<div>Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement. 
 
Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity. 
 
Result: Principal component analysis revealed that first five principal components possessed Eigen value &gt; 1, cumulatively contributed &gt; 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.</div>

<div>Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis</div>

<div style="text-align:justify">Background: Seventy breeding lines of mung bean were evaluated for 20 different characters and mean values were worked for genetic diversity by Mahalanobis D2 statistic. 
 
Methods: The experiments included 70 mung bean breeding lines which were collected from Plant Breeding Unit, Agricultural Research Station, Badnapur. They were grown during Kharif 2016 at experimental research farm Badnapur of Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. The data were recorded for 20 different characters on 10 randomly selected plants. The statistical analysis were done by Mahalanobis D2 statistics. 
 
Result: The results of D2 analysis indicated the presence of considerable genetic divergence among these breeding lines. In the present study, inter-cluster distances were worked out considering 20 characters and these distances ranged from 240.96 (between cluster V and cluster VII) to 1080.72 (between cluster V and cluster VIII). The inter-specific derivatives were grouped into eight clusters. The maximum inter-cluster distance was between cluster V and cluster VIII. The maximum inter-cluster distance was between cluster V and cluster VIII (1080.72), followed by cluster II and cluster III (932.25), cluster IV and cluster VIII (910.11), cluster VII and cluster VIII (738.30), cluster I and cluster VIII (732.61), cluster VI and cluster V (660.49) and cluster II and cluster VI (494.93). This suggested that there is wide genetic diversity between these clusters. Based on these studies, crosses can be made between breeding lines of these clusters to obtain desirable results either in transgressive breeding or in heterosis breeding. Cluster VIII and cluster IV showed high mean values for most of the yield contributing traits like100-seed weight, shelling %, harvest index, pod length, primary branches per plant, days to 50% flowering, days to maturity, leaf width and days to shattering. So the lines from cluster IV and cluster VIII can be used for mung bean yield improvement programme.</div>

<div>Multivariate Analysis using D2 and Principal Component Analysis in Mung bean [Vigna radiata (L.) Wilczek] for Study of Genetic Diversity</div>

Background: Based on D2 analysis 53 chickpea genotypes were grouped into seven clusters. Among the VII clusters, cluster I consists of 30 genotypes forming the largest cluster followed by cluster II with 16 genotypes, cluster VII with three genotypes and cluster III, IV, V and VI with one genotype each. Inter cluster distance were found to higher than intra cluster distance which depicted wide genetic diversity among the chickpea genotypes under study. Contribution of various characters towards expression of total genetic divergence indicated that seed yield (27.77%) contributed maximum (24.74%) followed by biological yield and number of pods per plant (20.43%). The clustering pattern of genotype demonstrated that clustering does not follow any particular cluster pattern with respect to origin. The pattern of cluster analysis of the first principal component had the largest eigenroot 4.18 per cent of total variation followed by 3.53, 2.91, 2.02, 1.45, 1.26 and 1.15 from second to seven principal components. The eigenroot of first principal component accounted for 19.91 per cent of total variation followed by second to seven principal components which accounted for 16.82, 13.84, 9.62, 6.90, 5.99 and 5.48 per cent of total variations present in the genotypes. 
 
Methods: The study was carried out at Pulses Research Sub-Station (PRSS), Samba and Advanced Center for Rain-fed Agriculture (ACRA), Rakh Dhiansar during Rabi seasons 2017-18 and 2018-19. The experimental material comprising of 48 chickpea (Cicer arietinum L.) genotypes along with 5 checks were evaluated in augmented block design. 
 
Result: The genotypes of cluster II, V and VII had highest inter-cluster distances as well as higher cluster means for most of the yield component traits indicating that these genotypes were most diverse can be used as parents in hybridization programme of chickpea breeding. The variation present in the chickpea genotypes under study can be exploited through selection and hybridization among identified genotypes for breeding high yielding chickpea genotypes.

Genetic Diversity Analysis of Chickpea Genotypes (Cicer arietinum L.) for Seed Yield and Morpho-genetic Traits

<div>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&rsquo;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&nbsp; 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.&nbsp;</div>

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

<div>Background: Asian soybean rust caused by Phakopsorapachyrhizi Syd. is a major threat for production and expansion of soybean in India. Understanding the nature of inheritance of rust resistance in DSb 21 will help in estimating the number of genes involved in governing the resistance mechanism and thus will be helpful in designing a suitable breeding method. &nbsp; 
 
Methods: Utilizing JS 335 and EC 241778, in a long term breeding programme, a highly rust resistant variety, DSb 21 has been released from University of Agricultural Sciences Dharwad, Karnataka. To study the genetics of rust resistance in DSb 21, F2 and F3 generation of&nbsp;two crosses involving susceptible x resistant (JS 335 x EC 241778) and resistant x susceptible (DSb 21 x JS 335) were used.&nbsp; 
 
Result: The F2 segregation analysis in both the crosses revealed the same segregation ratio of three resistant to one susceptible phenotype based on chi square test indicating rust resistance is controlled by a single dominant gene. In both the crosses the F2 results were confirmed by studying the F3 progenies for reaction to rust.</div>

<div>Genetic Enhancement and Genetic Analysis of Resistance to Asian Soybean Rust in India</div>

<div>Background: Fennel (Foeniculum vulgare Mill.) is a diploid horticultural species celebrated for its biennial or perennial life cycle. The cultivation of high yielding varieties necessitates a comprehensive understanding of the prevailing genetic diversity and the heritability of various traits. Therefore, the estimation of GCV and PCV, genetic progress and heritability, genetic advancement and correlation between seed yield and various quality is crucial. 
 
Methods: The present investigation was conducted at College of Agriculture in Jabalpur, Madhya Pradesh during the Rabi season in 2021-2022. This study evaluated twenty four fennel genotypes using a randomized block design with three replications. The primary aim was to explore the genetic variability, heritability and genetic advancement&nbsp; and analyze the nature and magnitude of correlations, path coefficients and genetic divergence related seed yield and its contributing traits. 
 
Result: The highest coefficient of variation, both GCV and PCV were recorded for number of umbels per plant, followed by number of seeds per umbel, branches per plant, seed yield per ha and per plant, test weight, plant height and number of umbellets per plant. High heritability was associated with genetic advance as a percentage of mean for traits such as number of seeds per umbel, seed yield and number of umbels per plant. Cluster V exhibited the highest intra cluster D2 followed by cluster III, both of which were polygenotypic. A thorough examination of the cluster means as well as intra and inter cluster distances and individual performances revealed that the genotypes RF 101 (check), UF 231 and RF 205 (check) stands out as superior options demonstrating significant genetic diversity. Thus, these genotypes may be utilized in future breeding&nbsp; programmes for creating maximum variability. 
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Genetic Variability, Heritability, Genetic Advance, Correlation Coefficient and Path Analysis of Fennel Genotypes

<div>Background: Ricebean (Vigna umbellata) is a minor pulse crop mainly cultivated for food, fodder and green manure. The assessment of variability is essential pre requisite for formulating an effective breeding programme, as the existing variability can be used to enhance the yield level of cultivars. 
&nbsp; 
Methods: The present experiment was carried out during rabi season 2022-23. The experiment was carried out using Augmented design II at Department of Pulses, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore. 
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Result: Morphological characterization of ricebean genotypes revealed the presence of low variability for the qualitative traits except for growth habit, twining tendency, terminal leaflet shape and stem pubescence. High heritability coupled with high genetic advance as per cent of mean was noticed for the following traits viz., number of pods per plant (95.56, 63.92), number of clusters per plant (87.58, 52.88), number of primary branches per plant (70.29,32.77), hundred seed weight (97.32, 26.29) and single plant yield (90.76, 43.36). The traits viz., number of pods per plant (0.881), number of clusters per plant (0.720), pod length (0.326), number of seeds per pod (0.311), plant height (0.257), number of primary branches per plant (0.196) and hundred seed weight (0.192) exhibited significant positive association with single plant yield. PCA analysis revealed that the following traits viz., number of pods per plant, single plant yield, number of clusters per plant, number of seeds per pod and pod length contributed maximum to the genetic variability. In addition, it also earmarked the best performing genotypes for each biometrical trait. Hence, the above findings could be effectively utilized for the development of ricebean cultivars with desirable plant type.</div>

Genetic Parameters, Genetic Association and Principal Component Analysis of Yield and Yield Contributing Traits in Ricebean (Vigna umbellata)

Generation Mean Analysis was carried out using six basic generations in 3 different crosses of cowpea to determine suitable breeding methods. &nbsp;For most of the studied traits, additive, dominance, additive x additive, additive x dominance and dominance x dominance effects were significant. &nbsp;Additive effect significantly contributed for days to 1st flowering and seed yield per plant. &nbsp;Dominance effect was significant for the incidence of cowpea mosaic virus in family 1, while for pod maturity in family 2. &nbsp;Additive x dominance type of interaction contributed significantly for days to 1st flowering, days to pod maturity and seed yield per hectare. &nbsp;Duplicate type of epistasis was observed for days to 1st flowering and incidence of cowpea mosaic virus in family 1, number of pods per plant and pod length in family 2 and 3. &nbsp;The findings suggested that pureline, pedigree and recurrent selection could be followed in cowpea improvement.

Genetic analysis of quantitative traits in cowpea [vigna unguiculata (L.) walp.] using six parameter genetic model&nbsp;

<div>Background: Though modern high yielding and synthetics developed through maize heterosis are replacing low-yielding maize populations worldwide, it has shown little impact in Kashmir due to poor adaptability and expensive seed cost. Nevertheless, retaining popularity due to adaptability, more resistance to natural factors, early maturity, good grain quality, great food and fodder value and ability to thrive best under low input conditions, landraces are going out of farmer&rsquo;s domain and becoming extinct owing to low yielding potential, low resilience to some biotic stresses and lower sensitivity to inputs. For developing high yielding, climate-resilient cultivars and broadening of the genetic base, efficient and rapid identification and introgression of novel and favourable alleles dispersed among the landraces are necessary.&nbsp; 
 
Methods: Seventy maize landraces from different parts of Kashmir valley designated as K-L1 to K-L70 were subjected to genetic analysis for thirteen important agronomic traits viz. days to 50% tasselling, days to 50% silking, anthesis-silking interval, plant height, ear height, days to maturity, ear diameter, kernel rows per ear, kernels per row, prolificacy, shelling percentage, yield per hectare and 100-grain weight. The least significance increase was calculated to evaluate best performing landraces and clustering of landraces was done using Mahalanobis D2 analysis through Tocher&rsquo;s method. The experimentation was carried out at Dryland Agriculture Research Station Budgam during the years 2019 and 2020. 
 
Result: Significant differences for all agronomic traits except anthesis-silking interval and prolificacy depicted the presence of significant genetic variability. The least significant increase calculations allowed the evaluation of best-performing landraces for specific traits and&nbsp; Mahalanobis D2 analysis through Tocher&rsquo;s method led to clustering landraces into 14 clusters with cluster I having the highest 23, followed by cluster VI with 14, cluster II and cluster III each with 9, cluster VIII with 6 genotypes and rest 9 clusters being mono-genotypic. Intra and inter-clustering distance and cluster means suggest utilizing genotypes belonging to clusters with wider statistical distances for crossing in hybridization programme to produce segregates with extensive variation resulting in higher heterosis.</div>

Genetic Diversity Analysis in Maize Landraces under Temperate Ecology

Bhendi [Abelmoschus esculentus (L.) Moench] is a short duration vegetable crop that could fit well in any cropping system. Karaikal located along the East Coast at the tail end of river Cauvery is suitable for cultivation of this nutritionally and commercially important vegetable crop. As identification of any high yielding genotypes depends on the extent of variability present in the germplasm and the extent of genetic gain expected out of selection for most desired traits, a study was conducted with forty genotypes of bhendi to assess the extent of variability, heritability and genetic gain, besides studying the nature and extent of correlation of important yield determinants on yield of bhendi. The presence of wide variation along with high heritability and genetic gain indicated the predominance of additive gene action for fruit length, fruit weight, number of fruits plant-1 and fruit yield plant-1. Correlation and path coefficient analysis revealed the importance of number of fruits plant-1 and fruit weight as important yield determinants in bhendi. 

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

Multivariate Analysis using D² and Principal Component Analysis in Mung bean [Vigna radiata (L.) Wilczek] for Study of Genetic Diversity

Genetic Diversity Analysis of Chickpea Genotypes (Cicer arietinum L.) for Seed Yield and Morpho-genetic Traits

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

Genetic Enhancement and Genetic Analysis of Resistance to Asian Soybean Rust in India

Genetic Variability, Heritability, Genetic Advance, Correlation Coefficient and Path Analysis of Fennel Genotypes

Genetic Parameters, Genetic Association and Principal Component Analysis of Yield and Yield Contributing Traits in Ricebean (Vigna umbellata)

Genetic analysis of quantitative traits in cowpea [vigna unguiculata (L.) walp.] using six parameter genetic model

Genetic Diversity Analysis in Maize Landraces under Temperate Ecology

Genetic analysis in Bhendi [Abelmoschus esculentus (L.) Moench]