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ThesisItem Open Access Estimation of Optimum Plot Size for Field Experiment on Green Gram (Phaseolus rediatus L.)(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 2004-05) Patel, Jayanatilal Balubhai; Awadaria, J. D.Estimation of optimum plot • size for field experiment on Co 4 variety of green gram was conducted during the year 2002 at the Pulse Research Station, Agricultural University, Navsari. The green gram yield data of 1200 plots (basic units; the size of each basic unit was I.OOm x 0.90 m i.e. l.OOm length x 2 rows) were recorded and analyzed to work out optimum size and shape of the plot using three different approaches viz. Maximum curvature method, Fairfield Smith's variance method and Spatial correlation method. The size and shape of the block was determined and relative efficiency of different experimental designs and number of replications and relative land use efficiency were also compared. The results revealed the followings. The variability as judged by coefficient of variation (C.V.) per unit area decreased with the increase in plot size. When this relationship expressed in equation form transforming variable plot • SIze (x) to In scale. the predictability of coefficient of variation was high (R:! = 0.90).ThesisItem Open Access D2-Analysis in Grain Sorghum (Sorghum bicolor (L.) Moench)(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 1986-06) Parikh, Rajeshkumar Kantilal; Parikh, R.K.ThesisItem Open Access Effect of Morpho-Physiological variables and Weather Parameters on Growth of Sapota [Manikara achras (mill) Fosberg] cv. kalipatti Under South Gujarat Conditions a Statistical Approach(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 2011-05) Raundal, Rajeshwari M.; Awadaria, J. D.The present study was carried out to know the impact of morpho-physiological variables and weather parameters on various growth stages of Sapota cv. Kalipatti , at Regiunal Horticultural Research Station, ASPEE College of Horticulture and Forestry. Navsari Agricultural University, Navsari during 20 I O. Navsari is considered as a representative orchard of South Gujarat condition. Therefore the 30 Sapota trees (15 years young), which are selected randomly for the purpose . Six growth stages with ten morpho - phys iological variables were s tudied with the effect of seven weather parameters. For studying individual and interaction effect among growth stages, morpho-physiological variables and weather parameters, analyses like correlation, regression analysis and descriptive statistics were carried out. Flowering and fruiting behaviour of Sapota were also studied for two seasons of flowering i.e . summer and winter.The relation in terms of correlation coefficient for various growth stages and all the morpho·physiological variahles were found to he positive and significant among them hut not found with number of matured fruit hut in that also numher of flowers observed significantly correlated. The correlation coefficient for growth stages of Sapota with weather parameters were found to he significant the number of bud were correlated with weather parameters where pea size fruit stage were mostly correlated with weather parameters except minimum temperature and wind velocity this also followed hy number of marble size fruit with weather parameters correlated significantly in that except minimum temperature, rainfall and sunshine hours. Morning and evening humidity showed positive and significant correlation with pea size and marble size fruit stage, followed by rainy days showed positive and significant correlation with pea size and marble size fruit stage, while rainfall showed positive and significant correlation with pea size fruit stage of Sapota. East-West canopy spread, North-South canopy spread, and tree girth had positive significant correlation with morning humidity, while number of fruits had positive and significant correlation with morning and evening humidity. Rainfall had positive and significant correlation with tree girth and number of fruits, while rainy days showed positive correlation with tree girth, number of leaves and number of fruits.The prediction models were derived with the help of regression analysis at various growth stages of Sapota with morpho-physiological variables. At the marble size fruit stage of Sapota, to estimate the numbt;r of marble size fruits per tree the below given model with R2 value 0.9764 provides reliable and greater efficiency for forecast and prediction of marble size fruits - Y = 57.87+ 1.7041'1-0.2931'2-0.07381'3-0.02551'4 -0.10281'5+ 1.972 1'6-0.448 1'7- 0.370P 8 +O.OOIP" " Where, Y = Number of marble size fruit per tree PI = Tree height (m) I' 6 = Tree girth (cm) I' 2= East- West spread (cm) I' 7 = Shoot length (cm) I' 3 = North - South Spread (cm) I' 8 = Number of flowers I' 4 = Leaf Area (cm 2 ) I' 9 = Number of fruits I' 5 = Leafnumbers • Growth characters of Sapota were measured in summer season. Their averages were tree height 7.3 (m), trunk girth 56 (cm), E-W and N-S canopy spread 457 and 514 (cm) respectively and number of fruits/tree 514, fruit yield 50 kg/tree with mean fruit weight 99 (g). The average length and girth were 5.3 and 6.1 (cm) respectively. The fruit in summer season observed were long in shape. Growth characters of Sapota were measured in winter with average tree height 8 (m), trunk girth 63(cm), E-W and N-S canopy spread measured 485 and 522 (cm) respectively and number of fruits/tree recorded were 498, fruit yield 46 kg/tree with mean fruit weight 93 (g). The average length and girth were 5.1nnd 5.2 (em) respectively. The fruit in winter season observed were round in shape. The average increase in growth of Sapota tree recorded • during one year were 72cm in height , 3 em in tree girth and E-W and N-S canopy spread about 28 and 25 em respectively. Sapota flowers took about 269 days for converting the matured fruit in the winter season where as in summer season it took 186 days for maturity of the fruit. This di fference might be due to very long spell of rainy season, the flowers took more days to convert the matured fruit in summer and also low temperature are playing an important role to delay the maturity of the fruit.ThesisItem Open Access Optimum Plot Size For Paddy in the Navsari Zone(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 1983-07) Upadhyay, Satishkumar M.; Raja, K. R.V.ThesisItem Open Access Genetic Variability, Correlation and Path Coefficient Analysis in Grain Sorghum (Sorghum bicolor L. Moench)(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 2013-07) Ashok, Sonawane Nivedita; Parikh, R. K.Variability, correlation and path coefficient analysis were studied in a set of 54 genotypes of sorghum (Sorghum hieolor L. Moench)" grown in a randomized block design with three replications at College Farm, N. M. College of Agriculture, Navsari Agricultural • University, Navsari during the Kharif season of 2012-13. The analysis of variance revealed significant differences among genotypes for all the characters . under investigation indicating the presence of considerable amount of variability in the material. The highest genotypic and phenotypic variances were observed for harvest index (%) followed by grain yield per plant (g) and number of primaries per panicle. Moderate genotypic and high phenotypic variances were observed for dry fodder yield (g). High heritability estimates were observed for characters number of primaries per panicle was recorded highest heritability estimated •• followed by days to maturity, plant height (cm), days to 50% flowering, number of grains per panicle , girth of panicle (cm), harvest index (%). The higher amount of genetic advance was observed for number of primaries per panicle followed by grain yield per plant (g), harvest index (%), number of grains per panicle, plant height (cm), dry fodder yield (g) . The highest genetic advance with high heritability was observed in the present investigation for 5 characters viz ., plant height (cm), number of primaries per panicle , grain yield per plant (g), number of grains per panicle, harvest index (%) . Thus, phenotypic selection would be effective for the genetic improvement in these traits. Grain yield per plant (g) showed significant and positive correlation with number of grains per panicle, harvest index (%), girth of panicle (cm) and panicle length (cm). The grain yield per plant (g) had negative correlation with days to maturity and plant height (cm). Path coefficient analysis indicated that the highest positive direct effect of number of grains per panicle on gra in yield per plant (g) followed by 100 grain weight (g) and harvest index (%) . Negative direct effect on grain yield per plant (g) wa s found with plant height (cm), days to maturity, number of primaries per panicle and days to 50 per cent flowering. Based on these finding , it can be suggested that for improving grain yield more emphasis should be given to panicle length (em), girth of panicle (em), number of grains per panicle and harvest index (%).ThesisItem Open Access Effect of Irrigation Levels on Plot Border in Summer Groundnut (Arachis Hyoogaes Linn) Under Havy Black Soils(Agricultural Statistics Department, N. M. College of Agriculture Gujarat Agricultural University, 1986-06) Awadaria, J. D.; Khatri, T. J.ThesisItem Open Access Estimation of genetic variability in F4 progenies of green gram (Vigna radiata (L.) R. Wilczek) for yield and component trait(DEPARTMENT OF AGRICULTURAL STATISTICS N. M. COLLEGE OF AGRICULTURE NAVSARI AGRICULTURAL UNIVERSITY NAVSARI, 2017) Keerthiga, S.; Pandya, H. R.As variability is pre-requisite for any breeding programme, an effort was made to create and assess the variability through hybridization using parameters like PCV, GCV, heritability, genetic advance and to figure out the inter-relationships among the yield components for seed yield per plant with correlation and path analysis in mung bean. The experiment comprised of three parents Meha, GJM-1006 and GJM-1008, F4 progenies of two crosses viz., Meha x GJM-1006 and Meha x GJM-1008 evaluated in replicated trial in summer, 2016. Observations on quantitative characters viz., days to 50% flowering, days to maturity, plant height, primary branches per plant, pods per plant, seeds per pod, 100 seed weight, seed yield per plant, clusters per plant and harvest index were recorded from parents and their F4 progenies. Considering two F4 population, highest mean value was depicted by Meha x GJM-1006 for days to 50% flowering, days to maturity, plant height, pods per plant, seed yield per plant, clusters per plant, harvest index and seeds per pod. Meha x GJM-1008 showed highest mean for primary branches per plant and 100 seed weight among all the F4 populations studied. Considerable variability was observed for most of the characters in different F4 populations of two crosses under study. Analysis of variance indicated that the F4 population of Meha x GJM-1006 had highest variance for days to maturity, pods per plant and seed yield per plant. The F4 populations of Meha x GJM-1008 depicted highest variance for days to 50% flowering, plant height, primary branches per plant, seeds per plant, clusters per plant, harvest index and 100 seed weight. The higher variances for most of the characters under study among different progenies of two F4 populations which suggested presence of sufficient amount of variability generated. This segregating population may be further advanced and explored for improvement of these traits. Considering all F4 progenies under study, the phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values were low for days to 50 % flowering, days to maturity, seeds per pod and 100 seed weight. Low to moderate PCV and GCV were observed in plant height and primary branches per plant. Low to moderate GCV and PCV values indicated the influence of the environment and limited scope for improvement by simple phenotypic selection. The GCV and PCV estimates were moderate to high for clusters per plant and harvest index. Pods per plant and seed yield per plant shows higher PCV and GCV in both the segregating population. The phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) exhibited wide variation for most of the characters in the two segregating populations. The progenies of the two crosses had higher GCV and PCV for pods per plant, seed yield per plant and cluster per plant. Meha x GJM-1006 exhibited the higher values of GCV and PCV for pods per plant, seed yield per plant and clusters per plant indicating that there is greater scope for improvement by applying selection on these characters in desirable direction and also greater diversity among the progenies for these characters. The result revealed that genotypic coefficient of variation was close to that of phenotypic variation for all the characters in F4 populations studied indicating predominant genetic contribution and less environmental influence. High heritability values of more than 65 per cent have been observed for plant height in the cross Meha x GJM-1006 and days to 50% flowering in Meha x GJM 1008. High heritability for some of the traits like days to 50% flowering, days to maturity, pods per plant and harvest index indicated that the traits are generally governed by additive gene effects and improvement for these traits could be made by simple phenotypic selection. Comparison of genetic advance as per cent mean value of the two populations revealed higher genetic advance as per cent mean value for pods per plant, and seed yield per plant and low genetic advance as per cent mean value for days to 50% flowering, days to maturity, primary branches per plant, seeds per pod and 100 seed weight. The genetic advance was moderate to high for the traits plant height, cluster per plant and harvest index, in almost both the populations. The moderate to high genetic advance coupled with moderate to high heritability estimates for these traits suggested the importance of additive genetic variance for these traits. The heritability estimates of pods per plant, clusters per plant and seed yield per plant were high with high genetic advance as per cent mean compared to other traits, hence, priority should be given to these traits in formulating selection strategies on the basis of these characters to realize better gains by selection. It was observed that generally seed yield per plant was strongly and positively associated with the yield components like days to 50 % flowering, plant height, primary branches per plant, days to maturity, pods per plant, 100 seed weight, seeds per plant and clusters per plant in the two segregating populations except days to 50 % flowering and days to maturity in the cross Meha x GJM-1006. While, harvest index depicted positive and non-significant association with seed yield in F4 populations of Meha x GJM-1006 as well as Meha x GJM-1008. Path analysis involving two segregating populations revealed that seed yield was primarily influenced by plant height and 100 seed weight which had higher positive direct effects on seed yield per plant in Meha x GJM-1008. While, in the cross Meha x GJM-1006, seed yield per plant was primarily influenced by plant height, seeds per pod and primary branches per plant which had positive direct effect on seed yield per plant. Plant height exhibited maximum positive direct effect and significant correlation with seed yield per plant in desirable direction. Hence, it would be rewarding to lay emphasis on plant height, while developing selection strategies in green gram. Other traits like days to 50% flowering, 100 seed weight and harvest index had positive direct effects on yield in both the crosses. Primary branches per plant, clusters per plant and seeds per pod also exhibited positive direct effect in the cross Meha x GJM-1006, while they showed negative direct effect in Meha x GJM-1008. Days to maturity depicted negative direct effect in two crosses viz., Meha x GJM-1006 and Meha x GJM-1008. Clusters per plant had negative direct effect in the cross Meha x GJM-1008 and positive direct effect in the cross Meha x GJM-1006. In the present investigation, segregating F4 populations three genotypes, Meha used as female parent and GJM-1006, GJM-1008 used as male parents resulted in increased variability, heritability and GAM values. The F4 populations of crosses viz., Meha x GJM-1006 and Meha x GJM-1008 needs to be handled under different selection schemes for improving productivity as they depicted high heritability along with high genetic advance as per cent mean for most of the traits. There is need to study the comparative performance of the progenies by carrying out inter-mating within and between populations and some sort of biparental mating involving the populations viz., Meha x GJM-1006 and Meha x GJM-1008. Simultaneous selection may be applied for yield associated attributes like clusters per plant, pods per plant and harvest index as revealed by correlation and path co-efficient analysis.ThesisItem Open Access PRE-HARVEST CROP MODELLING FOR KHARIF RICE USING WEATHER PARAMETERS IN SOUTH GUJARAT(Agricultural Statistics Dept., NMCA, NAU, Navsari, 2016-06) Banakara, Kanthesh B.; Bhatt, B. K.The importance of timely and reliable forecast of yield of principle crops need not be over-emphasized for developing countries like India where the country economy mainly based on agriculture. Weather is a major factor affecting crop production in agriculture system. The large variation in yield from year to year and place to place is dominated by the weather parameters. Forecast depends mainly on crop and weather parameters relationships which is important for policy decision. To estimate the effect of weather parameters and technological advances, thirty four years of yield and weather parameters data from 1975 to 2012 were collected. The weekly average of weather parameters viz. maximum temperature (X1), minimum temperature (X2), relative humidity (X3), wind speed (X4) and rain fall (X5) from 22nd to 37th standard meteorological week of the representative year were considered in the investigation. The week wise approach was carried out by developing indices using correlation coefficient. Time trend also included as independent parameter in all the approaches. To provide early forecast, from 22nd to 37th SMW were considered. The investigation was undertaken to explore the possibility of forecasting of yield of rice using multiple linear regression model and discriminant function analysis. The result showed positive as well as negative significant association between yield and some of the weekly weather parameters for both Surat and Valsad districts of South Gujarat. The ranges of correlation coefficient not exceeded more than 68 per cent. This suggest that simple regression using single weather parameters in not adequate to forecast the rice yield. It is necessary to utilize all weather parameters jointly through constructing unweighted and weighted indices. Yield forecasting model-A6 was found better with R2 value 80.2 per cent and RMSE value 378.254 and per cent forecast error ranging from 9.27 to 20.25 in 37 SMW (five weeks before harvest of crop). Similar results were found in yield forecasting model- B6 with marginal difference in RMSE i.e.384.115 and per cent forecast error range i.e. 9.83 to 20.44 with same adjusted R2 value and same pre-harvest forecast week for Surat district. Yield forecasting model-A5 was found better with adjusted R2 value 70.7 per cent and RMSE value 316.082 and per cent forecast error ranging from 10.285 to 13.528 in 36 SMW (six weeks before harvest of crop). Yield forecasting model-B3 was found better with R2 value 57.0 per cent and RMSE value 213.289 and per cent forecast error ranging from 3.65 to 11.26 in 36 SMW (five weeks before harvest of crop) for Valsad district. In discriminant function analysis eight models were used for forecasting rice yield, out of eight forecast models, model-3(E6) was found better as compared to other models with the lower RMSE i.e. 340.661 and per cent forecast error ranging from 2.60 to 19.21 having adjusted R2 value 69.7 per cent in 37 SMW (four weeks before harvest of crop) for Surat district. Similarly for Valsad district same eight models were utilized for analysis. Out of eight forecast models, model-3(E2) was found better as compared to other models with the lower RMSE i.e. 184.909 and per cent forecast error ranging from 4.32 to 9.27 having adjusted R2 value 66.2 per cent in 33 SMW (nine weeks before harvest of crop). Comparison between multiple linear regression model and discriminant function analysis for rice yield forecasting, model-E6 of discriminant function analysis was found superior as compared to MLR model A6 in Surat district whereas yield forecasting model E2 of discriminant function analysis was found superior as compared to MLR model-A5 in Valsad district. The best fitted pre-harvest forecasting model for Surat district was 2 1 ˆ 1190.037 32.290 112.177 (adj.R 69.7%)Y T ds = + + The best fitted pre-harvest forecasting model for Valsad district was 2 1 ˆ 1380.864 28.101 109.394 (adj.R 66.2%)Y T ds = + +