Selection Of Parents Research Articles

Combining ability analysis for fruit yield and related traits in Brinjal (Solanum melongena L.) using Line × Tester mating design

Brinjal (Solanum melongena L.) is a significant vegetable crop, widely cultivated and consumed in households across India. Enhancing fruit production per unit area requires a focus on key traits such as early maturity, enhanced plant vigor and increased fruit yield. Consequently, crop breeding programs emphasize the development and commercialization of brinjal hybrids tailored to regional needs. Effective crop improvement hinges on selecting suitable parental lines and employing precise crossing techniques to generate hybrids with desirable agronomic traits. The present study was conducted to assess the combining ability for fruit yield and related traits in brinjal. The experiment was carried out during the Kharif season of 2023 and the summer season of 2024 at the Vegetable Research Centre, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. A randomized block design (RBD) with three replications was utilized. The study involved 30 hybrid combinations derived from 13 brinjal genotypes, employing a line × tester mating design with 10 lines and 3 testers. Results indicated that among the parental genotypes, PBGL-5 (88.11), PBGL-7 (85.02) and Swarna Abhinav (67.80) demonstrated high general combining ability (GCA) for fruit yield and related traits. Among the hybrid combinations, Pusa Kaushal × Pant Samrat (153.16), Pusa Ankur × Kashi Uttam (126.37) and PBGL-5 × Pant Rituraj (116.77) exhibited superior specific combining ability (SCA) effects. These results highlight the potential of the identified parents and hybrids as promising genetic resources for future breeding programs aimed at hybrid development and yield enhancement. In conclusion, the identified genotypes and crosses with favorable GCA and SCA effects can serve as valuable candidates for breeding programs to develop high-yielding, region-specific brinjal hybrids. This study underscores the importance of systematic parental selection and hybrid evaluation in advancing brinjal crop improvement initiatives.

Assessment of Field Pea (Pisum sativum var. arvense) Genotypes for Morphological Traits, Quality Traits and Molecular Characterization using SSR Marker

Background: Field pea is an important cool season grain legume crop. This study was conducted on field pea to explore phenotypic and molecular diversity among field pea genotypes, catering to current and future crop improvement. Methods: In this investigation forty-six genotypes of field pea were evaluated in randomized block design to assess phenotypic diversity for morphological and quality traits, alongside molecular characterization using simple sequence repeat (SSR) markers. Result: Variability analysis displayed substantial variability for all traits among test genotypes. Cluster analysis grouped the all genotypes into three distinct multi-genotypic clusters with clusters II and III having highest inter-cluster distance. Molecular characterization revealed the detection of 43 repeatable alleles by 14 polymorphic SSR markers, spanning a size range of 150 bp (AA122) to 970 bp (AA504), with a maximum of 4 fragments intensified by AD147, D21, AA504, AA122 and A9. Utilizing Jaccard dissimilarity coefficients and UNJ methods, all forty-six genotypes were grouped into three clusters. This study on field pea facilitates the identification of diverse parent selections capable of producing desirable segregants in future breeding programs.

Assessment of the quality of genealogical data in breeding enterprises of Western Siberia

Analysis of genealogical databases containing more than 6 million records revealed a significant number of gaps in the data on the origin of animals, especially for sires. This complicates the implementation of automated parental pair selection technologies and reduces the effectiveness of inbreeding level control. It was found that on average 7% of records on ancestors up to the third row of the pedigree contain gaps, of which 85.5% are for sires. This is a serious problem in the creation of regional digital platforms for the automation of decision-making in breeding livestock, limits the possibilities of an objective assessment of the breeding value of animals and hinders the necessary pressure of targeted artificial selection and assignment of sires to breeding stock. Methods for improving the quality of primary genealogical data are proposed, including using foreign sources. It is shown that automation of the decision-making process in purebred dairy breeding allows not only to speed up the detection of errors, but also to significantly reduce the time for their correction thanks to the created data aggregators. This process can become the basis for large-scale verification and validation of primary zootechnical accounting data with subsequent transfer to the Federal State Information and Analytical System of Breeding Resources (FGIAS PR). In addition, this will increase the efficiency of zootechnicians-breeders in large breeding and commercial farms, and will also allow selecting breeding bulls that are genetically compatible with the breeding stock of both a separate region and their totality.

Breeding Cowpea (Vigna unguiculata L.) for High Seed Yield, Protein Content and Harvest Index: Genetic Parameters to Identify Useful Parents

Background: Cowpea is a highly adaptable, versatile and nutrient-dense grain legume hampered by low productivity across the globe. The selection of parents for getting high frequency of heterotic hybrids is a topic of recurrent contention among plant breeders. So with regard to obtaining high seed yield, harvest index and protein content, the goal of the current study is to identify parents which upon hybridization will generate superior heterotic hybrids. Methods: Three testers and seven lines were used to develop 21 crosses, totalling to 31 genotypes in the experimental material evaluated at Pulses Research Station, SDAU, Sardarkrushinagar, Gujarat, India. The overall heterotic status (high or low) and gca status (high or low) of each parent and hybrid were determined based on three characters viz., harvest index, protein content and seed yield. Furthermore, the hybrids were classified into various classes according to the parents gca status. Result: Examining the heterotic effect of the crosses along with the individual performance showed that the GC 7 x GC 4 and EC 724035 x PGCP 12 crosses were the best for seed yield per plant, harvest index and protein content. Three of the 7 lines viz., JLS 60, EC 72 3909 and PL 4 and two of the three testers i.e. PGCP 12, PL 7 displayed high overall gca status. Among the hybrids, eleven (52.38%) and twelve (57.14%) were categorised as having high (H) overall sca and heterotic status, respectively, while the remaining crosses were categorised as having low (L) overall sca and heterotic status. As non-additive gene action for these traits predominated in current study, heterotic hybrids for these traits were generated by parents with all combinations i.e. high, contrasting, or even low gca effects. Therefore, when selecting parents based on gca effects, careful consideration should be given to the sort of gene action governing that character.

Inheritance patterns of pomological traits in walnut hybridization breeding: influence of parental varieties on nut traits

BackgroundWalnut (Juglans regia L.) breeding programs aim to develop new genotypes that exhibit superior agronomic traits, including high yield, improved nut quality, and favorable phenological traits. One of the primary methods used in these programs is hybridization, which involves controlled crosses between selected parent varieties. In reciprocal cross, understanding the genetic contributions of both maternal and paternal parents is crucial, as these contributions significantly influence the phenotypic traits of the resulting progeny. This knowledge allows breeders to predict and select genotypes that best meet the desired breeding objectives, ultimately enhancing agricultural productivity and sustainability.ResultsThis study analyzed the pomological traits of F1 plants derived from four different hybrid combinations: Pedro × Maraş 18, Pedro × Sütyemez 1, Maraş 18 × Pedro, and Sütyemez 1 × Pedro. The assessment focused on key nut traits, including nut length, nut diameter, nut weight, kernel weight, and kernel percentage. Statistical analyses revealed significant variations in these traits among the hybrid combinations, with these differences determined at the p < 0.05 significance level. Kernel weight exhibited the highest coefficient of variation (CV = 33.63%), indicating substantial variability in this trait among the hybrids. Nut diameter had the lowest variability (CV = 12.82%), suggesting greater consistency across the hybrid combinations. Other traits, such as nut weight, nut length, and kernel percentage, showed intermediate levels of variability, with CVs of 27.33%, 13.45%, and 18.59%, respectively. The study found that maternal parents played a more partially dominant role in determining nut traits in most hybrid combinations. However, when Sütyemez 1 and Maraş 18 were used as maternal parents, their influence on the inheritance of some nut traits was relatively greater than the other parent variety (Pedro).ConclusionThe findings emphasize the crucial role of parent selection in walnut hybridization breeding programs, with parental effects being relatively prominent in influencing pomological traits, underscoring the need for careful selection of maternal parents to achieve the desired outcomes. Among the varieties studied, Pedro, Maraş 18, and Sütyemez 1 were identified as promising parent genotypes for improving key nut traits. The variability observed in traits such as kernel and nut weights suggests potential for further selection and genetic improvement. This variation highlights the genetic diversity present in the studied hybrids, which can be effectively utilized in breeding efforts. These results not only contribute to the improvement of walnut varieties but also have broader implications for global walnut production, providing valuable guidance for breeding programs aiming to improve nut quality in walnut hybridization programs.

Evaluation of Genetic Diversity of Advanced Pigeonpea [Cajanus cajan (L.) Millspaugh] Interspecific Derivatives Using Mahalanobis D2 and Selection of Elite Lines Using Multi-Trait Genotype-Ideotype Distance Index

The experiment was conducted during kharif (May–November, 2022) season at the field experimental area of the Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana and at Regional Research Station, Faridkot, Punjab, India to assess the genetic diversity of 40 advanced BC1F8/F9 pigeonpea interspecific derivatives derived from a cross between Cajanus scarabaeoides (L.) Thouars (ICP 15683) and C. cajan (L.) Millspaugh (ICPL 20329) using Mahalanobis D2. The data for 11 key productivity traits was statistically analysed using R software. The derivatives were grouped into five clusters. Intra-cluster distances varied from 0.00 (Cluster V) to 107.40 (Cluster IV), while inter-cluster distances ranged from 123.49 (Cluster II and V) to 511.00 (Cluster IV and V). The derivatives in the present study were mostly divergent for harvest index, pods plant-1, primary branches and seed yield plant-1. The MGIDI index was remarkably efficient in selecting superior derivatives, resulting in desired gains across numerous traits. The MGIDI index highlighted six high-performing genotypes—AL 2581, AL 2611, AL 2577, AL 2613, AL 2606 and AL 2597. This research laid the groundwork for forthcoming pigeonpea hybridization initiatives, enabling the selection of parents based on both diverse genetic backgrounds and specific traits. The study suggested a targeted screening of lines within promising clusters for utilization in ongoing breeding programs, facilitating the development of valuable populations and hybrids.

Genetic Tendency Analysis and Comprehensive Antioxidant Activity Evaluation of Leaves and Flowers of Loquat F1 Generation.

Loquat leaves, flowers, and other organs contain abundant antioxidant substances, which have wide applications in medicine, health, and food industries. This study aims to provide theoretical guidance for loquat hybrid parent and combination selection and a basis for high-quality loquat strain screening and development. For comprehensive antioxidant profiling, we used "Ninghaibai" and "Oobusa" loquat and their F1 generation as experimental materials to determine the total phenol, flavonoid, DPPH, ABTS, and FRAP content in the leaves and flowers of 56 strains. Five traits, including total phenols, flavonoids, DPPH, ABTS, and FRAP, were widely separated and normally distributed in the flowers of 56 F1 loquat strains, exhibiting the genetic basis of these quantitative traits. However, these traits displayed widely separated and slightly skewed distribution in the leaves of the F1 generation. The total phenols, flavonoids, DPPH, and FRAP showed a trend of small inheritance in the leaves. However, the ABTS showed a trend of medium and high inheritance in leaves and flowers, respectively. Through cluster and principal component analyses, a comprehensive antioxidant activity evaluation was conducted. Ten strains with comprehensive scores greater than 1 for antioxidant activity in leaves and flowers were selected. Among them, the top three strains with high antioxidant capacity were ND107, "Oobusa", and ND128. These results suggest that hybrid breeding guided by the genetic characteristics of each trait can improve the possibility of cultivating new varieties with high antioxidant activity.

LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization

This paper addresses the issue of quality of service routing optimization within the Internet of Things networks. We particularly focus on the energy-aware and the lightweight aspects. By recognizing the relationship between lightweight and energy-aware routing, we set out to study their combined benefits. This study aims to enhance the Routing Protocol for Low Power and Lossy Networks by integrating energy-awareness and lightweight characteristics based on the Particle Swarm Optimization algorithm. Our approach addresses energy consumption, routing overhead and decision complexity in route establishment. The principal contributions include the introduction of an objective function that considers Expected Life Time, Delay and a new proposed metric Energy Aware-Expected Transmission Count. The improvement of the Long Short Term Memory predicting inertia weight based PSO with Online Gradient Descent that is used to optimize both the parent selection process and Trickle Timer mechanism. The controlled parent switching process to solve unnecessary and frequent changes. Our approach is validated through simulations in Contiki COOJA, with thorough comparisons with some existing protocols based on packet delivery ratio, average energy consumption, convergence time, control overhead, average end-to-end delay and average parent switching as performance metrics. The results reveal that our approach performs better. Depending on the protocol used for comparison, our approach reduced parent switching by 42.59–61.73%, convergence time by 20.31–66.06%, control overhead by 14.4–23.64%, energy consumption by 29.86–49.6%, end-to-end delay by 7.66–40.81% and increased packet delivery ratio by 2–42.92%.

Genetic diversity and population structure analyses of tropical maize inbred lines using Single Nucleotide Polymorphism markers.

Analyses of the genetic distance and composition of inbred lines are a prerequisite for parental selection and to exploit heterosis in plant breeding programs. The study aimed to assess genetic diversity and population structure of a maize germplasm panel comprising 182 founder lines and 866 derived inbred lines using Single Nucleotide Polymorphism (SNP) markers to identify genetically unique lines for hybrid breeding. The founder lines were genotyped with 1201 SNPs, and the derived lines with 1484 SNPs. Moderate genetic variation, with genetic diversity ranging from 0.004 to 0.44 with a mean of 0.25, was recorded for the founder lines, while corresponding values of 0.004 to 0.34 with a mean of 0.13 were recorded for the derived lines. Heterozygosity values ranging from 0.00 to 0.24 and a mean of 0.08 were recorded for both lines. Of the SNP markers used, 82% of the 1201 markers and 84% of the 1484 markers exhibited polymorphism information content ranging from 0.25 to 0.50. Analysis of molecular variance revealed significant genetic differences (P ≤ 0.001) among and within populations in the founder and derived lines. Most detected variations, i.e., 97% and 88.38%, were attributed to within populations in the founder and derived lines, respectively. Population structure analysis identified three distinct subpopulations among founder lines and two among derived lines. Cluster analysis supported the population structure The following genetically distant founder and derived inbred lines were selected: G15NL337 and G15NL312 (Cluster 1), 15ARG152 and RGS-PL44 (Cluster 2), RGS-PL44 and 15ARG149 (Cluster 2), and RGS-PL33 and RGS-PL44 (Cluster 2), respectively. The selected lines are genetically distinct and recommended for marker-assisted hybrid maize breeding to exploit the frequency of beneficial alleles. This study provides valuable insights for maize breeding programs, enabling the exploitation of beneficial alleles and contributing to improved crop yields and food security through hybrid breeding.

Varietal Characterization and Selection of Superior Parents for Hybridization Programme in Greengram [Vigna radiata (L.) Wilczek

The present study was conducted to examine the genetic basis of yield and its related components, enabling selection based on heritability and genetic gain. The experiment involved the evaluation of fourteen accessions of green gram in Kharif season of year 2024 in a randomized complete block design. Data were collected from ten important yield related characters and analysed statistically. ANOVA revealed significant variation in the genetic material used in the study. Among the studied genotypes, CO 7, CO 4, CO 8, and CO 6 were identified as superior for seed yield based on their mean performance.The phenotypic coefficient of variation exceeded the genotypic coefficient of variation, indicating that the observed variation between the two is primarily due to the genotypes, with minimal environmental influence. Notably, single trait, number of pods per plant exhibited both high heritability and high genetic advance.

Genetic Analyses of Flower, Fruit, and Stem Traits of Intergeneric Hybrids Between 'Honghuagqinglong' and 'Heilong' Pitayas.

Pitaya is renowned for its delicious taste, high nutritional value, and economic as well as ornamental appeal. Breeding new pitaya varieties can boost economic returns by appealing to consumers with diverse morphological traits. However, the genetic basis underlying key traits in intergeneric hybrids of pitaya has yet to be fully understood. This study investigates the genetic dynamics in flower, fruit, and stem traits, including segregation patterns and a mixed inheritance model for major and polygenic traits, in an intergeneric hybridization between 'Honghuagqinglong' (HHQL) (Hylocereus stenopterus) and 'Heilong' (HL) (Selenicereus grandiflorus). The study identified normal or skewed, normal distribution patterns in seven floral, fifteen fruit, and five stem traits, indicating their quantitative nature governed by multiple genes. Specifically, flower size and color exhibited a hereditary bias towards 'HL' characteristics, while 'HHQL' significantly influenced the coloration of fruit peel and pulp. Fruit weight and total soluble solids (TSS) content decreased, whereas stem traits exhibited broader and thicker dimensions with fewer thorns. This study offers valuable insights into genetic variation and the influence of major genes on flower, fruit, and stem traits between 'HHQL' and 'HL' intergeneric hybrids, providing a useful reference for parental selection in pitaya breeding programs.

Integrating multi‐trait genomic selection with simulation strategies to improve grain yield and parental line selection in rice

AbstractInclusion of correlated secondary traits in the prediction of primary trait in multi‐trait genomic selection (GS) models can improve the predictive ability. Our objectives in the present investigations were to (i) evaluate the effectiveness of multi‐trait and single‐trait GS models for the higher predictive ability and (ii) compare the breeding potential of parental lines selected based on phenotype and GS for grain yield in rice. We used phenotype data of five correlated traits as secondary traits evaluated to predict the grain yield, a primary trait. Yield related functional markers were used for prediction. Breeding populations were simulated using the best parents selected through GS and phenotype based selection. Results suggest that the multi‐trait model resulted in higher predictive abilities (0.82 for grain yield) than single‐trait models (0.76 for grain yield) and parents selected through GS have potential to produce superior progenies. We conclude that the use of a multi‐trait GS approach is advantageous over single‐trait models, and the GS also help selecting potential parents for developing improved populations. The results of the study have potential scope for improving quantitative traits using GS in rice.

Genetic divergence and hybrid potential for yield and fiber quality in cotton (Gossypium hirsutum. L)

ABSTRACT Fiber trait is multigenic and each parent of the population carrying different genes aid in arriving at varied blend of association between yield and fiber quality traits. Eleven parental lines were crossed in half-diallel fashion to arrive at 55 hybrid combinations, which were evaluated under seven environments. The results manifested highly significant differences among the traits studied, indicating wide range of genetic diversity in the parental genotypes. Combining ability studies revealed parental genotypes SCS-PL-01, SCS-PL-04 as best general combiners for seed cotton yield; SCS-PL-04, SCS-PL-12, SCS-PL-51, SCS-PL-59 for fiber length; SCS-PL-51 for fiber strength and SCS-PL-02 for micronaire value. Genetic diversity of parental genotypes estimated using microsatellites was compared with SCA effects to understand the role of genetic distance (GD) in realizing the heterosis. Comparative characterization of parental genotypes indicated efficiency of capillary gel electrophoresis over metaphor agarose gel electrophoresis and could identify 55 unique bands. The study indicated predicting heterosis using GD estimates is competent when markers linked to the QTLs are used. Also, marker-assisted parental selection in combining ability studies would be a better approach in realizing potential crosses with high yield and fiber quality traits.

Optimizing Genetic Algorithm by Implementation of An Enhanced Selection Operator

The Traveling Salesman Problem (TSP) represents an extensively researched challenge in combinatorial optimization. Genetic Algorithms (GAs), recognized for their nature-inspired approach, stand as potent heuristics for resolving combinatorial optimization problems. Nevertheless, GA exhibits inherent deficiencies, notably premature convergence, which diminishes population diversity and consequential inefficiencies in computational processes. Such drawbacks may result in protracted operations and potential misallocation of computational resources, particularly when confronting intricate NP-hard optimization problems. To address these challenges, the current study underscores the pivotal role of the selection operator in ameliorating GA efficiency. The proposed methodology introduces a novel parameter operator within the Stochastic Universal Selection (SUS) framework, aimed at constricting the search space and optimizing genetic operators for parent selection. This innovative approach concentrates on selecting individuals based on their fitness scores, thereby mitigating challenges associated with population sorting and individual ranking while concurrently alleviating computational complexity. Experimental results robustly validate the efficacy of the proposed approach in enhancing both solution quality and computational efficiency, thereby positioning it as a noteworthy contribution to the domain of combinatorial optimization.

Breeding Brassica juncea hybrids with higher seed weight and oil content: Defining criteria for selection of parents

Most of the released high-yielding hybrids of Brassica juncea have a low 1000-seed weight (TSW) with no increment in the percent oil content (OC), and, therefore, these hybrids have poor acceptance among the farmers in India. It is, thus, imperative to understand the genetic basis of these traits and deploy them in commercial hybrid breeding programs. The present study utilized a set of 15 diverse B. juncea genotypes with TSW and OC ranging from 1.32 to 8.26 g and 31.93–43.39 %, respectively, to generate 210 hybrids following a full diallel mating scheme. These hybrids along with their parents, were evaluated in three different environments. Inheritance of TSW suggests the predominance of additive gene action, whereas non-additive gene action was observed to regulate OC. Further, TSW and OC were reported to be influenced by maternal and non-maternal effects, respectively. Parents with bold seeds viz., NPJ 253, RH 761 and EC 223389 were identified as good general combiners for both the traits. Hybrid generated from the cross NPJ 253 x NPJ 161, with both parents having high seed weights, exhibited the highest mean values (8.43 g) and heterobeltiosis (17.2 %) for TSW. Whereas, hybrid between parents NPJ 253 and IC 426372, possessing high and low seed weights, respectively, observed the highest mean value (44.95 %) and heterobeltiosis (14.89 %) for OC. Keeping both TSW and OC together, hybrids viz., NPJ 253 x EC 223389 (H1), NPJ 253 x NPJ 161 (H2) and NPJ 253 x Pusa Tarak (H4) were identified as promising using the Multi-trait Genotype-Ideotype Distance Index. Lines with higher TSW and better combining ability for OC shall be converted to male and/or female lines for generating commercial hybrids. The scheme for deploying higher seed weight and improved oil content in B. juncea hybrids is discussed.

Identification of Floral Fragrance Components in 20 Intersectional Hybrids of Paeonia in Luoyang Region

ABSTRACTIntersectional hybrids of Paeonia (Paeonia Itoh hybrids) have rich colours and strong fragrance, combining the advantages of sect. Moutan and sect. Paeonia, and have great economic value and development potential. However, there have been few studies on the floral fragrance components of intersectional hybrids of Paeonia. In this study, the types and contents of volatile components of 20 intersectional hybrids of Paeonia were conducted. A total of 53 floral volatiles were identified though gas chromatography–mass spectrometry (GC–MS) analysis, with linalool, nonanal and phenylethyl alcohol as the main floral components. Based on the compound contents and odour activity values (OAVs) analysis, the 20 cultivars were classified into four aroma types: a floral scent, a fresh floral scent, a floral with spicy scent and a fruity scent. ‘Magical Mystery Tour’ had the highest volatile compound contents and OAVs, and had potential for exploitation. This study provided a theoretical reference for the selection of parents for flower fragrance breeding of Paeonia Itoh hybrids.

Determination of S‐Allele Combination in an Italian Apple (Malus × domestica Borkh.) Germplasm Core Collection

ABSTRACTAn S‐RNase‐based gametophytic self‐incompatibility (GSI) system, a mechanism that forces outbreeding by preventing self‐fertilization, characterizes the genus Malus. Knowledge of the self‐incompatibility (S) genotypes of apple cultivars is crucial for choosing pollen donors for fruit production and breeding. Even though the S‐allele of most commercial apple cultivars has already been identified, limited information is available about the S‐allele diversity within local germplasm collections. In this study, 67 S‐allele combinations of local apple accessions were identified. The allele S3 was the most common among local apple accessions followed by S1 and S7. The main aim of this study is to provide new information on cultivar compatibility, and these results will be used to set up new parent selection in apple breeding programmes as well as pollinator selection for the commercial orchard.

Genetic Diversity and Population Structure Analysis in Guar.

Guar [Cyamopsis tetragonoloba (L.) Taub] was domesticated in India and Pakistan. It is mainly self-pollinated, bushy, and deeply tap-rooted. Guar seed endosperm contains galactomannan gum, which is used in many food products, pharmaceuticals, cosmetics, explosives, meat products, and pet foods, and in the textile industry, yet its genetic diversity remains largely underexplored. Using 7000 high-quality single nucleotide polymorphism (SNP) markers acquired from genotyping by sequencing (GBS), we analyzed the genetic diversity and population structure in 225 guar accessions from India, Pakistan, and the United States. Structure Harvester revealed that K = 3 had the best delta K, whereas K = 2 had the second-highest delta K. Three major genetic clusters (K = 3) were identified using population structure analysis, utilizing an admixture model: 156 accessions (69.3%) were classified into Q1, 23 accessions (10.2%) in Q2, and 16 accessions (7.1%) in Q3. The remaining 30 accessions (13.3%) were included in the admixture. In all three of the subpopulations at K = 3, most of the guar accessions came from India. We also found that these clusters mostly correlated with geographic origins. Results showed that the Q2 and Q3 subpopulations included only guar accessions from India. Genetic resources from Q2 and Q3 may represent an untapped reservoir for introducing beneficial variety into the U.S. breeding populations. This genetic diversity and population structure analysis of the guar gene pool will be of interest to conduct allele mining and donor parent selection for the development of new and better guar germplasm for desired traits.

Koi Fish (Cyprinus carpio) Nursery Techniques at the Batu Kumbung Lingsar Fish Seed Center, West Lombok

Koi fish is one type of freshwater fish that is classified as an ornamental freshwater fish that has economic value in the national and international markets. Efforts to develop koi fish cultivation cannot be separated from the breeding stage such as enlargement and nursery activities. One of the koi fish cultivation places in West Lombok Regency is at the Batu Kumbung Lingsar Fish Seed Center, so it is necessary to know what nursery techniques are applied there considering its good production. The activity was carried out for approximately 30 days at the Batu Kumbung Lingsar using a descriptive method. The results of the activities obtained were that in the koi fish nursery technique at the Batu Kumbung Lingsar Fish Seed Center, it started from pond preparation (drying, fertilization, liming, filling with water), parent selection, spawning, nursery and feeding. The pond drying is done for 2 days, liming, fertilization, and filling with water are done for 1 day, the weight of the parent that is ready to spawn is 1.5 kg for the male parent while for the female parent 4 kg, the ratio of the parent used is 2:1 where 6 male and 3 female broodstocks, the nursery is done at the age of 2 days with the results of the offspring spread in the nursery as many as 5000 larvae, and the feeding technique uses the ad satiation method.

Assessing population structure and morpho-molecular characterization of sunflower (Helianthus annuus L.) for elite germplasm identification.

Sunflower (Helianthus annuus L.), known for its adaptability and high yield potential, is vital in global edible oil production. Estimating genetic diversity is a key pre-breeding activity in crop breeding. The current study comprised of 48 genotypes which were assessed for their biometrical traits at department of Oilseeds, Tamil Nadu Agricultural University, during the rainy season of 2022. The lines were subsequently characterised using 103 simple sequence repeat (SSR) markers for molecular diversity analysis. The results indicated that the net nucleotide distances indicated varying genetic divergence, with subpopulations II and V showing the highest (0.056) and I and IV the lowest (0.014). Subpopulation IV exhibited the highest heterozygosity (0.352), while subpopulation III had the lowest heterozygosity and a low Fst (0.173). Principal components analysis (PCA) and hierarchical cluster analysis were employed for assessing the morphological diversity, facilitating genotype grouping and parent selection for breeding programs. The first four components cumulatively accounted for 86.72% of the total variation. Cluster Analysis grouped 48 sunflower genotypes into three clusters based on genetic diversity. COSF 13B stands out for its high head diameter, oil content, seed yield, and oil yield based on mean performance of morphological data. Principal coordinate analysis (PCoA) mirrored the groupings from the Neighbor Joining method, with the first three components explaining 27.24% of the total variation. Molecular data analysis identified five distinct clusters among the germplasm. By integrating morphological and molecular marker data with genetic distance analysis, substantial diversity was revealed with the genotypes RHA 273 and GMU 325 consistently demonstrated high oil yield per plant. The genotypes GMU 477, GMU 450, COSF 13B, RHA 102, CMS 1103B, and RHA GPR 58 have been identified as suitable parents for enhancing oil content in sunflower breeding programs. These findings also aid in selecting SSR markers for genotype characterization and in choosing diverse parents for breeding programs.