SELECTION INDICES FOR CANE YIELD IN SUGARCANE (SACCHARUM SPP.)

SELECTION INDICES FOR CANE YIELD IN SUGARCANE (SACCHARUM SPP.) Shanthi Priya M. 1, Reddy K.H.P. 1, Hemanth Kumar M. 2, Rajarajeswari V. 1, Mohan Naidu G. 1, Narasimhulu R. 1, Rupesh Kumar Reddy B. 1 and Mohan Reddy D. 1 1 S.V.Agricultural College, Tirupati, Andhra Pradesh 2 Agricultural Research Station, Perumallapalle, Andhra Pradesh *Author for Correspondence ABSTRACT Seventy seven genotypes of sugarcane were evaluated in second clonal stage. Selection indices were formulated considering cane yield and six of its component characters which showed high correlation with cane yield. Among seven characters, cane yield (X 1 ) was considered as dependent character while, other characters viz., shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ), single cane weight (X 5 ), fibre yield (X 6 ) and commercial cane sugar yield (X 7 ) were considered as independent variables. The selection indices constructed with the inclusion of more than one character gave higher genetic advance and relative efficiency over straight selection for cane yield. For indirect selection the index involving the combination of three characters viz., stalk volume (X 3 ), number of millable canes (X 4 ) and single cane weight (X 5 ) which exhibited maximum relative efficiency of 1010.31 with genetic advance of 280.93 could be considered for selection schemes to improve cane yield. INTRODUCTION Sugarcane is an important cash crop and raw material for sugar industry which is the second largest agro based industry of India. It assumes an important position in the economy of the country. Its contribution to agricultural GDP is 10% which is significant as the crop is grown in only 2.57% of the gross cropped area in the country (SBI, 2011). Sugarcane crop serves as the major source for a variety of products such as sugar, jaggery, molasses, bagasse, filter cake, out of which sugar and jaggery are meant for daily use as consumable products while other byproducts have industrial significance. Sugarcane is grown in an area of 17.53 M ha worldwide producing 1286.67 M t of cane with a productivity of 73.40 t ha -1 (FAOSTAT, 2011). In India sugarcane is cultivated in an area of 5.03 M ha producing 342.19 M t of cane with an average productivity of 68.1 t ha -1 (Sugar India, 2012). In India sugarcane is grown in both tropical and sub tropical regions. Uttar Pradesh, Maharastra, Karnataka, Tamil Nadu, Gujarat and Andhra Pradesh are the major cane growing states. In Andhra Pradesh it is grown in an area of 1.8 lakh ha producing 140.4 lakh tonnes of sugarcane with an average productivity of 78.0 t ha -1 (Sugar India, 2012). In India 24.39 M t of sugar is produced, but the projected requirement of sugar by 2030 is 36 M t which has to be achieved from the existing cane area through improved varieties for cane yield and sugar recovery as further expansion in area is not possible. Proper exploitation of variability in a crop like sugarcane with a complex ploidy and a high level of heterozygosity is a complicated process (Babu et al., 2009). Breeding for higher cane yield and quality traits requires basic information on the extent of genetic variation in a population and its response to selection. The main objective of a selection programme is to shift the mean to a new peak by directional selection. Continuous selection in one character may result in a loss or gain in the other characters, which are also of equal importance. On the other hand, if selection is made for a number of characters, the efficiency of selection would be reduced. So the plant breeder will have to base his selection on a combination of a few important characters related to the main character under consideration in the form of a selection index by appropriate weightages assigned to the phenotypic values of each character so that the genetic gain in the character under consideration will be maximum without any loss in other important characters. Selection indices provide the means for making use of correlated characters for higher efficiency in selection for 77

characters of low heritability. Selection index is a tool, which breeder can use successfully for selection on several characters simultaneously by discriminating the desirable ones on the basis of phenotypic performance. MATERIALS AND METHODS The present investigation was carried out at Agricultural Research Station, Perumallapalle (Acharya N.G.Ranga Agricultural University), situated in the Southern Agro-climatic Zone of Andhra Pradesh with seventy seven genotypes of sugarcane that were planted in a randomized block design with two replications during April, 2011. Each entry was planted in 2 rows of 5 m length spaced at a distance of 80 cm between rows with 4 three budded setts per meter as seed rate. Observations were recorded on each entry for the traits viz., no. of tillers at 120 DAP, shoot population at 180, 240 DAP, NMC at harvest, no. of green leaves at 90, 120, 240 DAP and at maturity, biomass per cane (kg), internode number, internode length (cm), stalk length (cm), stalk diameter (cm), stalk volume (cm 3 ), single cane weight (kg), fibre content (%), Brix (%), sucrose (%), CCS (%), juice purity (%), pol % cane, juice extraction (%), total sugars (%), fibre yield (tha -1 ), CCS yield (tha -1 ), theoretical yield of alcohol (g/100ml) and cane yield (tha -1 ). The technique of Discriminant function developed by Fisher (1936) was adopted to know the true genotypic worth of yield and its components and to have computational formulae for construction of selection indices which when applied to select plants can bring about effective improvement in yield compared to straight selection for yield. Smith (1936) has illustrated the use of discriminant function in plant selection. A number of different selection indices are constructed using 2, 3, n combination of characters. The expected genetic advance based on the composition of characters that was included for formulation of the various selection indices was calculated as per the formula of Robinson et al., (1951). The relative efficiency of each selection index formulated was evaluated by comparing with yield alone which is considered as 100 per cent efficient as given by Brim et al., (1959). RESULTS AND DISCUSSION Selection indices were formulated considering cane yield and six of its component characters which showed high correlation with cane yield. Among seven characters, cane yield (X 1 ) was considered as dependent character while, other characters viz., shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ), single cane weight (X 5 ), fibre yield (X 6 ) and commercial cane sugar yield (X 7 ) were considered as independent variables. The expected genetic advance was computed for each of the indices at five per cent selection intensity. The discriminant functions and the estimated values of genetic advance (GA) and relative efficiency (RE) for each combination of characters are presented in Table 1 and briefly discussed below. Higher relative efficiency of 1092.49 coupled with high genetic advance (303.78) was exhibited by the combination involving all the seven traits viz., cane yield (X 1 ), shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ), single cane weight (X 5 ), fibre yield (X 6 ) and commercial cane sugar yield (X 7 ) followed by the combination of six traits viz., cane yield (X 1 ), shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ), fibre yield (X 6 ) and commercial cane sugar yield (X 7 ) which recorded relative efficiency of 1090.22 with genetic advance of 303.15. Among single characters, stalk volume (X 3 ) was highly efficient with relative efficiency of 670.00 and high genetic advance of 186.30, compared to the direct selection based on cane yield (X 1 ), whereas among two character combinations, maximum relative efficiency of 993.66 was observed for the combination of stalk volume (X 3 ) and single cane weight (X 5 ) with high genetic advance of 276.30. However, in case of three character combinations, the combination involving cane yield (X 1 ), stalk volume (X 3 ) and single cane weight (X 5 ) exhibited higher relative efficiency of 1062.83 coupled with high genetic advance of 295.53. 78

Among four character combinations, cane yield (X 1 ), stalk volume (X 3 ), single cane weight (X 5 ) and commercial cane sugar yield (X 7 ) exhibited high relative efficiency of 1074.16 coupled with high genetic advance of 298.68, whereas among five character combinations, maximum relative efficiency of 1081.45 was observed for the combination of cane yield (X 1 ), shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ) and fibre yield (X 6 ) with high genetic advance of 300.71. Selection indices were formulated by several workers in sugarcane to suit different contexts. Miller et al. (1978) studied four hybrid populations of sugarcane and evolved suitable selection indices for them and reported high genetic gain for cane yield when the index was based on stalk height, stalk diameter, millable stalk number per plot and stalk yield. Nair and Sreenivasan (1989) reported that highest relative efficiency was observed for cane yield with the index involving stalk yield, millable stalk number per cane, stalk diameter, stalk weight and stalk height. Charumathi (2011) suggested a combination involving four characters viz., length of millable cane and diameter of cane, single cane weight and number of canes per clump in seedling nursery and clonal stages which showed the highest genetic advance as well as relative efficiency over straight selection for cane yield. Table 1: Discriminant functions, their Genetic Advance (GA) and Relative Efficiency (RE) over straight selection for cane yield in sugarcane S.No Discriminant function GA RE 1 Y= 0.91 X 1 27.81 100.00 2 Y= 0.92 X 2 14.49 52.13 3 Y= 0.46 X 3 186.30 670.00 4 Y= 0.71 X 4 11.79 42.42 5 Y= 0.50 X 5 0.12 0.42 6 Y= 0.92 X 6 4.30 15.46 7 Y= 0.92 X 7 3.23 11.60 8 Y= 0.37 X 3 + 899.25 X 5 276.30 993.66 9 Y= -1.62 X 1 + 0.40 X 3 + 1094.84 X 5 295.53 1062.83 10 Y= 0.38 X 3-3.22 X 4 + 862.47 X 5 280.93 1010.31 11 Y= 0.48 X 1 + 0.38 X 3 + 1084.32 X 5-19.51 X 7 298.68 1074.16 12 Y= 9.77 X 1 + 4.89 X 2 + 0.38 X 3-16.16 X 4-9.91 X 6 300.71 1081.45 13 Y= 4.11 X 1 + 4.37 X 2 + 0.40 X 3-9.79 X 4 + 481.11 X 5 298.68 1074.14 14 Y= 11.41 X 1 + 4.32 X 2 + 0.37 X 3-15.77 X 4-9.45 X 6 303.15 1090.22-15.67 X 7 15 Y= 7.53 X 1 + 4.41 X 2 + 0.37 X 3-10.48 X 4 + 408.18 X 5 303.78 1092.49-8.95 X 6-15.32 X 7 X 1 = Cane yield X 2 = Shoot population at 240 DAP X 3 = Stalk volume X 4 = Number of millable canes X 5 = Single cane weight X 6 = Fibre yield X 7 = Commercial cane sugar yield 79

Table 2: Top ranking genotypes (10%) based on the best selection index for cane yield in sugarcane Cane yield ( t ha -1 ) Rank Genotype Mean 1 2010T-84 169.48 1959 2 2010T-146 205.49 1763 3 2010T-124 120.35 1758 4 2010T-152 166.63 1500 5 2010T-344 154.50 1464 6 2010T-4 165.41 1429 7 2010T-153 107.86 1405 Mean of the above seven genotypes 155.67 Population mean 110.80 %gain over Population mean 140.50 Figure 1: Selection index score of sugarcane genotypes for cane yield Scoring of sugarcane genotypes for cane yield based on the best selection index is depicted in Figure 1. Selection of top ten percent of the genotypes (Table 2) based on the best selection index has shown 140.50% gain over population mean. 80

Since fibre yield and commercial cane sugar yield are derived characters, more emphasis during selection could be given on the directly measurable characters to get the accurate results. Hence, the combinations without fibre yield and commercial cane sugar yield could be considered for selection for cane yield. Among them the combination involving the traits cane yield (X 1 ), shoot population at 240 DAP (X 2 ), stalk volume (X 3 ), number of millable canes (X 4 ) and single cane weight (X 5 ) recorded maximum relative efficiency of 1074.14 with genetic advance of 298.68. When indirect selection scheme excluding cane yield in formulating index is to be followed, the index involving the combination of three characters viz., stalk volume (X 3 ), number of millable canes (X 4 ) and single cane weight (X 5 ) which exhibited maximum relative efficiency of 1010.31 with genetic advance of 280.93 could be considered for selection schemes to improve cane yield. REFERENCES Babu C, Koodalingam K, Natarajan US, Shanthi RM and Govindaraj P (2009). Assessment of rind hardness in sugarcane (Saccharum spp. Hybrids) genotypes for development of non lodging erect canes. Advances in Biological Research 3(1-2) 48-52. Brim CA, Johnson HW and Cockerham CC (1959). Multiple selection criteria in soybeans. Agronomy Journal 51 42-46. Charumathi M (2011). Studies on selection indices in sugarcane (Saccharum officinarum L.) Ph.D., Thesis submitted to the Acharya N. G. Ranga Agricultural University Hyderabad. FAOSTAT, Available at: http://faostat.fao.org. Fisher RA (1936). The use of multiple measurements in taxonomic problem. Annals of Eugenics 7 179-88. Miller JD, James NI and Lyrene PM (1978). Selection indices in sugarcane. Crop Science 18 369-372. Nair NV and Sreenivasan TV (1989). Analysis of stalk yield components in Saccharum officinarum L. Sugar Cane 2 4-5. Robinson HF, Comstock RE and Harvey PH (1951). Genotypic and phenotypic correlation in corn and their implications in selection. Agronomy Journal 43 282-287. SBI (2011). Vision 2030. Sugarcane Breeding Institute, Coimbatore. Smith HF (1936). A discriminant function for plant selection. Annals of Eugenics 7 240-250. Sugar India (2012). Sugar India Year book. Jain Book Agency, New Delhi. 81