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Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 06 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.706.383 Wheat Genotypes under Restricted Irrigated Conditions Rana Saha, Hausila Prasad Singh*, Sandeep Kumar, Md. Ekram Hussain and R. S. Shukla Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur - 482004, India *Corresponding author ABSTRACT Keywords Correlation coefficient, Genetic variability, harvesting index and path coefficient Article Info Accepted: 22 May 2018 Available Online: 10 June 2018 Wheat genotypes were shown under restricted irrigated condition, based on morphological traits and their genetic variability, correlation coefficient analysis, path coefficient analysis and rank germplasm based on principal component analysis for yield and yield attributing traits. This investigation was carried out with 30 genotypes of wheat using 17 traits viz., days to 50% flowering, days to maturity, plant height, number of effective tillers per plant, number of ears per plant, number of spikelets per spike, ear length, ear weight, peduncle length, number of grains per ear, 1000-grain weight, grain yield per plant, biological yield per plant, harvest index, relative water content, chlorophyll content and canopy temperature. The high heritability coupled with high genetic advance as percentage of mean was recorded for ear weight, harvest index, biological yield, number of ears per plant, grain yield, number of effective tillers per plant, peduncle length, number of grains per ear, ear length, number of spikelets per spike, total grain weight and canopy temperature. The high heritability coupled with moderate genetic advance was recorded for chlorophyll content and relative water content whereas, high heritability coupled with low genetic advance was observed for plant height, days to 50% heading and days to maturity. On the basis of correlation and path studies of the present investigation, most important traits identified among the promising genotypes of wheat were biological yield, number of ears per plant and harvest index. On the basis of principal component analysis 5 principal components (PCs) showed about 68.05% variability and germplasm viz., PYT61, PYT-101, PYT-22, PYT-49, PYT-40, PYT-16, PYT-97, PYT-51, PYT-115 and PYT27 had been identified as promising genotypes as they posses higher values for yield and yield attributing traits. Introduction Bread wheat is the world's second most important staple food crop for more than 35 percent of world's population next to the rice. It is cultivated under a wide range of climatic conditions favoured by cool, moist weather followed by dry warm weather. It produces about 20% food resources of the world. India is the second largest wheat producer in the world next to China with a production level of 95.91 million tonnes (FAO 2015). Despite remarkable growth in food production, the risks were exposed by food crisis in the recent years. Therefore, wheat production must continue to increase by 2% annually, more 3251 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 particularly in developing world including South-East Asia to meet future demands imposed by population and prosperity growth (Reynolds et al., 2008). Accordingly, understanding and improving plant survival and growth under restricted water availability is of central significance in contemporary plant science. This challenge will probably be further compounded by reduced water availability and increased temperature due to global warming. Since, the estimation of genetic parameters like character association and path coefficient serve as an important tool in breeding programmes to improve the concern traits. Simultaneous inheritance of characters that help to decide breeding strategies may vary with environmental conditions and set up of experimental genotypes. Hence, it is essential to conduct studies in different environment with diverse available genotypes. The interaction effects of wheat genotypes with water and temperature stress on grains, days to maturity, plant height, peduncle length, number of grains per ear, number of spikelets per spike, 1000- grain weight, chlorophyll content, canopy temperature and RWC have generally been worked out which were established facts to contribute more for yield under restricted irrigation. Materials and Methods A field experiment was carried out under Wheat Improvement Project Department of Plant Breeding and Genetics at Seed Breeding Farm, College of Agriculture, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur under restricted irrigated conditions. The experimental area occupied was quite uniform in respect of topography and fertility. The experimental material consists of 30 wheat genotypes including 3 checks viz., DBW71, DBW107 and K307. The experiment was conducted in three replications under Randomized Complete Block Design. Each plot consisted of six rows of 2.5 m length and 22.5 cm. Details of genotypes are listed in table 1. Correlation coefficient Correlation coefficients were calculated for a combination of all characters under study at genotypic, phenotypic and environmental levels with the help of formula suggested by Miller et al., (1958). To test the significance of phenotypic correlation coefficients, the estimated values were compared with the tabulated values of Fisher and Yates (1963) at n-2 d.f. at two levels of probability, viz., 5% and 1%. Path coefficient analysis Path coefficient is a standardized partial regression, which measures the direct influence of one variable upon another and allows partition of correlation coefficient into components of direct and indirect effects. The proportion of direct and indirect contributions of various characteristics to the total correlation coefficients with seed yield was estimated through path coefficient analysis as suggested by Wright (1921) and elaborated by Dewey and Lu (1959). To estimate various direct and indirect effects, the sets of simultaneous equations were formed and solved for estimating direct and indirect effects. Residual effect measures the contribution of the characters not considered in the causal scheme. Results and Discussion Correlation coefficient The phenotypic and genotypic correlation coefficients for different pairs of character were studied and results are presented in table 2 and 3. The correlation coefficients were tested for their significance at (n-2) degree of 3252 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 freedom. In general, the result showed that genotypic correlation coefficients were lower than phenotypic correlation coefficient for almost all the characters under study, which were in turn higher than the environmental correlation. Days to 50% heading Days to 50% flowering had a highly significant positive correlation with days to maturity (0.7299), chlorophyll content (0.2959) and harvest index (0.2924). Association of days to 50% heading with other traits studied were very low in magnitude and non-significant. Days to maturity Days to maturity had highly significant positive correlation with grain yield per plant (0.4706), number of grains per ear (0.4467), number of spikelets per ear (0.4164), biological yield (0.3513), and 1000 grain weight (0.3121). Significant positive correlation with ear weight (0.2428). Whereas, RWC (-0.2363) had a significant negative effect on days to maturity. Association of days to maturity with other traits studied were very low in magnitude and non-significant. Plant height Plant height had a highly significant positive correlation with peduncle length (0.7973), ear weight (0.6898), ear weight (0.6668), number of spikelets per spike (0.2969) and significant positive correlation with canopy temperature (0.2258). Association of plant height with other traits studied were very low in magnitude and non-significant. Peduncle length Ear weight (0.8617), ear length (0.8584), number of spikelets per spike (0.5918), canopy temperature (0.3378) number of grains per ear (0.3375) had a positive highly significant correlation with peduncle length. Grain yield per plant (0.2926) and biological yield (0.2305) had positive significant with peduncle length. Association of peduncle height with other traits studied was very low in magnitude and non-significant. Ear length Ear length had a highly significant positive correlation with ear weight (0.9652), number of spikelets per spike (0.6515), number of grains per ear (0.4560), canopy temperature (0.3406) and grain yield per plant (0.3240). Harvest index (0.2309) had positive significant with ear length. Association of ear length with other traits studied were very low in magnitude and non-significant. Ear weight Number of spike lets per spike (0.696), number of grains per ear (0.4148), grain yield per plant (0.3318) and canopy temperature (0.3063) had positive highly significant correlation with ear weight. Harvest index (0.2193) had positive significant with ear weight. Association of ear weight with other traits studied were very low in magnitude and nonsignificant. Number of effective tillers per plant Number of effective tillers per plant had positive highly significant with a number of ears per plant (0.9952) and positive significant with (0.2574). Harvest index (-0.2399) had negative significant with a number of effective tillers per plant. Association of a number of effective tillers per plant with other traits studied were very low in magnitude and nonsignificant. 3253 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Number of ears per plant Number of ears per plant had positive significant with biological yield (0.2619) and negative significant with harvest index (0.2420). Association of a number of ear per plant with other traits studied were very low in magnitude and non-significant. Number of spikelets per spike Number of spikelets per spike had a positive highly significant correlation with the number of grains per ear (0.7438), grain yield per plant (0.5823), 1000 grain weight (0.5213), canopy temperature (0.4622) and biological yield (0.3741). Association of a number of spikelets per spike with other traits studied were very low in magnitude and non-significant. yield. Association of biological yield with other traits studied were very low in magnitude and non-significant. Harvest index Harvest index had positive highly significant with 1000 grain weight (0.3624), grain yield per plant (0.3002), days to 50% heading (0.2924), and positive significant with ear length (0.2309), ear weight (0.2193), and negative highly significant with biological yield (-0.6085) and negative significant with number of ears per plant (-0.2420), number of effective tillers per plant (-0.2399). Association of harvest index with other traits studied were very low in magnitude and nonsignificant. Chlorophyll content Number of grains per ear Number of grains per ear had a positive highly significant correlation with grain yield per plant (0.7985), 1000 grain weight (0.6893), biological yield (0.4821) and canopy temperature (0.3230). Association of a number of grains per ear with other traits studied were very low in magnitude and non-significant. Chlorophyll content had positive highly significant with days to 50% heading (0.2959). Association of chlorophyll content with other traits studied was very low in magnitude and non-significant. Canopy temperature Grain yield per plant (0.8323), Harvest index (0.3624) and biological yield (0.3608) had positive highly significant correlation with 1000 grain weight. Association of 1000- grain weight with other traits studied were very low in magnitude and non-significant. Canopy temperature had positive highly significant with a number of spikelets per spike (0.4622), ear length (0.3406), peduncle length (ear length), number of grains per ear (0.3230), ear weight (0.3063) and positive significant with plant height (0.2258). Association of canopy temperature with other traits studied was very low in magnitude and non-significant. Biological yield Relative water content Grain yield per plant (0.5526) had a positive highly significant correlation with biological yield and had negative highly significant with harvest index (-0.6085) and RWC (-0.3583) had negative highly significant with biological Relative water content had a positive highly significant correlation with biological yield (0.3588) and negative highly significant with days to maturity (-0.2363) and negative significant with grain yield per plant (- 1000 grain weight 3254 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 0.2141). Associations of RWC with other traits studied were very low in magnitude and non-significant. Path coefficient analysis Path coefficients are standardized partial regression coefficients. It partitions the observed correlation between dependent and independent variable in direct and indirect effects in such a manner that observed a correlation between dependent and independent trait is equal to the sum of direct and all possible indirect effects. Path coefficient analysis, which measures the direct and indirect effect of one variable through another on the end product, was carried out using genotypic as well as phenotypic correlation considering grain yield per plant as a dependent variable. The observed genotypic and phenotypic correlation coefficient on grain and its components were partitioned into direct and indirect effects and have been presented in table 4 and 5. Direct effects Biological yield revealed highest direct positive effect (0.9249) on grain yield followed by number of ears per plant (0.8992), harvest index (0.8695), ear length (0.3532), 1000 grain yield (0.2045), days to maturity (0.1848), chlorophyll content (0.0738), peduncle length (0.0689), canopy temperature (0.0033). However, number of effective tillers per plant (-0.8378), ear weight (-0.3400), days to 50% heading (-0.2169), plant height (0.0816), number of grains per ear (-0.0731), RWC (-0.0547) and number of spikelets per spike (-0.0229) had direct negative effect on grain yield. Indirect effect Days to 50% heading The association of days to 50% flowering with grain yield per plant was positive and small (0.0973) and it exerted positive indirect effect via RWC (0.0381), canopy temperature (0.0259) on grain yield per plant. Days to 50% flowering showed negative indirect effect via days to maturity (-0.1599), chlorophyll content (-0.0669). Other indirect effects of this trait via other characters were relatively low and negligible. Days to maturity Days to maturity exhibited a moderate positive direct effect on grain yield per plant (0.4882). The positive indirect effect exerted on grain yield by other characters via days to 50% heading (0.1362), number of grains of the ear (0.855), 1000 grain weight (0.0671), biological yield (0.0609) and negative indirect effect exerted on RWC (-0.0452), canopy temperature (-0.0051). Other indirect effects of this trait via other characters were relatively low and negligible Table.1 The details of 30 wheat genotypes Sl.no. Lines Sl.no. Lines Sl.no. Lines 1 2 3 4 5 6 7 8 9 10 PYT-2 PYT-6 PYT-16 PYT-21 PYT-22 PYT-23 PYT-24 PYT-25 PYT-27 PYT-40 11 12 13 14 15 16 17 18 19 20 PYT-46 PYT-47 PYT-49 PYT-51 PYT-57 PYT-58 PYT-60 PYT-61 PYT-66 PYT-68 21 22 23 24 25 26 27 28 29 30 PYT-69 PYT-89 PYT-97 PYT-101 PYT-104 PYT-109 PYT-115 PYT-118 PYT-120 PYT-122 3255 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Table.2 Phenotypic correlation coefficient analysis for yield and its component traits SL. N0 Characters DFF DM PH PL EL EW NETPP NEPP NSPS NGPE TGW BY HI CC CT RWC GYPP 1 DFF 1.000 0.729** 0.082 0.004 -0.005 0.051 0.009 0.002 0.057 0.050 0.080 -0.107 0.292** 0.295** -0.127 -0.169 0.089 2 DM 1.000 0.017 0.160 0.206 0.242* 0.101 0.105 0.416** 0.446** 0.312** 0.351** 0.078 0.082 -0.032 -0.236* 0.470** 3 PH 1.000 0.797** 0.666** 0.689** -0.139 -0.165 0.296** 0.027 0.064 0.081 0.097 0.198 0.225* 0.025 0.103 4 PL 1.000 0.858** 0.861** -0.183 -0.198 0.591** 0.337** 0.145 0.230* 0.085 -0.021 0.337** 0.043 0.292** 5 EL 1.000 0.965** -0.072 -0.084 0.651** 0.456** 0.178 0.105 0.230* -0.049 0.340** 0.126 0.324** 6 EW 1.000 -0.081 -0.090 0.629** 0.414** 0.193 0.131 0.219* 0.004 0.306** 0.118 0.331** 7 NETPP 1.000 0.995** 0.060 0.134 -0.012 0.257* -0.239* -0.115 -0.101 -0.161 0.092 8 NEPP 1.000 0.060 0.143 -0.004 0.261* -0.242* -0.134 -0.099 -0.157 0.098 9 NSPS 1.000 0.743** 0.521** 0.374** 0.125 -0.152 0.462** -0.115 0.582** 10 NGPE 1.000 0.689** 0.482** 0.193 -0.119 0.323** -0.191 0.798** 11 TGW 1.000 0.360** 0.362** -0.097 0.165 -0.062 0.832** 12 BY 1.000 -0.608** -0.046 0.107 -0.358** 0.552** 13 HI 1.000 0.109 -0.034 0.194 0.300** 14 CC 1.000 -0.135 0.075 0.002 15 CT 1.000 0.059 0.100 16 RWC 1.000 -0.214* 17 GYPP 1.000 DFF-Days to 50% flowering, DM-Days to maturity, PH-Plant height, PL-Peduncle length, EL- Ear length, EW- Ear weight, NETP-Number of effective tillers per plant, NEPP-Number of ears per plant, NSPS-Number of spikelets per spike, NGPE-Number of grains per ear, TGW-Thousand grain weight, BYPPBiological yield per plant, HI-Harvest index, GYPP-Grain yield per plant, CC-Chlorophyll content, CT-Canopy temperature, RWC-Relative water content. 3256 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Table.3 Genotypic path coefficient analysis for yield and its component traits x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x12 x13 x14 x15 x16 x17 X11 x1 -0.2169 -0.1599 -0.0196 -0.0015 -0.0007 -0.0123 -0.0009 0.0002 -0.0130 -0.0113 -0.0187 0.0239 -0.0660 -0.0669 0.0259 0.0381 0.0973 x2 0.1362 0.1848 0.0056 0.0305 0.0413 0.0474 0.0187 0.0204 0.0795 0.0855 0.0609 0.0671 0.0147 0.0158 -0.0051 -0.0452 0.4882 x3 -0.0074 -0.0025 -0.0816 -0.0659 -0.0561 -0.0583 0.0117 0.0140 -0.0248 -0.0022 -0.0052 -0.0067 -0.0080 -0.0164 -0.0187 -0.0021 0.1053 x4 0.0005 0.0114 0.0556 0.0689 0.0604 0.0610 -0.0128 -0.0137 0.0411 0.0233 0.0099 0.0159 0.0059 -0.0015 0.0237 0.0030 0.2934 x5 0.0012 0.0789 0.2428 0.3099 0.3532 0.3484 -0.0247 -0.0293 0.2341 0.1636 0.0652 0.0373 0.0841 -0.0180 0.1241 0.0459 0.3306 x6 -0.0192 -0.0872 -0.2428 -0.3011 -0.3354 -0.3400 0.0256 0.0308 -0.2192 -0.1439 -0.0701 -0.0454 -0.0766 -0.0004 -0.1052 -0.0413 0.3380 x7 -0.0036 -0.0849 0.1196 0.1558 0.0587 0.0630 -0.8378 -0.8379 -0.0519 -0.1129 0.0133 -0.2168 0.2045 0.0969 0.0835 0.1372 0.0917 x8 -0.0007 0.0991 -0.1540 -0.1792 -0.0746 -0.0815 0.8993 0.8992 0.0575 0.1303 -0.0061 0.2376 -0.2213 -0.1216 -0.0885 -0.1432 0.0989 x9 -0.0014 -0.0098 -0.0069 -0.0137 -0.0152 -0.0147 -0.0014 -0.0015 -0.0229 -0.0171 -0.0120 -0.0086 -0.0029 0.0035 -0.0107 0.0027 0.5880 x10 -0.0038 -0.0338 -0.0020 -0.0248 -0.0339 -0.0310 -0.0099 -0.0106 -0.0546 -0.0731 -0.0507 -0.0353 -0.0142 0.0088 -0.0239 0.0140 0.8017 x12 0.0176 0.0674 0.0129 0.0295 0.0378 0.0422 -0.0032 -0.0014 0.1075 0.1416 0.2045 0.0741 0.0745 -0.0200 0.0351 -0.0129 0.8397 x13 -0.1018 0.3358 0.0762 0.2138 0.0977 0.1235 0.2393 0.2444 0.3485 0.4463 0.3351 0.9249 -0.5640 -0.0432 0.1007 -0.3318 0.5543 x14 0.2647 0.0693 0.0854 0.0740 0.2072 0.1958 -0.2122 -0.2140 0.1096 0.1688 0.3166 -0.5303 0.8695 0.0951 -0.0310 0.1698 0.2973 x15 0.0227 0.0063 0.0148 -0.0016 -0.0038 0.0001 -0.0085 -0.0100 -0.0114 -0.0089 -0.0072 -0.0034 0.0081 0.0738 -0.0102 0.0057 0.0013 x16 -0.0004 -0.0001 0.0008 0.0011 0.0012 0.0010 -0.0003 -0.0003 0.0016 0.0011 0.0006 0.0004 -0.0001 -0.0005 0.0033 0.0002 0.0997 x17 0.0096 0.0134 -0.0014 -0.0024 -0.0071 -0.0067 0.0090 0.0087 0.0064 0.0105 0.0035 0.0196 -0.0107 -0.0042 -0.0033 -0.0547 -0.2149 Residual effect (r) = 0.024 Bold diagonal values are direct effects of each independent trait. Off diagonal values are indirect effects of each dependent trait via independent traits. X1-Days to 50% heading, X2-Days to maturity, X3-Plant height, X4-Peduncle length, X5-Ear length, X6-Ear weight, X7-Number of effective tillers per pant, X8-Number of ears per plant, X9-Number of spikelets per spike, X10-Number of grain per ear, X11-Grain yield, X12-Thousand grain weight, X13-Biological yield, X14-Harvest index, X15-Chlorophyll content, X16- Canopy temperature, X17- Relative water content 3257 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Table.4 Phenotypic path coefficient analysis for yield and its traits x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x12 x13 x14 x15 x16 x17 X11 x1 -0.2123 -0.1550 -0.0176 -0.0010 0.0001 -0.0108 -0.0020 -0.0004 -0.0121 -0.0106 -0.0171 0.0227 -0.0621 -0.0628 0.0270 0.0359 0.0893 x2 0.1244 0.1704 0.0030 0.0273 0.0351 0.0414 0.0172 0.0180 0.0709 0.0761 0.0532 0.0599 0.0133 0.0140 -0.0055 -0.0403 0.4706 x3 -0.0060 -0.0013 -0.0730 -0.0582 -0.0486 -0.0503 0.0102 0.0121 -0.0217 -0.0020 -0.0047 -0.0059 -0.0071 -0.0145 -0.0165 -0.0018 0.1039 x4 0.0001 0.0042 0.0209 0.0263 0.0226 0.0226 -0.0048 -0.0052 0.0155 0.0089 0.0038 0.0061 0.0023 -0.0006 0.0089 0.0012 0.2926 x5 0.0000 0.0126 0.0409 0.0526 0.0613 0.0592 -0.0045 -0.0052 0.0400 0.0280 0.0109 0.0064 0.0142 -0.0030 0.0209 0.0078 0.3240 x6 -0.0034 -0.0163 -0.0462 -0.0578 -0.0647 -0.0670 0.0054 0.0061 -0.0422 -0.0278 -0.0130 -0.0088 -0.0147 0.0000 -0.0205 -0.0080 0.3318 x7 0.0012 0.0130 -0.0179 -0.0235 -0.0093 -0.0104 0.1281 0.1275 0.0078 0.0172 -0.0016 0.0330 -0.0307 -0.0148 -0.0130 -0.0207 0.0927 x8 -0.0002 -0.0088 0.0139 0.0166 0.0071 0.0076 -0.0835 -0.0839 -0.0051 -0.0121 0.0004 -0.0220 0.0203 0.0112 0.0083 0.0132 0.0981 x9 -0.0007 -0.0052 -0.0037 -0.0074 -0.0081 -0.0079 -0.0008 -0.0008 -0.0125 -0.0093 -0.0065 -0.0047 -0.0016 0.0019 -0.0058 0.0014 0.5823 x10 -0.0004 -0.0040 -0.0002 -0.0030 -0.0041 -0.0037 -0.0012 -0.0013 -0.0066 -0.0089 -0.0061 -0.0043 -0.0017 0.0011 -0.0029 0.0017 0.7985 x12 0.0111 0.0430 0.0089 0.0200 0.0246 0.0267 -0.0017 -0.0006 0.0719 0.0951 0.1379 0.0498 0.0500 -0.0135 0.0229 -0.0086 0.8323 x13 -0.1029 0.3375 0.0781 0.2214 0.1010 0.1264 0.2473 0.2516 0.3594 0.4632 0.3467 0.9607 -0.5846 -0.0449 0.1035 -0.3442 0.5526 x14 0.2647 0.0708 0.0884 0.0777 0.2091 0.1985 -0.2172 -0.2191 0.1136 0.1755 0.3281 -0.5509 0.9053 0.0990 -0.0308 0.1760 0.3002 x15 0.0099 0.0028 0.0067 -0.0007 -0.0016 0.0000 -0.0039 -0.0045 -0.0051 -0.0040 -0.0033 -0.0016 0.0037 0.0335 -0.0045 0.0025 0.0029 x16 -0.0014 -0.0003 0.0024 0.0036 0.0036 0.0033 -0.0011 -0.0011 0.0049 0.0034 0.0018 0.0011 -0.0004 -0.0014 0.0106 0.0006 0.1007 x17 0.0052 0.0073 -0.0008 -0.0014 -0.0039 -0.0037 0.0050 0.0048 0.0036 0.0059 0.0019 0.0110 -0.0060 -0.0023 -0.0018 -0.0308 -0.2141 Residual effect (r) = 0.107 Bold diagonal values are direct effects of each independent trait. Off diagonal values are indirect effects of each dependent trait via independent traits. X1-Days to 50% heading, X2-Days to maturity, X3-Plant height, X4-Peduncle length, X5-Ear length, X6-Ear weight, X7-Number of effective tillers per pant, X8-Number of ears per plant, X9-Number of spikelets per spike, X10-Number of grain per ear, X11-Grain yield, X12-Thousand grain weight, X13-Biological yield, X14-Harvest index, X15-Chlorophyll content, X16- Canopy temperature, X17- Relative water content 3258 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Table.5 Genotypic correlation coefficient analysis for yield and its contributing traits Sl. Characters DFF DM PH PL EL EW NETPP NEPP NSPS NGPE TGW BY HI CC CT RWC GYPP 1 DFF 1.000 0.737 0.090 0.007 0.003 0.056 0.004 -0.003 0.060 0.051 0.086 -0.110 0.304 0.308 -0.119 -0.175 0.097 2 DM 1.000 0.030 0.165 0.223 0.256 0.101 0.110 0.430 0.462 0.329 0.363 0.079 0.085 -0.027 -0.244 0.488 3 PH 1.000 0.807 0.687 0.714 -0.142 -0.171 0.303 0.027 0.063 0.082 0.098 0.201 0.229 0.025 0.105 4 PL 1.000 0.877 0.885 -0.185 -0.199 0.596 0.338 0.144 0.231 0.085 -0.022 0.343 0.044 0.293 5 EL 1.000 0.986 -0.070 -0.083 0.662 0.463 0.184 0.105 0.238 -0.050 0.351 0.129 0.330 1.000 -0.075 -0.090 0.644 0.423 0.206 0.133 0.225 0.001 0.309 0.121 0.338 1.000 1.000 0.061 0.134 -0.015 0.258 -0.244 -0.115 -0.099 -0.163 0.091 1.000 0.064 0.145 -0.006 0.264 -0.246 -0.135 -0.098 -0.159 0.098 1.000 0.746 0.525 0.376 0.126 -0.154 0.467 -0.116 0.588 1.000 0.692 0.482 0.194 -0.120 0.326 -0.191 0.801 1.000 0.362 0.364 -0.097 0.171 -0.063 0.839 1.000 -0.609 -0.046 0.108 -0.358 0.554 1.000 0.109 -0.035 0.195 0.297 1.000 -0.138 0.076 0.001 1.000 0.060 0.099 1.000 -0.214 N0. 6 EW 7 NETPP 8 NEPP 9 NSPS 10 NGPE 11 TGW 12 BY 13 HI 14 CC 15 CT 16 RWC 17 GYPP 1.000 DFF-Days to 50% flowering, DM-Days to maturity, PH-Plant height, PL-Peduncle length, EL- Ear length, EW- Ear weight, NETP-Number of effective tillers per plant, NEPP-Number of ears per plant, NSPS-Number of spikelets per spike, NGPE-Number of grains per ear, TGW-Thousand grain weight, BYPPBiological yield per plant, HI-Harvest index, GYPP-Grain yield per plant, CC-Chlorophyll content, CT-Canopy temperature, RWC-Relative water content. 3259 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 3251-3263 Plant height Plant height exhibited a moderate positive effect on grain yield per plant (0.1053).The positive indirect effect exerted on grain yield by other characters via numbers of ears per plant (0.0140), a number of effective tillers per plant (0.0117) and negative indirect effect exerted on peduncle length (-0.0659), ear weight (-0.0583), ear length (-0.0561). Other indirect effects of this trait via other characters were relatively low and negligible Peduncle length The association of peduncle length with grain yield per plant was positive and small (0.2934) and it exerted positive indirect effect via ear weight (0.0610), ear length (0.0604) and negative indirect effect via number of ears per plant (-0.0137), number of effective tillers per plant (-0.0128). Other indirect effects of this trait via other characters were relatively low and negligible. Ear length Ear length exhibited a moderate positive effect on grain yield per plant (0.3306). The positive indirect effect exerted on grain yield by other characters via ear weight (0.3484), peduncle length (0.3099), plant height (0.2428) and negative indirect effect via numbers of ears per plant (-0.0293), a number of effective tillers per plant (-0.0247). Other indirect effects of this trait via other characters were relatively low and negligible. Ear weight The indirect effect of ear weight on grain yield per plant was positive (0.3380) and it exerted positive indirect effect via number of ears per plant (0.0308), number of effective tillers per plant (0.0256) and negative indirect effect via ear length (-0.3354), plant height (- 0.2428). Other indirect effects of this trait via other characters were relatively low and negligible. Number of effective tillers per plant The indirect effect of Number of effective tillers per plant on grain yield per plant was positive (0.0917) and it exerted positive indirect effect via peduncle length (0.1558), harvest index (0.2045), RWC (0.1372) and negative indirect effect via number of ears per plant (-0.8379), number of grains per ear (0.1129). Other indirect effects of this trait via other characters were relatively low and negligible. Number of ears per plant The indirect effect of Number of ears per plant on grain yield per plant was positive (0.0989) and it exerted positive indirect effect via number of effective tillers per plant (0.8993), biological yield (0.2376), number of grains per ear (0.1303) and negative indirect effect via harvest index (-0.2213), peduncle length (-0.1792), plant height (-0.1540). Other indirect effects of this trait via other characters were relatively low and negligible. Number of spikelets per spike The indirect effect of Number of effective tillers per plant on grain yield per plant was positive (0.5880) and it exerted positive indirect effect via chlorophyll content (0.0035), RWC (0.0027) and negative indirect effect via number of grains per ear (-0.0171), ear length (-0.0152). Other indirect effects of this trait via other characters were relatively low and negligible. Number of grains per ear The indirect effect of Number of effective tillers per plant on grain yield per plant was 3260