ISSN International Journal of Innovative and Applied Research (2017) Journal home page: RESEARCH ARTICLE

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1 Journal home page: RESEARCH ARTICLE PERFORMANCE OF FUSARIUM WILT RESISTANT CHICKPEA (CICER ARIETIUM L.) GENOTYPES DEVELOPED THROUGH MABC D. M. Mannur, Satishkumar and Sharanabasappa B. Yeri Agriculture Research Station, Kalaburagi , Karnataka, India *Corresponding Author:- D. M. Mannur. Abstract: Fusarium wilt is the major constraint in chickpea cultivation. Developing wilt resistant genotype is the most effective means of wilt management in chickpea. MABC approach was used to develop wilt resistant genotypes. Experiment was carried out to estimate genetic parameters among 10 MABC lines of chickpea including three standard checks across three locations Viz., Gulbarga (L-1), Bidar (L-2) and Dharwad (L-3). Analysis of variance for mean sum of squares for important quantitative traits such as plant height (cm), number of primary branches per plant, number of pods per plant, grain yield per plant (g), 100 seed weight (g) and net plot yield (kg) revealed significant differences between the genotypes across the locations, except for plant height in L-3 indicating the existence of considerable amount of variability among the genotypes. This was evident by larger difference between minimum and maximum range value for traits under study across the locations. Narrow difference between phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) was observed for all traits except number of pods per plant in L-1 indicating negligible influence of external environment on the expression of traits. High heritability coupled high genetic advance expressed over per cent mean (GAM) was recorded for grain yield per plant, 100 seed weight and net plot yield in L-1, 100 seed weight and net plot yield in L-2 indicating preponderance of additive gene action, simple selection could be effective for improvement of these traits. Overall the performance of the two MABC lines SA-1 and SA-2 were better across all the three locations. Key Words:-Genetic parameters, PCV, GCV, Heritability, GAM. Introduction:- Chickpea (Cicer arietinum L.) is a cool season food legume commonly known as Bengal gram or Garbanzo. It is cultivated and consumed across the globe including semi-arid tropics in India. The crop is largely grown on residual moisture during Rabi season in India. Though India stands first in area and production but the productivity is very low in the subcontinent. Low productivity of chickpea in India is attributed to several biotic and abiotic stresses. Fusarium wilt, caused by Fusarium oxysporum Schlechtend: Fr. f. sp. ciceris (Padwick) Matuto& K. Sato, is one of the major constrain to chickpea productivity. The disease is widespread found in all the chickpea growing areas (Nene et al., 1989; Halila and Strange 1996; Sharma and Muehlbauer, 2005). Annually 10-15% yield losses is associated to wilt in chickpea (Jalali and Chand, 1992), seldom favourable condition accelerate fusarium wilt epidemics leading to crop devastation (Halila and Strange, 1996; Navas-Corte s et al., 2000). The pathogen can survive for many years even in the absence of host plants and build permanent disease inoculum (Haware et al., 1996) thus pretense its control difficult. Chemical and fungicides use to control fusarium wilt not only adds to the cost of cultivation but also contribute to environmental pollution. The most economic, effective and eco-friendly means for management of wilt disease is to deploy host plant resistance by use of resistant cultivars. Even effectiveness of such a cultivar is further limited by existence of different races of pathogens (Mannur et al., 2015). Several efforts are made in chickpea breeding to develop high yielding chickpea cultivars. Introgression lines resistance to FW targeting foc4 loci were developed by crossing Annigeri-1 an elite but otherwise susceptible cultivar of chickpea with WR 315 (genetic stock from Kanpur) a solitary and most promising source of resistance towards all the races of fusarium wilt, by the aid of marker assisted backcross (MABC) breeding at Agriculture Research Station, Kalaburagi. The advanced generation MABC lines were found to be resistant to wilt and phenotypically mimicking the elite recurrent parent (Annigeri-1) with respect to all the agronomic and productivity 47

2 traits (Mannur et al., 2015). These MABC lines were evaluated under AVT-1 at national level, few lines were found to be superior for most of the agronomic and yield attributing traits along with resistant to wilt and ranked top among the other national entries. The present study is focused on evaluation of these wilt resistant MABC lines for their yield and yield attributing traits across three locations in Karnataka. Material and Methods:- Advanced progenies of MABC lines were stringently evaluated under wilt sick plot to identify resistant lines during and Based on resistance reaction to wilt disease ten MABC lines were selected for evaluation under multilocation. In the present investigation all the ten MABC lines along with three standard checks were sown in randomized block design with three replications during Rabi at Gulbarga (L-1), Bidar (L-2) and Dharwad (L-3). All the recommended package of practices was adopted to raise the crop. Five randomly selected plants from each genotype in each replication were used for recording the observations to estimate the genetic parameters among genotypes. The data was recorded on quantitative traits such as plant height (cm), plant height from bottom to first pod bearing length (cm), number of primary branches, number of pods per plant, grain yield per plant (g), 100 seed weight (g) and net plot yield (g). The mean values of all the quantitative characters were subjected to statistical analysis using windostat 8.1. The genetic parameters such as phenotypic or genotypic coefficient of variation and heritability were classified according to Sivasubramanian and Menon (1973) and Robinson et al. (1951), respectively. Results and Discussions:- Analysis of variance revealed significant differences between the genotypes for all traits except plant height in L-3indicating existence of genetic variability among genotypes for different traits (Table 1). A wide range of variability observed for maximum and minimum values for all the traits across the locations suggested greater scope for practicing selection and improvement of specific traits (Ramanappaet al., 2013). Narrow difference between PCV and GCV was observed for all traits except number of pods per plant in L- 1 indicating negligible influence of environment on the expression of traits (Table 2). Similar observations were made by Parammeshwarappa et al., 2012 for days to 50% flowering, plant height, 100 seed weight and grain yield per plant in chickpea. Further the magnitude of PCV was slightly higher than corresponding GCV for all traits across the three locations indicating least influence of environment in the expression of these traits (Ramanappa et al., 2013). High PCV with moderate GCV were recorded for number of pods per plant and grain yield per plant in L-1and L-2, whereas Moderate PCV and GCV was recorded for 100 seed weight and net plot yield in L-1and L-2 suggesting existence of genetic variability for these traits. Similar results were obtained by Qurban Ali and Muhammad Ahsan, 2012 in chickpea for number of pods per plant, number of seeds per pod, grain yield per plant and 100 seed weight. The coefficient of variation give idea about extent of variability found for different traits but not the heritable portion, hence to obtain the heritable portion for different traits it is necessary to compute the heritability estimates (Parammeshwarappa et al., 2012). Heritability with genetic advance expressed as per cent mean (GAM) depicts the predicted genetic gain and nature of gene action operating among the genotypes. High heritability coupled with high GAM was observed for grain yield per plant, 100 seed weight and net plot yield in L-1 while, 100 seed weight and net plot yield in L-2 indicating preponderance of additive gene action. Hence these traits could be improved through simple selection. Present results are in accordance with the findings of Patil (1996), Sidramappa (2003) and Parameshwarappa et al. (2012). High heritability with moderate GAM was observed for plant height in L-1 indicating existence of both additive and non additive gene action, care must be taken while practicing selection for this trait. Similar observations were made by Hasan and Deb, 2017 for plant height in chickpea. Moderate heritability coupled with moderate GAM was observed for number of primary branches per plant, number of pods per plant in L-2 and number of primary branches per plant and net plot yield in L-3 respectively, suggesting preponderance of non additive gene action thus selection for traits may not be taken in to account or manifested carefully. Moderate heritability coupled with low GAM was observed for number of primary branches per plant in L-1,plant height in L-2, whereas grain yield per plant and 100 seed weight in L-3 indicating high influence of environment on expression of these traits thus selection for such traits ineffective. The results are accordance with Babbar et al., 2012 in chickpea for number of primary branches per plant. Overall the performance of the MABC line showed considerable variation for their response to important agronomic and productivity traits (Table 3). However two line SA-1 and SA-2 performed better for all most all the traits studied. The MABC line SA-1 showed higher number of primary braches, grain yield per plant and net plot 48

3 yield than the standard check at all the three locations, additionally the line also showed higher 100 seed weight at L-3. The second line SA-2 also showed better responses to the above traits (Figure1). These two lines also performed better at national trails in AVT and ranked top among the national entries. Thus further evaluation and validation of these lines in subsequent seasons would help in delivering promising wilt resistant chickpea cultivar to the farming community so as to double the farmer s income by use of superior seed material. Table1:-MSS, mean and range for different quantitative traits of chickpea in different locations MSS Mean Range Traits GLB BDR DWD GLB BDR DWD GLB BDR DWD PH 24.30** 11.85* PB 0.16** 0.26** 0.21** NPB ** 72.35** 26.58* GY 6.37** 5.94** 0.43* SW 14.00** 14.00** 3.40** NPY 0.06** 0.04** 0.01* GLB= Gulbarga; BDR= Bidar; DWD= Dharwad; PH=Plant height; SW= Seed WeightNPB=No. of primary Table 2:-Estimates of genetic parameters for different traits across three locations Locations Parameters Traits PH NPB NP GY 100 SW NPY GCV (%) PCV (%) GLB h 2 (%) GA GAM (%) GCV (%) PCV (%) BDR h 2 (%) GA GAM (%) GCV (%) PCV (%) DWD h 2 (%) GA GAM (%) GLB= Gulbarga; BDR= Bidar; DWD= Dharwad; PH=Plant height; SW= Seed Weight; NPB=No. of primary Table 3:-top performing entries for different traits under different locations Locations PH PB NPB GY 100 SW NPY WR-315 SA-4 SA-1 SA-1 JG-11 SA-1 GLB JG-11 SA-9 SA-8 SA-2 SA-8 SA-2 SA-7 SA-1 SA-2 A-1 A-1 A-1 WR-315 SA-1 SA-1 SA-1 JG-11 SA-1 BDR SA-7 SA-3 SA-2 SA-2 A-1 SA-2 JG-11 SA-2 SA-3 SA-3 SA-8 SA-4 JG-11 SA-1 SA-1 SA-1 JG-11 SA-1 DWD SA-9 SA-2 SA-2 A-1 SA-7 SA-9 SA-4 SA-6 SA-10 SA-2 SA-1 SA-2 Across three locations SA-1 ranked top followed by SA-2 GLB= Gulbarga; BDR= Bidar; DWD= Dharwad; PH=Plant height; SW= Seed Weight; NPB=No. of primary 49

4 Figure 1:-Fusarium wilt reaction of SA-1 and SA-2 along with Annigeri-1 and susceptible check References:- 1. Babbar A, Prakash V, Tiwari P, Iquebal MA. (2012): Genetic variability for chickpea (Cicer arietinum L.) under late sown season. Legume Research, 35 (1): Halila MH, Strange RN. (1996): Identification of the causal agent of wilt of chickpea in Tunisia as Fusarium oxysporumf.sp. ciceri race 0. Phytopathlogy Medit, 35: Hasan TM, Deb AC. (2017): Assessment of genetic variability, heritability, character association and selection indexes in chickpea (Cicer arietinum L.). International Journal of Biosciences, 10(2): Haware MP, Nene YL, Natarajan M. (1996): Survival of Fusarium oxysporum f. sp. ciceri in the soil in the absence of chickpea. Phytopathlogy Medit, 35: Jalali BL, Chand H. (1992): Chickpea wilt. In: Singh US, Mukhopadhayay AN, Kumar J, Chaube HS (eds) Plant diseases of international importance, vol 1, diseases of cereals and pulses. Prentice Hall, Englewood Cliffs, New York, Mannur DM, Yeri SB, Mahiboobsa M, Shankergouda I, Jayalakshmi SK. (2015): Introgression of Fusarium wilt resistance loci (foc 4) from WR315 to a widely adopted cultivar Annigeri-1 through phenotypic elimination Journal of Food Legumes 28(4): Navas-Corte s JA, Alcala -Jime nez AR, Hau B, Jime nez-dı az RM. (2000): Influence of inoculum density of races 0 and 5 of Fusarium oxysporum f. sp. ciceris on development of Fusarium wilt in chickpea cultivars. European Journal of Plant Pathology, 106: Nene YL, Haware MP, Reddy NMV, Philps JP, Castro EL, Kotasthane SR, Gupta O, Singh G, Shukia P, Sah RP. (1989): Identification of broad based and stable resistance to wilt and root rots in chickpea. Indian Phytopathology,42: Parameshwarappa SG, Salimath PM, Upadhaya HD, Patil SS, kajjidoni ST. (2012): Genetic variability studies in minicore collection of chickpea (Cicer arietinum L.) under different environments. Karnataka Journal of Agricultural Sciences, 25 (3): Patil SB. (1996): Variability studies in segregating populations of chickpea. Legume Research, 13(1): Qurban Ali and Muhammad Ahasan. (2012): Estimation of variability and correlation analysis for quantitative traits in chickpea (Cicer arietinum L). International Journal for Agro Veterinary and Medical Sciences, 6(4): Ramanappa TM, Chandrashekara K, Nuthan D. (2013): Analysis of Variability for Economically Important Traits in Chickpea (Cicer arietinum L.). International Journal of Research in Applied, Natural and Social Science, 1(3): Robinson HF, Comstock RE, Harvey PH. (1951): Genotypic and phenotypic correlations in corn and their implications in selection. Agronomy Journal, 43: Sharma KD, Muehlbauer FJ. (2005): Fusarium wilt of chickpea: physiological specialization, genetics of resistance and resistance gene tagging. Euphytica, 157:

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