection than heritability alone. However, it is not necessary that a character showing high heritability will also exhibit high genetic advance. High heritability for grain yield plant -1 was recorded. The result was in agreement with that reported by Durai et al. (2001), Mishra and Verma (2002), Elayaraja et al. (2004), Hasib et al. (2004), Madhavilatha et al. (2005), Panwar (2005), Girish et al. (2006), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Kole et al. (2008) and Selvaraj et al. (2011). Similarly, High heritability for number of effective tillers plant -1 was observed in this investigation which was same as reported by Mishra and Verma (2002), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Bhagat (2007), Nandan et al. (2010) and Selvaraj et al. (2011). High heritability for Biological yield plant -1 was recorded in present investigation. The same was observed by Thakur et al. (2000), Narinder (2006), Girish et al. (2006) and Abdul Fiyaz et al. (2011). However, high heritability for sterility % and spikelet density was elucidated by Mishra and Verma (2002) while, the same for days to maturity was reported by Narinder (2006). High heritability for kernel length, kernel breadth, milling percentage, panicle length, effective tillers plant -1, biological yield, harvest index and grain yield was observed in present investigation. These results were similar as reported by Chaudhary et al. (2003). High heritability for panicle length was also observed. This was in agreement with one reported by Mishra and Verma (2002), Hasib et al. (2004), Saxena et al. (2005), Ananthi et al. (2006), Narinder (2006) and Muthuswamy and Ananda Kumar (2006). Similarly, high heritability was observed for number of grains panicle -1. This was in agreement with Durai et al. (2001), Saxena et al. (2005), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Bhagat (2007), Kole et al. (2008), Chandra et al. (2009) and Nandan et al. (2010). Similarly, high heritability for days to 50 % flowering was 86

91 found in present investigation. This was in agreement with Durai et al. (2001), Ananthi et al. (2006) and Narinder (2006). In present investigation, high heritability for 1000 grain weight was recorded and so supports the result observed by Mishra and Verma (2002), Narinder (2006), Kole et al. (2008), Nandan et al. (2010) and Abdul Fiyaz et al. (2011) while, the same for plant height was also observed which was in agreement with Mishra and Verma (2002), Elayaraja et al. (2004), Sinha et al. (2004), Girish et al. (2006), Narinder (2006), Kole et al. (2008), Chandra et al. (2009) and Selvaraj et al. (2011). Total number of spikelet per panicle showed high heritability which was also observed by Saxena et al. (2005), Girish et al. (2006), Narinder (2006), Bhagat (2007) and Abdul Fiyaz et al. (2011). High heritability was also observed for number of filled grains panicle -1 thereby supported the report of Mishra and Verma (2002), Hasib et al. (2004), Panwar (2005), Narinder (2006) and Bhagat (2007) The entire yield contributing characters showed high heritability. The result was in agreement with whatever was elucidated by Tyagi et al. (2004) and Narinder (2006). High heritability for harvest index was also observed. The result supports that observed by Elayaraja et al. (2004), Madhavilatha et al. (2005) and Girish et al. (2006). High heritability for spikelet fertility % was also observed. The same was reported by Madhavilatha et al. (2005). Moderate to High heritability coupled with high genetic advance and high genotypic variation for spikelet no. per panicle, number of tillers, number of productive tillers per plant, plant height and grain yield per plant was observed in present investigation. This result was in confirmation of that reported by Selvaraj et al. (2011), Hosseini et al. (2012) and Reddy et al. (2013) except for spikelet no. per panicle. Highest heritability was recorded for spikelet no. per panicle followed by fertile spikelet no. per panicle and sterile spikelet no. per panicle. This result was not in agreement with that reported by Rafii et al. (2014) who reported highest heritability for plant height followed by panicle length. 87

92 5.4 Genetic Advance Genetic advance refers to the improvement in the genetic value of the selected single plants over the base population. Heritability estimates along with genetic advance are normally more helpful in predicting the gain under selection from heritability alone. High genetic advance for Grain yield plant -1 was observed in present investigation which support the result reported by Mishra and Verma (2002), Agrawal (2003), Chand et al. (2004), Chaudhary et al. (2004), Sinha et al. (2004), Sharma and Bhuyan (2004), Madhavilatha et al. (2005), Panwar (2005), Girish et al. (2006), Muthuswamy and Ananda Kumar (2006), Narinder (2006), Chandra et al. (2009), Nandan et al. (2010) and Selvaraj et al. (2011). Moderate genetic advance for 1000 grain weight was recorded. This result was not in agreement with what was reported by Rao (2000), Sinha et al. (2004), Hasib et al. (2004), Nandan et al. (2010) and Abdul Fiyaz et al. (2011). Similarly, Moderate genetic advance for panicle length was observed. The result differs with what was reported by Chaudhary et al. (2004) and Hasib et al. (2004). High genetic advance observed for plant height which was in agreement with the findings advocated by Mishra and Verma (2002), Elayaraja et al. (2004), Hasib et al. (2004), Saleem et al. (2008) and Selvaraj et al. (2011), for number of effective tillers plant -1 which support the result of Mishra and Verma (2002), Chaudhary et al. (2004), Girish et al. (2006), Nandan et al. (2010) and Selvaraj et al. (2011) and for number of tillers plant -1 supporting the report of Kumari et al. (2003) and Girish et al. (2006). Number of grains panicle -1 showed high genetic advance thereby supporting the report of by Rao (2000), Agrawal (2003), Kumari et al. (2003), Sharma and Bhuyan (2004), Panwar (2005), Madhavilatha et al. (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009). At the same time, this result was not in agreement with the findings of Satyanarayana et al. (2005). Low genetic advance for days to 50 % flowering, panicle length,grain length and breadth was recorded which were same as reported by Agrawal 88

93 (2003), Chand et al. (2004) and Padmaja et al. (2008) while, low genetic advance for number of tillers plant -1 was also observed. The result was in agreement with the findings of Agrawal (2003) and Chand et al. (2004). Moderate genetic advance was recorded for spikelet fertility %. This result differs from the one reported by Satyanarayana et al. (2005), Madhavilatha et al. (2005), Panwar (2005), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009). High genetic advance for characters viz., harvest index, number of filled grains panicle -1, biological yield plant -1,spikelet sterility %, number of filled grains panicle -1 and spikelet density were observed in present investigation. The results were same as reported by Elayaraja et al.(2004) and Girish et al.(2006) by Hasib et al. (2004), Chaudhary et al.(2004), Madhavilatha et al. (2005), Panwar (2005), Saleem et al.(2008), Muthuswamy and Ananda Kumar (2006) and Chandra et al. (2009) Moderate genetic advance for Days to 50 % flowering, panicle length and 1000 grain weight were recorded. It shows agreement with the result advocated by Ananthi et al. (2006). Low genetic advance observed for grain length. It was not in agreement with the result advocated by Chand et al. (2004) and Hasib et al. (2004), who reported high genetic advance for grain length. Low genetic advance for kernel length and milling percentage was recorded. It was not in agreement with Chaudhary et al. (2004) who observed high genetic advance for the same. High genetic advance was recorded for grain yield per plant, biological yield per plant, panicle weight per plant, number of tillers per plant, number of productive tillers per plant, panicle length, number of spikelet per plant and filled grain per panicle whereas moderate to low genetic advance for plant height, days to 50% flowering, 1000 grain weight and days to maturity. This was in agreement with Narinder (2006). Highest genetic advance was observed for spikelet no. per panicle followed by fertile spikelet no. per panicle, sterile spikelet no. per panicle, plant height and culm length. This was not in agreement with Saleem et al. 89

94 (2008) who reported same for biological yield per plant followed by plant height, flag leaf area, yield plant -1, harvest index and panicle density. High heritability coupled with high genetic advance was recorded for spikelet no. per panicle followed by fertile spikelet per panicle and sterile spikelet per panicle. This was not in agreement with Jayasudha and Sharma (2010) who reported High heritability associated with high genetic advance for spikelet fertility % followed by days to 50% flowering and grain yield per plant. High to medium genetic advance for the number of grains per panicle, grain yield, panicle weight and the number of panicles per plant was recorded. This was in agreement with Akinwale et al. (2011). High genetic advance for number of grains per panicle and grain yield per plant whereas, the estimates were relatively low-moderate for the remaining yield contributing characters. This was in agreement with Reddy et al. (2013). In the present study, high heritability coupled with high genetic advance was observed for the characters fertile spikelet per panicle, spikelet per panicle, culm length, biological yield, panicle index, spikelet density and test weight (Table 11) suggest that these traits were controlled by additive genes. By using simple selection for these traits, governed by additive gene action, grain yield may be enhanced, whereas the characters under the control of non additive genes with component traits breeding, indirect selection may result in fixing of other traits. 5.5 Correlation coefficients Correlations indicate the magnitude of linear association between pairs of characters and form the basis of selection index, thereby aiding the breeder in crop improvement programmes. It will help to know how the improvement in one character will bring simultaneous changes in other characters. Yield is a polygenically inherited character and is highly influenced by environmental effects. Knowledge of genetic correlation among the factors contributing to yield leads to the most effective method of selection by the use of favorable combination of characters. Hence, direction and magnitude of component characters with yield serves as a prerequisite for 90

95 successful breeding programmes. Correlation studies provide better pathway for yield improvement during selection (Robinson et al and Johnson et al. 1955). In the present investigation, an attempt has been made to estimate the correlation in all the character combination for different set of character with the objective to get the information about the nature, extent and direction of selection pressure which should be extended to achieve practical and usable results. The association analysis has been discussed with the following paragraphs. Grain yield plant -1 was found to be positively associated with productive tillers per plant, panicle length and number of grains panicle -1. The result was in agreement with that advocated by Rao (2000). Grain yield plant -1 was found to be positively associated with number of effective tillers plant -1, panicle length, number of grains panicle -1, harvest index and biological yield plant -1. The result was in agreement with Tomar et al. (2000), Nayak et al. (2001), Shashidhar et al. (2005) and Sabu et al. (2009). Grain yield plant -1 does not show any significant correlation with plant height and negatively correlated with days to 50 % flowering. The result was in partial agreement with Islam et al. (2002) who reported positive correlation of grain yield per plant with plant height while negative correlation with days to 50 % flowering. No significant association of plant height with grain yield plant -1 observed. The result was not in agreement with Rasheed et al. (2002), Girish et al. (2006) and Samo et al. (2002) who reported the positive association of plant height with grain yield plant -1. Correlation of plant height with number of tillers plant -1 was founded positive. The result was in agreement with Rasheed et al. (2002). Grain yield plant -1 showed positive correlation with 1000 grain weight, number of panicles plant -1, panicle length and number of tillers plant -1. The result was in agreement with Samo et al. (2002). Grain yield plant -1 indicated significant positive correlation with number of effective tillers plant -1 and biological yield plant -1. The result was in agreement with Chaudhary and 91

96 Motiramani (2003). A significant positive correlation of grain yield per plant was observed with grains panicle -1 and grain length. The result was in agreement with Chand et al. (2004). Number of effective tillers plant -1, panicle length and 1000 seed weight showed significant and positive association with grain yield plant -1. The result was in agreement with Tyagi et al. (2004). A positive and significant correlation between grain length and grain yield per plant was observed as reported by Chand et al. (2004) while, non significant correlation between grain breadth and grain yield was observed which was not in agreement with Girish et al. (2006), who reported significant correlation for same. Grain yield plant -1 was observed to be positively associated with number of effective tillers plant -1, panicle length, and number of grains panicle - 1, harvest index and 1000 grain weight which is in agreement with Madhavilatha et al. (2005b). While, negatively associated with days to 50 % flowering and plant height which is not in agreement with Madhavilatha et al. (2005b) who reported positive association. Grain yield plant -1 was observed to be positively associated with spikelet fertility, panicle length, number of grains panicle -1 and number of effective tillers plant -1. The result was same as reported by Satyanarayana et al. (2005). Significant and positive correlation was found between grain yield plant 1 and number of effective tillers plant -1 and number of tillers plant -1 and number of grains panicle -1. The result was in agreement with Gazafrodi et al. (2006). A significant and positive correlation was present between plant height and number of grains panicle -1. The result was in agreement with Zahid et al. (2006). A significant and positive association was observed between number of tillers plant -1 and grain yield plant -1 which was not in agreement with Zahid et al. (2006) who reported non-significant and negative association. Grain yield plant -1 was found to be significantly correlated with days to 50 % flowering, number of tillers plant -1, number of effective tillers plant -1 and 92

97 number of grains panicle -1. The result was in agreement with Agahi et al. (2007). Grain yield plant -1 was correlated significantly and positively with panicle length and number of grains panicle -1. Correlation of plant height with number of tillers plant -1 was positive. Number of grains panicle -1 showed positive correlation with grain yield plant -1.The result was in agreement with reported by Khan et al. (2009). Strong positive association of yield with number of grains per panicle, number of spikelet per panicle and spikelet fertility was observed. The result was in agreement with reported by Nandan et al. (2010). While, it is negatively associated with days to 50 % flowering and plant height. The result was not in agreement with Nandan et al. (2010) who reported strong positive association for same. The correlation analysis indicated that grain yield was significantly associated with panicle length, test weight, number of tillers per plant, number of productive tillers per plant, number of spikelet per panicle and per cent spikelet fertility. The result was in agreement with Basavaraja et al. (2011). Significant positive correlation for number of grain per panicle, panicles length and grain yield. The result was in agreement with Suwarto et al. (2013).The obtained results indicated that number of grains per panicle, total number of productive tillers per plant, harvest index, and panicle length showed highly significant positive association with grain yield per plant. The result was in agreement with Nagaraju et al. (2013). While, negative correlation was found for milling percentage which was not in agreement with Nagaraju et al (2013) who reported positive correlation between grain yield and milling percentage. Thus, from this study, it is concluded that characters having positive and significant correlation with grain yield per plant are panicle weight, Harvest index, Panicle index, Productive tillers per plant, Biological yield per plant, Total tillers per plant, Spikelet fertility %, Fertile spikelet per panicle, test weight, Grain length, Panicle length and Spikelet number per panicle. 5.6 Path coefficient analysis 93

98 Path coefficient measures the direct and indirect contributions of independent variables on a dependent variable. Though the correlation coefficients depict the nature of association among the characters, it is the path analysis that splits the correlation coefficients into direct and indirect effects thus specifying the relative contribution of each character. It further reveals the different ways in which a particular character influences a dependent variable. The Path coefficient analysis has been discussed in the following paragraph. Plant height, Culm length, spikelet density, panicle length, spikelet no. per panicle, biological yield, productive tillers per panicle, harvest index and days to 50% flowering had high direct (positive and negative both) effect on grain yield. The effects of these characters were further increased by positive indirect effect of culm length for plant height, harvest index for culm length, panicle length through biological yield and total tillers per plant, spikelet no. per panicle through spikelet density and fertile spikelet no. per panicle, biological yield through productive tillers per plant, productive tillers per plant through total tillers per plant, harvest index through plant index and panicle weight and days to 50% flowering through days to maturity. The result was in partial agreement with Janardhanam et al. (2000) who revealed that, plant height, spikelet panicle -1, and grains panicle -1 had high direct effects on plant yield and The effects of these characters were further increased by positive indirect effect of plant height through spikelet and grains panicle -1, productive tillers plant -1, panicle length through plant height, spikelet panicle -1, and grains panicle -1, spikelet panicle -1 through plant height and grains panicle -1, The major yield-contributing characters, based on indirect and direct effects, were plant height, spikelet panicle -1 and grains panicle -1. Highest positive direct effect towards grain yield plant -1 was contributed by plant height. The result was in agreement with Babu et al. (2002), Babar et al. (2007).The result was not in agreement with Tomar et al. (2000), Gazafrodi et al. (2006) and Agahi et al. (2007). Similarly, the result was not in agreement with the report of Tomar et al. (2000) and Gazafrodi et al. (2006), who reported same for number of effective tillers plant -1. Harvest index and number of grains panicle -1 had moderate direct effects on grain yield plant

99 The result was in agreement with Tomar et al. (2000) and Gazafrodi et al. (2006). Path analysis showed that panicle number plant -1, grains panicle -1 and 1,000 seed weight contributed to the grain yield. The result was in agreement with Nayak et al. (2002). Positive indirect effects were contributed by panicle length, number of grains panicle -1 and spikelet fertility. The result was same as advocated by Babu et al. (2002). Plant height, spikelet density, harvest index, milling %, biological yield, panicle weight, grain width, plant index, total tillers per plant, test weight, and days to 50% flowering had direct positive effect on grain yield. The result was not in agreement with Mishra and Verma (2002) who reported Flag leaf width followed by flag leaf length, spikelet density, harvest index, biological yield plant -1 and plant height had the greatest positive effect on grain yield plant -1. A high direct effect on grain yield plant -1 was due to number of effective tillers plant -1 reported by Sinha and Banerjee (2002). The result also not support the report advocated by Khedikar et al. (2004) who revealed that, 1,000 seed weight had the highest positive direct effect on grain yield followed by spikelet density, effective tillers plant -1, panicle length and days to fifty per cent flowering. Plant height exhibit high positive direct effect followed by spikelet density, harvest index, milling %, biological yield, panicle weight and grain width. The result was not in agreement with Shanthala (2004) who reported that spikelet density exhibited the highest direct effect on grain yield plant -1 followed by harvest index, 1000 grain weight and number of effective tillers plant -1. The result also not supported the view of Agahi et al, (2007) who reported that, the productive tillers plant -1 had the highest positive direct effect on grain yield plant -1, followed by the number of grains panicle -1 and 1,000 seed weight. Path coefficient analysis indicated moderate direct effect of number of grains panicle -1 on grain yield plant -1. The result was not in agreement with Khan Salam et al. (2009) who reported highest direct effect of number of 95

100 grains panicle -1 on grain yield plant -1. Plant height and number of panicles plant -1 recorded the highest positive indirect effect on yield via harvest index whereas number of filled grains panicle -1 on grain yield plant -1 via harvest index and panicle length reported by Chakraborty et al. (2010). The result was not in agreement with Nandan et al. (2010) who observed that the number of grains per panicle had maximum direct effect on grain yield per plant followed by days to 50 % flowering, hulling percentage, plant height, harvest index. Days to maturity had negative direct effect on grain yield per plant and days to heading show positive direct effect on grain yield. The result was not in agreement with Wattoo et al. (2010) who revealed that, days to maturity had the highest direct effect on grain yield per plant. In addition, the yield components had positive direct effect on grain yield except the days to heading. The order of yield components was the number of productive tillers per plant, flag leaf area and 1000 grain weight. Test weight exhibited low positive direct effect followed by days to 50% flowering. The result was not in agreement with Selvaraj et al. (2011) who reported that path coefficient analysis for test weight exhibited maximum positive direct effect on grain yield / plant followed by filled grains / panicle, plant height, panicle length, number of tillers per plant and days to 50% flowering. Path coefficient analysis revealed that plant height, spikelet density, panicle number, total tillers per plant and days to 50% flowering, had positive direct effect on grain yield but negative for culm length. The result was in partial agreement with Basavaraja (2011) who reported the same positive effects but the effect of culm length was also found to be positive. The path coefficient analysis for all characters showed that plant height and spikelet density serves as the main yield components because these traits showed the highest positive direct effects towards increasing grain yield. The result was not in agreement with Nagaraju et al. (2013) who reported same for spikelet no. per panicle and no. of productive tillers per plant. In the present investigation harvest index, biological yield, panicle weight, panicle index, total tillers per plant and test weight found to have 96

101 highest positive direct effect on grain yield per plant and also have a positive association with grain yield. A simple selection based on these traits can easily enhance the yield level. 5.7 Molecular Analysis At molecular level, a total of fifteen SSR markers were used for genetic diversity analysis Genetic diversity based on SSR markers analysis A total of ten SSR markers were used for analysis of genetic diversity in rice. All the markers were found polymorphic (Table 15). It showed that sufficient amount of genetic diversity is present in genotypes included in this study. Polymorphic markers are useful for breeding aspects because they have capacity to differentiate allelic variations present in the genotypes and easily useful for the important molecular breeding programmes i.e. mapping, tagging, QTL analysis and candidate gene approaches. In present investigation SSR s markers have been used to analyze diversity and to locate genes. Thus the utility of these DNA markers had resulted in precise and reliable characterization and discrimination of genotypes. The markers found to be polymorphic namely, RM256, RM259, RM42, RM276, RM201, RM468, RM502, RM236, RM223 and RM234 are associated with important qualitative and quantitative traits i.e. kernel length, grain length, amylose content, amylose content, drought tolerance, kernel width, plant height, panicle number, aroma and grain protein. Because all of the ten polymorphic markers having sufficient amount of polymorphism in the genotypes and show presence of desired gene available/present in the study material, will be helpful for designing of suitable breeding programmes for the development of high quality and high yielding cultivars of rice. The genetic diversity for a specific locus/marker can be evaluated by the Polymorphic Information Content (PIC) value. The PIC value ranged between (RM 259) to (RM234) with a mean value of The highest PIC value was observed for the marker RM234 (0.8499) amplified with three alleles ( XiLan et al.,2010). Unique alleles were amplified by four markers (Table 16) viz., RM256, RM276, RM236 and RM234. Allele size was found to be highest in RM256 (320bp) whereas lowest in RM236. Presence of specific band reported earlier 97

102 for panicle length, amylose content, panicle number and grain protein was found in genotypes IR , IET 12014, Pusa Basmati 6, ANP327 and Suganda Mati respectively. These genotypes will be directly used for cultivation purposes because each has unique alleles for specific yield contributing character. Genotype Suganda Mati produces reported band for grain protein and also produces specific band (Unique band) for this trait. Thus, it is concluded that the genotype having high proportion of grain protein and this trait will be very useful for study purpose and development of suitable rice cultivars having high grain protein. All genotypes show bright bands with RM223 revealed the presence of gene for aroma. High protein and high amylose content related bands shows that the genotypes used for this study having rich genetic wealth for current breeding goals and in future utilized for the development of high nutritive value crop. Similarly, aroma related bands shows that these genotypes must be used for breeding programmes in developing fine aromatic rice with high export quality. A candidate gene study related to this trait may confers the actual position and utility of this gene for the transfer in desired high yielded cultivars having deficient of this trait. The markers found to be specific on specific genotype will be beneficial for future plant breeding and genetics programmes. The cluster analysis revealed that the total 15 genotypes were divided into two major cluster groups I and II. The group I consist of lines IR and Suganda Mati which were highly diverse with other genotypes. The second major group II was further subdivided into two major sub groups A and B. The subgroup A comprises of three lines viz. Mugad Sugandha, IR and IET The second subgroup B further sub divided into two subgroups C and D. subgroup C consists of ANP 327 and subgroup D was further subdivided into 2 subgroups E and F. Subgroup E consists of UPR and Pusa Basmati 6. Subgroup F was further subdivided into two subgroups 1 and 2.Subgroup 1 consists of IR and Krishna kamod whereas subgroup 2 consists of IR , Basmati Mohan 381, IR , IR and IET It depicted that there is considerable genetic variability in the lines which match to the result of analysis done on the basis of morphological data. Based on the molecular analysis, it was found that the genotypes viz., IR , Suganda 98

103 Mati, ANP327 and IET could be utilized in crop improvement programmes. The dendogram based on the cluster analysis by microsatellite polymorphism, grouped 15 rice cultivars into two groups and further subgroups effectively differentiating basmati cultivars from non-basmati cultivars. The result supports the findings of Priyanka et al., 2004 and Shah et al., Validation of polymorphic informative SSR markers on elite rice lines In this study, a total of one hundred forty nine genotypes were used for characterization based on yield and yield attributing traits and also analyzed for genetic diversity. On the basis of L/B ratio fifteen diverse lines were selected for molecular characterization especially diversity analysis on the basis of polymorphic SSR markers reported for different qualitative and quantitative traits. A total of ten SSR markers having different linked traits were applied to analyze the genetic architecture of the present material utilized for this study. It was found that all SSR markers used namely, RM256, RM259, RM42, RM276, RM201, RM468, RM502, RM236, RM223 and RM234 are associated with important qualitative and quantitative traits i.e. kernel length, grain length, amylose content, drought tolerance, kernel width, plant height, panicle number, aroma and grain protein respectively. Polymorphic marker RM256 was linked with the yield attributing trait panicle length and it was found that when this marker was applied on the genotypes having long and small panicle length trait then each genotypes namely Suganda Mati and UPR produce band (140/320bp) related to long panicle length trait whereas, IR , ANP327 and Mugad Sugandha produces band with the length of 130/230bp for small panicle length. In this case it is validation for the confirmation of marker RM256 associated with panicle length as a yield attributing trait reported earlier and confirmed in this study as a suitable marker applicable directly selection of genotypes having long panicle length associated with grain yield. 99

104 SUMMARY, CONCLUSIONS AND SUGGESTIONS FOR FURTHER WORK 6.1 Summary The present investigation entitled Characterization and Quantitative analysis of Rice was conducted at Seed Breeding Farm, Department of Plant Breeding and Genetics, College of Agriculture, J.N.K.V.V., Jabalpur, during Kharif This investigation was carried out with 149 germplasm lines of aromatic rice in randomized complete block design with three replications with the objectives to characterize aromatic lines of rice based on morphological traits and to estimate genetic parameters of variability viz., coefficient of variation, heritability, genetic advance as percentage of mean, correlation coefficient analysis, path analysis and molecular analysis using SSR markers. Results of analysis of variance indicated that the mean sums of squares due to genotypes were highly significant for all the traits under study, suggesting presence of sufficient variation among the genotypes for these traits. Maximum variability was observed for number of spikelet per panicle and minimum for grain width. Coefficient of variation truly provides a relative measure of variance among the different traits. The values of PCV for all the traits under study were found to be more than GCV and slight difference between GCV and PCV were observed in all the traits, revealing very little influence of environment for their expression. High Heritability accompanied with High Genetic Advance indicated the predominance of additive gene action for the traits fertile spikelet per panicle, spikelet per panicle, culm length, harvest index, biological yield, panicle index, spikelet density and test weight. It indicates that the heritability is most likely due to additive gene effect and selection may be effective. Characters having positive and significant correlation with grain yield per plant are panicle weight, harvest index, panicle index, productive tillers per plant, biological yield per plant, total tillers per plant, spikelet fertility %, 100

105 fertile spikelet per panicle, test weight, grain length, panicle length and spikelet per panicle. The path coefficient analysis of different traits contributing towards grain yield revealed that plant height, spikelet density, harvest index, milling %, biological yield per plant, panicle weight, grain width, panicle index, total tillers per plant, test weight and days to 50% flowering had positive direct effect towards grain yield. On the basis of L/B ratio fifteen diverse lines were selected for molecular characterization especially diversity analysis on the basis of polymorphic SSR markers reported for different qualitative and quantitative traits. It was found that all SSR markers used namely, RM256, RM259, RM42, RM276, RM201, RM468, RM502, RM236, RM223 and RM234 are associated with important qualitative and quantitative traits i.e. kernel length, grain length, amylose content, drought tolerance, kernel width, plant height, panicle number, aroma and grain protein respectively. All the markers were found polymorphic. It showed that sufficient amount of genetic diversity is present in genotypes included in this study. In this study, it depicted that there is considerable genetic variability in the lines which match to the results of analysis done in the basis of morphological data. Based on the molecular analysis, it was found that the genotype viz., IR & IET 12014, Pusa Basmati 6, ANP327 and Suganda Mati could be utilized in crop improvement programme because each has unique alleles for specific yield contributing traits. 6.2 Conclusions Germplasm lines of aromatic rice showed sufficient variation among the lines for the traits under study. The values of PCV for all the traits were found to be more than GCV and there were very small difference was present in between GCV and PCV revealing very little influence of environment for their expression. Heritability and genetic advance are important selection parameters. Heritability estimates along with genetic advance are normally more helpful in predicting the gain under selection than heritability alone. 101

106 Result showed that the characters viz., fertile spikelet per panicle, spikelet per panicle, culm length, harvest index, biological yield, panicle index, spikelet density and test weight had high heritability coupled with high genetic advance. It indicates that the heritability is most likely due to additive gene effect and selection may be effective. Based on the studies of correlation and path analysis, it may be concluded that harvest index, panicles weight per plant, panicle index, total tiller per plant and 1000 grain weight which showed positive correlation with grain yield and at the same time exhibited positive direct effect towards yield seems to be primary yield contributing characters and could be relied upon for selection to improve genetic yield potential of rice. On the basis of morphological characterization and quantitative analysis varieties IR , SUGANDA MATI, IR , KRISHNA KAMOD, IET 12601, MUGAD SUGANDHA, IR , BASMATI MAHON 381, IR , UPR , IR , PUSA BASMATI 6, IET and IR were found to be excellent in phenotypic acceptability, vigour, panicle exsertion, yield and tolerance to lodging. Unique alleles were amplified by four markers viz., RM256, RM276, RM236 and RM234. Presence of specific band reported earlier for panicle length, amylose content, panicle number and grain protein was found in genotypes IR & IET 12014, Pusa Basmati 6, ANP327 and Suganda Mati respectively. These genotypes will be directly used for cultivation purposes because each has unique alleles for specific yield contributing character. From overall molecular analysis, it is concluded that these markers will be used for diversity analysis, mapping and tagging of targeted genes and also QTL analysis, candidate gene approach and other relevant fields of genetics and plant breeding. 102

107 6.3 Suggestions for further work 1. As evident from phenotypic and genotypic coefficients of variation, heritability and genetic advance, correlation coefficient and path analysis the characters viz., harvest index, biological yield per plant, panicle index and 1000 grain weight might be utilized in designing high yielding plant ideotypes. 2. The genotypes IR , SUGANDA MATI, IR , KRISHNA KAMOD, IET 12601, MUGAD SUGANDHA, IR , BASMATI MAHON 38, IR , UPR , IR , PUSA BASMATI 6, IET and IR were found to be excellent and could be utilized in further breeding programmes. 3. Biochemical analysis for protein and cooking quality parameters viz., aroma, milling percentage, alkali spreading value and amylose content etc. may be carried out on the present genotypes. 4. In molecular work, Metaphor and polyacrylamide matrix can be used for better resolution of alleles. ********* 103

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117 Fig.1 Path diagram showing effects of independent characters on dependent characters

118 L Lanes: 1. IR , 2.Suganda Mati, 3. IR , 4. Krishna Kamod, 5. IET 12601, 6. Mugad Suganda, 7. IR , 8. ANP 327, 9. Basmati Mohan 381, 10. IR , 11. UPR , 12. IR , 13. Pusa Basmati 6, 14. IET 12014, 15. IR Fig.2 Banding pattern of SSR marker RM276 with the above mentioned fifteen varieties of aromatic rice Fig.3 Banding pattern of SSR marker RM42 with the above mentioned fifteen varieties of aromatic rice

119 L Lanes: 1. IR , 2.Suganda Mati, 3. IR , 4. Krishna Kamod, 5. IET 12601, 6. Mugad Suganda, 7. IR , 8. ANP 327, 9. Basmati Mohan 381, 10. IR , 11. UPR , 12. IR , 13. Pusa Basmati 6, 14. IET 12014, 15. IR Fig. 4 Banding pattern of SSR marker RM234 with the above mentioned fifteen varieties of aromatic rice L Lanes: 1. IR , 2.Suganda Mati, 3. IR , 4. Krishna Kamod, 5. IET 12601, 6. Mugad Suganda, 7. IR , 8. ANP 327, 9. Basmati Mohan 381, 10. IR , 11. UPR , 12. IR , 13. Pusa Basmati 6, 14. IET 12014, 15. IR Fig. 5 Banding pattern of SSR marker RM201 with the above mentioned fifteen varieties of aromatic rice

120 Fig. 6 Dendogram showing different clusters of Aromatic Rice Lines

121 APPENDIX-I Weekly Meteorological parameters during crop season (2013) Moths Meteo. weeks Temperature ( 0 C) Relative humidity (%) Max. Min. Mor. Eve. Sun Shine hrs. Rainfall (mm) Rainy days June July August Sept Oct Nov Dec Jan I

122 Appendix-II Nie s(1983) Frequency distribution value among rice genotypes using SSR primers Genotype II

123 ABSTRACT Title of the thesis : Characterization and Quantitative Analysis in Aromatic Rice Germplasm Student Name : Kumari Shahnaz Address : Advisor Name : Dr. D.K.Mishra D/O Shri Himayatulla Khan Behind Post Office, Patna Distt: Koriya, Chhattisgarh (497331) khanshahnaj44@gmail.com Mob.no Address : Director of Farms, Professor and Head Department of Plant Breeding and Genetics Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur (M.P.) contact number : Degree awarded : M.Sc. (Ag.) Plant Breeding and Genetics Year of award of Degree : 2014 Major Subject : Plant Breeding and Genetics Total number of pages in the thesis Number of words in the abstract : 112 : 784 Dr. D.K.Mishra Dr. D.K. Mishra Kumari Shahnaz (Chairman of Advisory committee) (Professor & Head) (Student)

124 ABSTRACT The present investigation entitled Characterization and Quantitative Analysis in Aromatic Rice Germplasm was carried out at Seed Breeding Farm of J.N.K.V.V, Jabalpur with one hundred and forty nine lines in Randomized Complete Block Design with three replications during Kharif Morphological observations (as per DUS guideline) viz., basal leaf sheath colour, leaf pubescence of blade surface, leaf auricle, leaf anthocyanin colouration of auricle leaf shape of ligules, leaf ligule colour, flag leaf attitude of blade, stem-anthocyanin colouration of nodes, spikelet colour of stigma, spikelet density of pubescence, sterile lemma colour, spikelet- colour tip of lemma, panicle exsertion, panicle- attitude of branches, panicle- awns, distribution of awns colour of awns were recorded. The quantitative observation were recorded on 10 randomly selected plants e.g. days to fifty percent flowering, plant height, number of tillers plant -1, number of productive tillers plant -1, days to maturity, panicle length, average panicle weight per plant, fertile spikelets per panicle, sterile spikelets per panicle, number of spikelets per panicle, spikelet fertility percent, spikelet density, 1000 grain weight, grain yield per plant, biological yield per plant, panicle index, harvest index, and qualitative observation were grain length, grain width, decorticated grain length, decorticated grain width, hulling percent, milling percent. The objective of this study was to estimate genetic variability for yield and quality traits in aromatic rice genotypes, to study genotypic and phenotypic association among all the traits, to estimates direct and indirect effect of yield and quality attributes on seed yield, to indentify superior aromatic rice genotypes based on yield and quality traits and to validate the reported SSR markers on selected genotypes for yield related traits. Characterization of genotypes concluded that the characters viz., basal leaf sheath color, pubescence of blade surface, auricle, auricle color, shape of ligule, ligule color, flag leaf-attitude of blade, spikelet-color of stigma, stemanthocyanin coloration of nodes, spikelet-density of pubescence, sterile lemma color, spikelet-color of tip of lemma, panicle exsertion, panicle-attitude of branches, awn, distribution of awns, color of awns had sufficient amount of variability. Analysis of variance indicated that the differences among genotypes were highly significant for all the traits studied. This indicated that the genotypes had

125 sufficient amount of variability. The variability among genotypes ranged from number of spikelet per panicle to decorticated grain width. High GCV and PCV exhibited by unfilled spikelet per panicle followed by spikelet no. per panicle, harvest index, grain yield, panicle weight, fertile spikelet no. per panicle, biological yield, spikelet density, productive tillers per plant, total tillers per plant, decorticated grain length, test weight, culm length, panicle index, plant height, spikelet fertility %, grain length, decorticated grain length, grain width, days to 50% flowering, panicle length, days to maturity, hulling % and smallest for milling %. The characters fertile spikelet per panicle, spikelet per panicle, culm length, biological yield, panicle index, spikelet density and test weight exhibited high heritability coupled with high genetic advance. It indicates that the heritability is most likely due to additive gene effect and selection may be effective. Grain yield plant -1 exhibited positive and significant association with panicle weight, Harvest index, Panicle index, Productive tillers per plant, Biological yield per plant, Total tillers per plant, Spikelet fertility %, Fertile spikelet per panicle, test weight, Grain length, Panicle length and Spikelet number per panicle. The highest positive direct effect on seed yield plant -1 was observed for Plant height, spikelet density, harvest index, milling %, biological yield, panicle weight, grain width, plant index, total tillers per plant, test weight, and days to 50% flowering had direct positive effect on grain yield. It indicates true relationship between them and direct selection for these traits will be rewarding for yield improvement. At molecular level, all ten markers used were polymorphic. The total number of alleles amplified was 62 with a mean value The highest number of allele were nine amplified by markers RM 276 and RM 223. The highest major allele frequency, gene diversity, heterozygosity and polymorphic information content were (RM 259 and RM 468), (RM 234), (RM 502 and RM 276) and (RM234), respectively. Unique allele and multiple alleles were amplified by four markers RM256, RM276, RM236 and RM234. The cluster analysis on basis of molecular analysis revealed that the selected fifteen genotypes were divided into two major clusters group. Considering, the morphological characterization, quantitative analysis and molecular level it could be concluded that best genotypes are IR , SUGANDA MATI, IR , KRISHNA KAMOD, IET 12601, MUGAD SUGANDHA, IR , BASMATI MAHON 381, IR , UPR , IR , PUSA BASMATI 6, IET and IR Thus, genotypes might be further used in breeding programmes.

126 CURRICULAM VITAE Name of the author- Ku. Shahnaz Place- Baikunthpur (C.G.) Date of Birth- 4 th February 1990 The author of this thesis Ku. Shahnaz, D/o Shri. Himayatulla Khan was born on 4 th February 1990 at Baikunthpur (C.G.) She has joined the following institutions and successfully completed the degree of Msc. (Ag.) during the year S. No. Institutions 1 JNKVV, Jabalpur (M.P) 2 IGKV, Raipur (C.G.) 3 Kendriya Vidyalaya Baikunthpur, (C.G.) She has got the following degrees, S. No. Degrees granted University/Board Year 1 M.Sc. (Ag.) JNKVV, Jabalpur B.Sc. (Ag.) IGKV, Raipur (C.G.) th CBSE Board 2007 She has following scientific interests- Scientific interests a. Genetics and Plant Breeding b. Molecular Breeding c. Research and Development Scholarship and award She received IGKV merit scholarship in B.Sc. (Ag.) for 2 nd year, 3 rd year and 4 th year. Participated and obtained winning certificate in various inter and intra college cultural competition during B.sc. (Ag.). For the partial fulfilment of the master s degree programme she was allotted a research problem on Characterization and Quantitative analysis in Aromatic Rice Germplasm which was successfully conducted by her and being submitted in the form of the thesis.