Maximum Inter-cluster Distance Research Articles

Estimation of Genetic Divergence in Garden Pea (Pisum sativum L.) Germplasm

Genetic diversity among thirty garden pea genotypes was worked out using Mahalanobis D2 statistics. Based on genetic distance, genotypes were grouped into ten clusters of the ten clusters, cluster I was the largest, having 11 genotypes, followed by cluster IV, cluster VIII, cluster III, cluster V and clusters II, VI, VII, IX and X, with one genotype in each. The average intra-cluster distance was maximum in cluster VIII (487.04) and minimum in cluster V (125.72). The maximum inter-cluster distance was observed between cluster VIII and cluster X (3439.67), indicating the genotypes in these clusters are more diverged and they can be used as parents in the hybridization program to obtain superior segregants. Cluster means for various traits revealed that cluster VIII was found superior for plant height at 60 DAS, number of branches per plant at 60 DAS, and number of pods per plant. Thus, genotypes from this cluster could be used as divergent parents to improve these particular characters. Pod yield per plant contributed the maximum (38.16 %) to the genetic diversity among the characters studied.

Genetic Divergence Study in Groundnut Genotypes (Arachishypogaea L.)

Employing the Mahalanobis D2 statistic, a divergence study was performed on 36 groundnut genotypes and 13 clusters were identified. Indicating that the genotypes of these groups may be more divergent from one another, the maximum inter-cluster distance (D) was found between cluster II and cluster XIII (315.56), followed by cluster III and cluster IX (289.56), cluster III and cluster XII (289.21), and cluster XII and cluster XIII (297.11). The genotypes in the mentioned clusters showed a significant difference in the means for traits that contribute significantly to yield, indicating that the genotypes in these clusters make ideal parents in a hybridization programme to produce transgressive segregants and improve groundnut.

Assessment of Genetic Diversity for Grain Yield in Rice (Oryza sativa L.) Genotypes under Humid South Eastern Plain of Rajasthan, India

Rice (Oryza sativa L.) is the most staple food source and grain for more than half of the world’s population, therefore identify the best suitable genotypes for proper crossing is important to produce high yielding potential varieties with best cooking and biochemical quality characters. Diversity helps the plant breeder in selecting the best parents for breeding programmes. The experimental material were evaluated in Randomized Block Design (RBD) with three replications. The 25 Rice genotypes were divided into 1 to 6 clusters grounded by Mahalanobis’s D2 statistics. Cluster II comprise with the highest number of (8) genotypes from differently originated and cluster I comprise of 7 cultivars exhibit supreme grain yield whereas cluster VI consisted with the least number of (1) genotypes. Maximum inter-cluster distance was recorded between cluster III and VI. Cluster I had the principle mean values for grain yield and Number of productive tillers per plant and Cluster VI had the head mean values for 1000-grain weight. These clusters of cultivars may serve as prospective donors for future hybridization programs to create high yielders if they possess the desired traits.

Genetic analysis and diversity studies in sesame (Sesamum indicum L.)

Genetic variability, path coefficient and diversitywere studied using 56 genotypes ofsesame [Sesamum indicum (L.)] in RBD with three replications at Agricultural Research Station, Mandor, Jodhpur during kharif 2019. Themean squares for all the characters were significant indicating the presence of wide genetic variability. The high magnitudes of PCV and GCV for seed yield and moderate values for primary branches/plant depicted the presenceof high amount of variation. High heritability coupled with high genetic advance for seed yield suggesting that it could be improved through direct selection due to predominant additive variation. High heritability with moderate genetic advance as 5% of mean were observed for plant height and 1000 seed weight indicating the influence of non-additive gene action in the expression ofthese traits. Correlation coefficient analysis showed that seed yield had significant positive association with number of capsules/plant followed by 1000 seed weight and oil content at both genotypic and phenotypic level. Path coefficient analysis revealed that number of capsules/plant possess the highest positive direct effect (0.473) followed by 1000 seed weight (0.432) and plant height (0.313) on seed yield, whichsuggested that during selection more emphasis should be given to these characters to develop a desirable plant type. In the diversity study, the maximum intra-cluster distance was estimated in cluster-VIII (11.77) followed by cluster-VI (10.74), cluster-I (8.94), cluster-II (8.76), cluster-III (7.11) and cluster-IV (5.12) indicating wide genetic variability within the genotypes of these six clusters. The maximum inter-cluster distance was estimated between cluster-III and VIII (69.10) followed by cluster-III and IV (62.33) and cluster-III and VI (62.24), suggesting wide diversity between genotypes of these clusters.

Genetic divergence studies for yield and quality traits in white and brown finger millet (Eleusine coracana (L).)

The present study assessed the nature and magnitude of genetic variability for yield and quality-related traits in 64 finger millet genotypes for 25 parameters during Kharif, 2020-21 at Agricultural College Farm, Bapatla, Andhra Pradesh. In D2 analysis, the maximum inter-cluster distance was observed between cluster Ⅳ, with white-seeded genotypes and cluster Ⅵ with brown-seeded genotypes indicating these clusters may give a high heterotic response and better segregants. The principal component analysis identified the maximum contributing variables i.e., grain yield per plant, harvest index, fingers per earhead, test weight, peduncle length, seed protein content and seed calcium content in the first principal component. PCA scores of 64 genotypes indicated that genotypes IC0477628, IC0476988, IC0477206, VR1034, IC473950 and IC0477272 are diverse for yield and quality traits and hence hybridization between these genotypes is suggested for generating transgressive segregants.

Genetic diversity and screening for bacterial wilt in tomato (Lycopersicon esculentum)

Thirty-four tomato genotypes from different geographical locations were evaluated for genetic diversity and screened for bacterial wilt (BW) caused by Ralstonia solanacearum. Results revealed that plant height, fruits per cluster, fruit weight, fruit diameters, locules per fruit, fruit firmness, yield per plant, and quality parameters exhibited high heritability and genetic advance. Clustering based on D2 analysis, classified genotypes into four clusters. Maximum intra-cluster distance was recorded within cluster I and maximum inter-cluster distance between cluster II and IV followed by cluster I and IV, indicating existence of wide genetic variability. Genotypes in cluster IV (AVTO 1711, AVTO 1717 and AVTO 1718) recorded high fruit weight coupled with high yield. These may be explored as promising donors for developing large sized bacterial wilt resistant tomatoes. The large fruited genotypes in cluster IV can also contribute to the genetic improvement of existing bacterial wilt resistant varieties placed in cluster I. Out of 34 genotypes screened for BW disease, 5 genotypes were classified as resistant and 7 as moderately resistant.

Studies on Genetic Divergence of Parental Lines and Their F1 Progeny in Bottle Gourd [Lagenaria siceraria (Mol.) Standl.

The current experiment was carried out in Randomized Complete Block Design with three replications. In present investigation forty-three genotypes (10 lines + 3 testers + 30 F1’s) of bottle gourd were grouped into seven distinct non over lapping clusters. This suggested that the genotypes had a significant amount of variability. Additionally, it was discovered that the genotypes belonging to the same geographic area were clustered together. Thus, there was no consistent relationship between genetic divergence and geographical distribution. Number of genotypes per cluster ranged from fifteen to one. The cluster II was the largest with fifteen genotypes followed by cluster III and cluster I, cluster VII, cluster VI while, cluster IV had one genotype. The maximum intra cluster distance was recorded in cluster VII followed by cluster V and cluster III. Maximum inter-cluster distance was observed between cluster I and V followed by that between cluster V and VI and cluster III and VI. The higher inter cluster distance indicated greater genetic divergences between the genotypes of those clusters. The inter-cluster distance was least between cluster IV and VI indicated, that the genotypes of these clusters were genetically least diverse and with almost of the same genetic architecture. Percent character contribution towards genetic divergence among the bottle gourd genotypes were maximum for fruit length followed by days to first harvest, fruit circumference, node number to first pistillate flower appearance and number of primary branches plant-1. Therefore, these traits must be included while studying genetic divergence in bottle gourd. The results suggested that crosses between selected lines/F1’s from widely separated clusters are most likely to give desirable recombinants/hybrids.

Genetic Divergence on Chickpea (Cicer arietinum L.) Genotypes Grown under Late Sown Conditions

In the current experiment, 102 chickpea.germplasm showed wide range of variation for various characters were evaluated during Rabi 2017-18 along with BG 372, Udai and Pant G 186 as checks varieties in Augmented Block Design at Agronomy Research Farm of Acharya Narendra Deva University of Agriculture and Technology, Narendra Nagar (Kumarganj), Ayodhya (U.P.). The observations were recorded on 11 quantitative characters viz., days to 50 per cent flowering, days to maturity, primary branches per plant, secondary branches per plant, plant height (cm), pods per plant, seeds per pod, biological yield per plant (g), seed yield per plant (g), harvest index (%) and 100-seed weight (g). A statistical investigation of each character's genetics yielded a number of results. Higher seed yield per plant was generated by genotypes GJG 1416, followed by BG 256, GJG 1416, PhuleG0819. Seed yield per plant had positive and extremely significant associations with secondary branches per plant, pods per plant, seeds per pod, biological yield per plant, harvest index, and 100-seed weight. Primary branches per plant were shown to have positive significant associations with seed output per plant, where as plant height was determined to be non-significant. It showed a poor, non-significant correlation with the number of days until 50% blooming and the number of days till maturity. Biological yield per plant (g) and the Harvest index were found to be significant direct components of seed yield per plant by path analysis. The traits mentioned above that were significant direct and indirect components ought to be taken into account when creating a chickpea selection strategy that would produce high yielding varieties. The 11 clusters formed in divergence analysis contained genotypes of heterogeneous origin there by indicating no parallelism between genetic and geographic diversity. In this context, the maximum inter-cluster distance was recorded between cluster X and XI (12.201) followed by cluster III and XI (11.254), cluster VI and XI (11.125) and cluster VII and XI (10.875). Therefore, crosses between members of cluster separated by high inter-cluster distances are likely to throw desirable segregants.

Genetic Variability, Heritability, Genetic Advance and Divergence Analysis in Wheat (Triticum aestivum L.)

Background: Wheat is a cereal crop that is widely farmed across the world and ranks first in global crop production. Wheat cultivation is the world’s most important food crop.The assessment of genetic divergence existing in the germplasm collections is very important to select genetically divergent parents for hybridization in a transgressive breeding programme for development of high yielding wheat varieties coupled with quality, multiple resistance and wider adaptability. Methods: The experiment on 21genotypes including two checks viz., HD 2967 and PBW 824 was conducted to work out the genetic variability, heritability, genetic advance and divergence analysis for yield and yield contributing traits in wheat (Triticum aestivum L.). The experiment was laid out in randomised block design (RBD) during Rabi, 2021-2022 at Lovely Professional University, Phagwara, Punjab. Result: The analysis of variance revealed mean sum of square due to genotypes were significant for all the characters indicating sufficient genetic variability among the genotypes. The magnitude of PCV and GCV were moderate for grain yield per plant and harvesting index, which suggests greater phenotypic and genotypic variance among the genotypes and responsiveness of the attributes for making further improvement by selection and indicating limited scope for improvement. High heritability coupled with high genetic advance observed for harvest-index thus these characters show additive gene action in their expression. In divergence analysis, maximum intra-cluster distance exhibited by cluster 2 followed by cluster 1among the different genotypes. The maximum inter-cluster distance between cluster 2 and 3 followed by cluster 2 and 7 and the minimum inter cluster distance was recorded between cluster 5 and 6 followed by cluster 1 and 3. It indicated that for crop improvement in wheat diversified genotypes may be selected from cluster 2 and cluster 3 to received maximum transgressive recombinants from segregating generations.

Towards the Development of a Finger Millet (Elesine Coracana L. Gaertn) Breeding Programme in Zambia

Finger millet [Eleusine coracana (L.) Gaertn] is one of the potential cereals that can be used to mitigate climate resilience among the smallholder farmers who are the major growers. It has the capacity to adapt to extreme environmental conditions as well as grow under a wide range of wider agroecology, an advantage to other cereals, which can be capitalized in breeding. However, the breeding of finger millet in Zambia is constrained by the lack of knowledge on the genetic information, compared to other small grains cereal crops. Therefore, a study was conducted to assess the diversity of mutant lines in the sixth generation. A pure line selection from a landrace finger millet variety Mutubila was sourced from the Sorghum and Millet Breeding Program of the Zambia Agriculture Research Institute (ZARI) in 2013. The seed was divided into four lots of 1 kg and subjected to gamma-ray mutagenic treatment at 0 (control), 100, 150 and 200 at the National Institute for Scientific and Industrial Research (NISIR) in Lusaka in 2014. An equal amount of Irradiated seed (First mutation generation) from each dose was planted in Mpulungu during the off-season of 2013 in plots of 50m x 50m spacing 30cm intra row and 30cm inter rows. The second generation showed 99% plant survival with 0, 70% plant survival with 100, 10% plant survival with 150 and 0% plant survival with 200. Therefore, the subsequent segregating generations from 100 were used for selection. The mutant lines were selected from generations that were exposed to different culling rates as generations increased, after repeated selection 40 mutant lines were selected planted with six checks using an Alpha Lattice design with two replications and eight blocks, 48 genotypes were evaluated for agronomic performance. Results revealed that the mutant lines were diverse in the number of productive tillers per plant, main ear length that ranged from 3 to 15 and 4.4cenmetre to 14.5cenmtre respectively, while the number of fingers per gearhead and grain yield ranged from 3 to 17 and 0.58, to 2.5kilogram per hectare respectively. Productive number of tillers, Finger length, strawweight, and number of fingers were strongly and positively correlated to grain yield (R2 > 0.67). There were X clusters, the highest number of sub-clusters was (11) in cluster I. Maximum inter-cluster distance was observed between clusters V and IV, V and VII, V and IX and VII and XI, indicating wider divergence among these clusters. The minimum inter-cluster distance was between II and III, VIII and X, I and VIII. Distant clusters indicated that the genotype present in one cluster differed completely from the one in the other clusters and thus could be used for generating superior genotypes. The study showed that selecting yield components as the mutants is advanced results in divergent lines, which can be recombined to breed high-yielding and disease-tolerant finger millet. We conclude, therefore, that mutation breeding for Finger Millet can be used to generate diversity, and divergent lines can be recombined to develop improved genotypes for commercialisation.

Genetic divergence study in greengram [Vigna radiata (L.) Wilczek

The present investigation was undertaken to obtain information on the nature and extent of genetic diversity among 60 greengram genotypes for yield related traits and quality traits by using Mahalanobis’s D2 statistics.  The genotypes were grouped into eleven clusters. Cluster I was found to be the largest  with 38 genotypes followed by cluster V with 13 genotypes and all the other clusters were found to be solitary, each containing a single genotype. Clusters VIII and XI had the maximum inter-cluster distance, followed by clusters IV and XI. Cluster XI had the highest mean values for yield and other yield attributing traits. Iron content contributed high towards total genetic diversity followed by protein content and test weight. Based on the mean performance and diversity studies, the genotypes COGG 18-17, LGG 460, Daftri vikas and IPM 1603-3 were found to be the best for further yield improvement in greengram. Utilizing the genotypes from the more divergent clusters as parents in breeding programmes will yield relatively good amount of heterosis in F1 and high frequency of transgressive segregants and genetic variability in subsequent generations can be acquired. Keywords: D2 statistic, Cluster analysis, Genetic Divergence, Greengram, Tocher’s method.

Genetic variability and divergence in okra (Abelmoschus esculentus)

An experiment comprising of 10 genotypes of okra {Abelmoschus esculentus (L) Moench} sown in RBD with three replications was conducted during rainy season of 2019 and 2020 at Vegetable Research Farm, BUAT Banda. The genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were highest for days to 50% germination and lowest for first flower, days to 50% flower, days to maturity, fruit length, fruit diameter, number of seeds/fruit, fruit yield/plant, fruit yield/plot and fruit yield (q/ha). The heritability estimates were high for days to 50% germination, average fruit weight, number of fruits/plant, fruit yield/ plant and fruit yield (q/ha) indicating that selection based on phenotypic performance would be more operative. The high heritability coupled with high GAM was observed for days to 50% germination, average fruit weight and number of fruits/plant, indicating that additive gene effect was more important. Based on D2 analysis, 19 genotypes were grouped into six clusters. The cluster I had seven genotypes followed by cluster II and III with six and three genotypes respectively, while and remaining clusters were monogenotypic. The cluster II recorded maximum intra cluster distance, followed by cluster I and clusters III. Maximum inter-cluster distance was observed between cluster III and VI, followed by that between cluster III and IV and between cluster I and III, suggesting that genotypes belonging to cluster III and VI, III and IV and I and III are more divergent than the rest of the clusters. Per cent character contribution towards genetic divergence was maximum for fruit yield (q/ha), followed by average fruit weight, days to 50% germination, number of seeds/fruit and fruit yield/plant showing selection of these characters. Apart from the above findings it can be concluded that, selection and hybridization of genotypes from high divergent clusters III (Kashi Kranti, Hisar Naveen, P-8) and VI (Punjab Suhavani) and cluster I (NDO-10, Azad Bhindi-1, Kashi Vibhuti, Arka Abhay, Kashi Vardan, Arka Anamika, Kashi Pragati) and cluster III (Kashi Kranti, Hisar Naveen, P-8) are expected to yield potential F1s and transgressive for further exploitation.

Estimation of Genetic Divergence and Character Association Studies in Local and Exotic Diversity Panels of Soybean (Glycine max L.) Genotypes

The availability of favorable genetic diversity is a thriving vitality for the success of a breeding program. It provides a firm basis of selecting superior breeding lines for the development of high yielding crop genotypes. In this context, present investigation aimed to generate information on genetic divergence and character association in a diversity panel of 123 local and exotic soybean genotypes. Analysis of variance revealed significant response of the evaluated genotypes based on studied attributes. It depicted the probability of selecting desirable soybean genotypes by focusing on character association studies and genetic diversity analysis. Correlation analysis revealed that seed yield per plant showed high positive correlation with 100-seed weight followed by pods per plant and plant height. Furthermore, path coefficient analysis exposed that pods per plant had maximum direct contribution in seed yield per plant followed by 100-seed weight, days to flowering and SPAD measurement. Genotype named “G-10” showed maximum yield per plant followed by 24607, G-52, 24593, Arisoy, 24566, 17426, A-3127, 24570 and 24567. Genetic diversity analysis grouped the evaluated germplasm into 17 clusters. All clusters showed zero intra-cluster variability; while inter-cluster divergence ranged from 9.00 to 91.11. Cluster V showed maximum inter-cluster distance with cluster XII followed by that of between V and VIII. Moreover, cluster IV with superior genotypes (G-10, 24607, 24593 and 24566), VI (17426 and 24567), XIII (24570) and X (Arisoy and G-52) showed above mean values for most of the studied characters. Overall, the results of hybridization between the superior genotypes of these cluster pairs might be useful for soybean breeding with improving agronomic traits and adaptability.

Multivariate analysis among advanced breeding lines of rice (Oryza sativa L.) Under sub-tropical ecology of Jammu region of Jammu and Kashmir

The present study aimed to determine the nature and extent of genetic divergence for agro-morphological and quality traits amongst advanced breeding lines of rice utilizing multivariate techniques. Based on the inter se D2 values, breeding lines were grouped into six non-overlapping clusters, indicating presence of diversity amongst the lines.  Cluster I and Cluster II were found to be the largest clusters consisting of 14 and 9 genotypes, respectively, while, the remaining four clusters were mono-genotypic. The maximum inter-cluster distance was observed between cluster II and VI, while the maximum intra-cluster distance was recorded for cluster II. Breeding lines present in cluster II were observed to have highest cluster means for traits viz., plant height, total number of tillers per plant, amylose content, grain yield per plant and grain yield per plot indicating its superiority over rest of the clusters. Traits including grain yield per plot, grain yield per plant, days to maturity, 1000-grain weight, total number of tillers per plant and panicle length were observed to be the major contributors to genetic divergence. Principal component analysis extracted six principal components of which first five components viz., PC-I to PC-IV had eigen scores greater than one. This suggested that traits within these axis were of importance. Principal component analysis revealed that the traits viz., number of effective tillers per plant, grain yield per plot, plant height, panicle length and days to 50 per cent flowering contributed maximum towards genetic diversity.  Keywords: Rice, Genetic diversity and PCA analysis

Genetic diversity, correlation and path co-efficient for yield and yield associated traits in rice (Oryza sativa)

The present investigation was conducted to assess the high grain yielding varieties and their related traits for evolving better genotypes for further breeding programme. Twenty-five rice genotypes were collected from different geographical regions of Tamil Nadu to discern the extent of divergence, variability and character association. The analysis of variance exposed the presence of significant differences among all the genotypes for eight characters studied and indicated the occurrence of considerable amount of deviation in the genotypes. In D2 analysis, 25 rice genotypes were grouped into six clusters. The maximum intra-cluster distance was registered in cluster III (31.88). The maximum inter-cluster distance was found between cluster II and cluster IV (144.96). IR 64, PMK 3 and CO 51 were the potential donors and could be used as a parent as they possessed high per se for yield and majority of its attributes. Number of grains/panicle, 1000-grain weight, plant height, days to 50% flowering and grain yield/plant were the major contributors towards the total genetic divergence among the traits studied. The genetic correlation revealed that number of tillers/plant and panicle length showed positive and significant association with respect to number of productive tillers/plant and number of grains/panicle at both genotypic and phenotypic levels. So, it may be inferred that selection and manoeuvring of anyone of the traits viz., number of productive tillers/plant and panicle length were likely to improve grain yield/plant. Path analysis indicated that number of productive tillers/plant, 1000-grain weight and number of grains/panicle exerted maximum positive direct and all identified genotypes with their resulted traits would be obliging to progress or deploy for further breeding programme.

Divergence Study of Rice (Oryza sativa L) Genotypes for Consumer-preferred Quality Traits

Aim: To study the divergence of forty rice genotypes for consumer-preferred eleven quality traits.
 Design, Place and Duration of the Study: The rice seeds were harvested from randomly selected plants grown in alpha lattice design with three replications during Kharif season (start in June and end in October) 2018 at Agricultural research farm, Banaras Hindu University, Varanasi UP, India.
 Methodology: The data were analysed using biometrical tools - Mahalanobis D2 and Principal Component Analysis (PCA). The studied traits include, - grain length, grain breadth, kernel length, length to breadth ratio, kernel breadth, kernel length after cooking, kernel breadth after cooking, elongation ratio, elongation index, amylose content and alkali digestion value.
 Results: Using Mahalanobis D2, all forty genotypes were distributed into six clusters. The maximum inter-cluster distance was recorded between Cluster II to cluster V (5.76), followed by cluster V and cluster III (5.71), and cluster II and cluster VI (5.57) which indicated the existence of high genetic diversity among genotypes in these clusters and, therefore, crosses between the genotypes of these clusters could yield desirable transgressive isolates for desirable quality traits and the importance of the genotypes present in these clusters for exploiting heterosis for the desirable traits of these clusters. The PCA indicates that the five principal components (PC) captured almost 90% of variability present among the 40 rice genotypes.
 Conclusion: The genotypes belonging to Cluster II to cluster V, followed by cluster V and cluster III, and cluster II and cluster VI, can be used for making crosses as they have higher mean values for quality traits and higher inter-cluster distance for greater diversity.

Multivariate Analysis for Elucidating Genetic Diversity of Chickpea (Cicer arietinum L.) Germplasm using Agro-morphological Traits

Background: Chickpea is grown on a large scale in India but the productivity is very low as compared to other chickpea-growing countries. Because, in India, the crop is affected by many biotic and abiotic stresses and also has a narrow genetic base in germplasm lines, which are the prerequisite of any breeding program for developing high-yield varieties. The breeding program’s success depends on genetic variation and efficient selection strategies that make it possible to exploit exist­ing genetic resources. Methods: The agro-morphological characterization of 94 chickpea germplasm accessions including four checks viz., JG 14, JG 16, JAKI 9218 and Radhey was carried out during Rabi 2018-19. The experiment was laid out in augmented design in nine blocks. The analysis of variance was estimated with the help of statistical software SPAD and using the statistical package Windostat version 9.1. Result: The significant variance among the germplasm lines was found for most of the studied traits. Genetic diversity analysis revealed the grouping of genotypes into eight distinct clusters irrespective of breeding centers. The maximum number of 32 genotypes was fallen in cluster II and the minimum in cluster VI which consisted of 8 genotypes, whereas clusters IV and VIII were identified as bi-genotypic clusters. Clusters VII and IV showed maximum inter-cluster distance indicating the maximum genetic diversity among the genotypes of these clusters. Principal component analysis transformed data into three variables (PCs) which contributes 97.78 percent of the total variation. The genotypes identified in this study will be utilized in chickpea improvement programs.

Genetic Divergence Analysis in Rice (Oryza sativa L.) Germplasms under Sodic Soil

Background: Salt affected areas have increased day by day because of excessive use of irrigation water with improper drainage coupled with the poor quality of irrigation water. The assessment of genetic divergence existing in the germplasm collections is very important for success of hybridization programme leading to development of high yielding varieties. Methods: The experiment on 113 genotypes (aromatic and non-aromatic rice) including three checks viz., Sarjoo 52, FL 478 and CSR 10 (salt tolerant ) of rice (Oryza sativa L.) was conducted to work out the genetic divergence. Result: The 113 genotypes were grouped in to eleven different non-overlapping clusters. Cluster II, having 20 genotypes, emerged with highest number of entries. The highest intra-cluster distance was found for cluster X. The maximum inter-cluster distance was recorded between cluster VII and XI. The highest cluster mean for grain yield per plant was observed in cluster III. Presence of substantial genetic diversity among the germplasm lines screened in the present study indicating that this material may serve as good source for selecting the diverse parents for further hybridization program aimed at isolating desirable segregants for grain yield and other important characters.

Study of Genetic Diversity in Greengram (Vigna radiata (L.) Wilczek) Germplasm in Prayagraj Region

The present study consists of 41 Greengram genotypes including one Check variety used to study the nature and magnitude of genetic divergence using Mahalanobsi’s D2 statistics. The data for 13 quantitative characters recorded from the genotypes raised in Randomized Block Design having three replications at Department of Genetics and Plant Breeding, SHUATS, Prayagraj, Uttar Pradesh, India during Kharif-2021. 13 quantitative characters viz., Days to 50% flowering, Days to 50% pod setting, Days to maturity, Number of clusters per plant, Number of primary branches, Plant height (cm), Number of pods per plant, pod length (cm), Biological yield per plant (g), Number of seeds per pod, Harvest index (%), Seed yield per plant(g), Seed index to estimate the variability, heritability, genetic advance, genetic diversity among yield. SML-668 (14.96 g) has the highest Seed yield followed by IPM-205-7 (13.48 g), IPM-410-03913.21 g) showed the higher yield over the SM-20-29 (Check). Maximum (GCV), (PCV), Heritability was recorded for Number of primary branches. High Heritability coupled with high Genetic advance was recorded for Plant height (cm). Divergence analysis followed by Mahalanobis [1] D2 analysis has revealed the presence of a substantial amount of diversity among the genotypes. Clusters I contain 19 genotypes followed by Clusters II contain 18 genotypes while Clusters III, IV, V, VI are mono genotypic. The maximum inter-cluster distance was observed between Cluster IV and VI (290.82) followed by Cluster IV and V (238.70). Thus, genotypes present in these clusters suggest that the genetic architecture of the genotypes in one cluster differ from another cluster which provides a broad spectrum of variability in segregation and may be used as parents in the future hybridization programme to develop desirable genotypes.

Genetic Diversity Analysis for Yield and Quality Traits in Rice Cultivars of Manipur and Assam

The North–Eastern region of India is blessed with wide variability in rice. The present investigation was carried out with 41 diverse cultivars of rice collected from the farmers’ fields of Manipur and Assam to estimate the nature and magnitude of genetic divergence among the genotypes using Mahalanobis D2 statistics. The germplasm consisted of the popular black rice and some glutinous and non-glutinous rice which are commonly grown in both regions. The experimental materials were evaluated during the Kharif season of 2020-2021, following a randomized block design with three replications at the experimental field of BN College of Agriculture, Biswanath Chariali, Assam. The genotypes exhibited significant differences for all 24 characters under study. The cluster analysis indicated that 41 genotypes were grouped under 12 different clusters and cluster IV was the largest comprising the maximum number of genotypes with 12 genotypes, followed by cluster V with eight genotypes, cluster X with five genotypes, clusters II and XII with four genotypes each, cluster I with two genotypes and clusters III, VI, VII, VIII, IX & XI with one genotype each. Among all the characters studied, grain length exhibited maximum contribution towards divergence followed by kernel length after cooking, grain breadth, 100-grain weight and kernel breadth after cooking. Clusters X and XII showed the maximum inter-cluster distance and the maximum intra-cluster distance was exhibited by cluster XII, indicating the existence of a significant amount of variability within the cluster. The intra-cluster distance ranged from zero (clusters III, VI, VII, VIII, IX, XI) as they consist of a single genotype each to 1146.89 (cluster XII). Hybridization among the genotypes of clusters X and XII is expected to produce better heterotic combinations.