Higher Genetic Gain Research Articles

Assessing Heat Stress Tolerance of Wheat Genotypes through Integrated Molecular and Physio-Biochemical Analyses

Heat as an abiotic stress significantly impairs the sustainable productivity of wheat (Triticum aestivum L.). To determine the tolerance of genotypes to heat stress, a comprehensive approach should be used that integrates simultaneous phenotyping and genotyping analyses. The aim of this study is to identify local heat-tolerant genotypes using simple sequence repeat (SSR) markers and evaluate the selected genotypes under field conditions for their tolerance to heat stress. Of the 12 SSR markers that showed polymorphism, eight were associated with six important traits. The use of hierarchical cluster analysis (HC) based on SSR markers led to the identification of 13 genotypes that showed varying results and were grouped into three distinct heat tolerance classes: tolerant (T), moderately tolerant (MT), and sensitive (S). The results showed that heat stress had a significant effect on 19 traits under this study, with significant variation in tolerance to heat stress between genotypes. The tolerant genotypes exhibited a range of average thousand-kernel weight (TKW) values between 40.56 and 44.85, while the sensitive genotype (Yecora Rojo) had an average TKW of 35.45. Furthermore, the tolerant genotypes showed two to three times higher levels of antioxidants compared to the sensitive genotypes when exposed to heat stress. Among the traits analyzed, six showed a favorable combination of high heritability (>60%) and genetic gain (>20%). Through the integration of principal component analysis and stepwise multiple linear regression, it was determined that six traits (grain yield, 1000-kernel weight, plant height, intercellular carbon dioxide, flag leaf area, and grain filling duration) revealed differences between the 13 genotypes. HC analysis of the six traits resulted in the same division of genotypes into three main categories as observed in an HC analysis based on SSR markers. It is worth noting that Saudi wheat, including KSU106, KSU105, and KSU115 as local genotypes, in addition to the 16HTWYT-22 genotype, showed higher heat tolerance compared to the other genotypes tested, indicating its potential suitability for agriculture in Saudi Arabia. These results contribute to breeding programs focused on developing heat-tolerant wheat varieties and accelerate progress in wheat productivity improvement programs.

The number of drones to inseminate a queen with has little potential for optimization of honeybee breeding programs

BackgroundMating control is a crucial aspect of honeybee breeding. Instrumental insemination of queens gives the breeder maximum control over the genetic origin of the involved drones. However, in addition to the drones’ descent, the breeder’s control also extends over the number of drones to use for inseminations. Thus far, this aspect has largely been ignored in attempts to optimize honeybee breeding schemes. The literature provides some comparisons between single drone inseminations (SDI) and multi drone inseminations (MDI) but it is unclear whether the number of drones used in MDI is a relevant parameter for the optimization of honeybee breeding programs.MethodsBy computer simulations, we investigated the effect of the number of drones per inseminated queen in breeding programs that relied on best linear unbiased prediction (BLUP) breeding values. We covered a range of 1 to 50 drones per queen and observed the developments of genetic gain and inbreeding over a period of 20 years. Hereby, we focused on insemination schemes that take the drones for one queen from a single colony.ResultsSDI strategies led to 5.46% to 14.19% higher genetic gain than MDI at the cost of 6.1% to 30.2% higher inbreeding rates. The number of drones used in MDI settings had only a negligible impact on the results. There was a slight tendency that more drones lead to lower genetic gain and lower inbreeding rates but whenever more than five drones were used for inseminations, no significant differences could be observed.ConclusionThe opportunities to optimize breeding schemes via the number of drones used in inseminations are very limited. SDI can be a viable strategy in situations where breeders are interested in genetically homogeneous offspring or precise pedigree information. However, such strategies have to account for the fact that the semen from a single drone is insufficient to fill a queen’s spermatheca, whence SDI queens will not build full-strength colonies. When deciding for MDI, breeders should focus on collecting enough semen for a succesful insemination, regardless of how many drones they need for this purpose.

Selection of high yielding stable forage sorghum genotypes using WAASB and MGIDI methods

Forage sorghum is a versatile and sustainable crop that is less demanding on inputs, produces significant biomass, and is tolerant of drought. In the present study, a set of 30 forage sorghum genotypes, including 21 B–lines and 9 varieties or restorer lines were evaluated under five different environments in Assam and Hyderabad during kharif, rabi and summer 2020–2021 for 12 forage yield related traits. Phenotypic stability was analyzed using multivariate techniques, including the weighted average absolute scores of BLUPs (WAASB) stability index and the multi-trait genotype ideotype distance index (MGIDI). A WAASBY, Y x WAASB bi-plot analysis revealed that genotypes G24 (348B), G25 (424B), and G30 (SSG-59-3) exhibited excellent stability with higher mean performance. MGIDI identified four genotypes, viz., G30 (SSG-59-3), G7 (NSS11B), G19 (327B) and G24 (348B) with higher mean performance and stability for all the 12 studied traits. These selected genotypes exhibited high heritability and genetic gain for green forage yield, indicating their stability and desirability. The strength-weakness plot showed that all selected genotypes were weak contributors to the MGIDI for all traits. This indicates that these genotypes are stable and closer to the ideotype, making them ideal candidates for breeding programs aimed at improving these traits.

Evaluation of Genetic Variability for Yield Improvement in Bitter Gourd (Momordica charantia L.) Genotypes

The degree of genetic variability found in any particular germplasm is a major factor in determining the best breeding program or technique to be used. Exploitation of the natural genetic variability present within a crop species can aid in meeting the rising demand through the identification and modification of the adaptive and productive genes present. Breeders thus identify natural genetic variability as the key to crop improvement. The present investigation was undertaken at the Experimental field of Urban Technological Park Habbak, Srinagar, Jammu and Kashmir during kharif-2022. To investigate several aspects of genetic variability, including mean, range, PV, GV, PCV, GCV, heritability, genetic gain, and genetic advance among the genotypes, the experiment was set up in a Randomized Block Design with three replications and a plant spacing of 2×1 m for thirty genotypes. For every character under study, it was discovered that the estimates of the phenotypic coefficient of variation were marginally greater than the respective genotypic coefficient of variation, indicating a possible involvement of environment in the expression of these traits. Fruit yield hectare-1 (q) exhibited the largest genotypic and phenotypic coefficient of variation (39.788 and 38.970). For yield hectare-1 (q), high heritability and high genetic gain (0.95 and 78.62) were observed. This suggests that additive gene effects are most likely the cause of the heritability and increases the likelihood that this characteristic would be fixed by selection. For every characteristic, the estimates of broad sense heritability were high. All these factors help in selection of better parents for the development of commercial varieties/hybrids. Considering the potential nutritional and economic benefits of bitter gourd (Momordica charantia L.), there is an imperative necessity to isolate such breeding lines having desirable traits, high yield potential along with better quality.

Genetic Variability, Correlation and Path Coefficient Analysis in Bottle Gourd [Lagenaria siceraria (Molina) Standl.] Genotypes

The present investigation was carried out at the Experimental field of Urban Technological Park Habbak, Srinagar, Jammu and Kashmir during kharif-2022. The experiment was laid out in Augmented Randomized Block Design with three blocks and plant spacing of 2×1 m for seventy- seven genotypes including two checks, Pusa Naveen and Pusa Santushti. Observations were recorded for growth and yield traits, seed traits and quality parameters. Analysis of variance revealed significant differences among genotypes for all the traits. The estimates of phenotypic coefficient of variation (PCV) were slightly higher than the corresponding genotypic coefficient of variation (GCV) for all the characters studied indicating little influence of environment in the expression of these traits. The highest phenotypic and genotypic coefficient of variation were observed for seed weight fruit-1 (45.15 and 45.13). High heritability coupled with high genetic gain was recorded for seed weight fruit-1 (0.99 and 93.01), indicating that the heritability is most likely due to additive gene effects and thus the chances of fixing this trait by selection are more. The estimates of heritability in broad sense were high for all the traits. Correlation studies indicated that fruit yield plant-1 followed by fruit weight, vine length, number of primary branches and number of fruits plant-1 had significant and positive correlation with fruit yield ha-1. Path coefficient analysis showed that fruit yield plant-1 followed by fruit weight, number of primary branches, node number at which 1st male flower appeared and fruit diameter had highest direct effects on the yield per ha-1.

Genetic Variability and Multivariate Analysis of Physio-Biochemical Traits in Coloured Grape Genotypes

Twenty-two coloured grape accessions were screened for various physio-biochemical traits. The genetic variability and multivariate analysis were carried out for growth and biochemical parameters of grape accessions grown under Pune conditions. High genotypic and phenotypic coefficient of variations were observed in average bunch weight, berry weight, proline and total tannin. All the biochemical parameters showed very high estimated heritability for broad sense (h2b.s.). Higher genetic gain was recorded for average bunch weight, total tannin, proline and protein while low genetic gain was observed in berry diameter and seeds/berry. The multivariate analysis revealed that biochemical parameters could be potentially used for discrimination of grape genotype. The heat map cluster analysis showed higher biochemical parameters in Kali Sahebi, Kishmish Maldovski, Red Ficosa, H-516 and Omania Black. Among the accessions studied, Kali Sahebi performed better concerning growth attributes like average bunch weight, berry diameter, berry and seed weight, days to harvest and biochemical constituents like total phenol, anthocyanin and colour intensity. A very close association was observed between phenotypic and genotypic variation, particularly for biochemical parameters. Therefore, very high heritability and genetic advance were recorded in these parameters. It can be concluded that the parameters governing the very close association between phenotypic and genotypic variation can contribute to the varietal selection and trait-specific varietal development programmes.

Morpho-agronomıc varıabılıty, herıtabılıty and genetıc advance studıes ın sesame (sesamum ındıcum L.) In nıgerıa

The study explored morpho-agronomic and biochemical traits to assess variability level and the degree of genetic diversity in 15 Sesame accessions. Data were subjected to analysis of variance, multivariate analyses, and genetic parameters were estimated. Significant differences (P < 0.05) existed among the accessions in all the characters. Four components with a cumulative variation of 85.7% were extracted. Substantial broad sense heritability estimates and high genetic gain were observed in secondary branches (97.8%; 719.4%), primary branches (96.1%;142,5%), capsules per plant (97.8%; 141.1%), single plant seed yield (86.87%; 46.03%), capsule length (99.16%; 32%), and 500 seed weight (95.15%; 34.12%). It may be inferred that a considerable level of variability existed among the accessions studied and charcters like branching habit, capsules per plant, capsule length and single plant seed yield could be considered for selection in breeding for superior genotypes. Bangladesh J. Bot. 53(1): 75-81, 2024 (March)

AI-assisted selection of mating pairs through simulation-based optimized progeny allocation strategies in plant breeding.

Emerging technologies such as genomic selection have been applied to modern plant and animal breeding to increase the speed and efficiency of variety release. However, breeding requires decisions regarding parent selection and mating pairs, which significantly impact the ultimate genetic gain of a breeding scheme. The selection of appropriate parents and mating pairs to increase genetic gain while maintaining genetic diversity is still an urgent need that breeders are facing. This study aimed to determine the best progeny allocation strategies by combining future-oriented simulations and numerical black-box optimization for an improved selection of parents and mating pairs. In this study, we focused on optimizing the allocation of progenies, and the breeding process was regarded as a black-box function whose input is a set of parameters related to the progeny allocation strategies and whose output is the ultimate genetic gain of breeding schemes. The allocation of progenies to each mating pair was parameterized according to a softmax function, whose input is a weighted sum of multiple features for the allocation, including expected genetic variance of progenies and selection criteria such as different types of breeding values, to balance genetic gains and genetic diversity optimally. The weighting parameters were then optimized by the black-box optimization algorithm called StoSOO via future-oriented breeding simulations. Simulation studies to evaluate the potential of our novel method revealed that the breeding strategy based on optimized weights attained almost 10% higher genetic gain than that with an equal allocation of progenies to all mating pairs within just four generations. Among the optimized strategies, those considering the expected genetic variance of progenies could maintain the genetic diversity throughout the breeding process, leading to a higher ultimate genetic gain than those without considering it. These results suggest that our novel method can significantly improve the speed and efficiency of variety development through optimized decisions regarding the selection of parents and mating pairs. In addition, by changing simulation settings, our future-oriented optimization framework for progeny allocation strategies can be easily implemented into general breeding schemes, contributing to accelerated plant and animal breeding with high efficiency.

Estimation of genetic parameters for bull conception rate and its genetic correlations with semen production traits in Japanese Black bulls

The P of achieving pregnancy is an important trait of bull fertility in beef cattle and is defined as the bull conception rate (BCR). This study aimed to clarify and better understand the genetic architecture of the BCR calculated using artificial insemination and pregnancy diagnosis records from a progeny testing program in Japanese Black bulls. In this study, we estimated the genetic parameters of the BCR and their correlation with semen production traits. In addition, we assessed the correlated responses in BCR by considering the selection of semen production traits. Nine hundred and sixteen Japanese Black bulls were selected based on fertility, with 28 869 pregnancy diagnostic records from the progeny testing program. Our results showed that the heritability estimate was 0.04 in the BCR at the first service and 0.14 in BCR for the three services, and an increase in the inbreeding coefficient led to a significant decrease in BCR. The phenotypic trend of BCR remained almost constant over the years, whereas the genetic trend increased. In addition, the changes in the progeny testing year effect showed a similar tendency to the phenotypic trends, suggesting that the phenotypic trends could be mainly due to non-genetic effects, including progeny testing year effects. The estimated genetic correlation of BCR with sperm motility traits was favorably moderate to high (ranging from 0.49 to 0.97), and those with sperm quantity traits such as semen volume were favorably low to moderate (ranging from 0.23 to 0.51). In addition, the correlated responses in BCR at the first service by selection for sperm motility traits resulted in a higher genetic gain than direct selection. This study provides new insights into the genetic factors affecting BCR and the possibility of implementing genetic selection to improve BCR by selecting sperm motility traits in Japanese Black bulls.

Combining Genetic and Phenotypic Analyses for Detecting Bread Wheat Genotypes of Drought Tolerance through Multivariate Analysis Techniques.

Successfully promoting drought tolerance in wheat genotypes will require several procedures, such as field experimentations, measuring relevant traits, using analysis tools of high precision and efficiency, and taking a complementary approach that combines analyses of phenotyping and genotyping at once. The aim of this study is to assess the genetic diversity of 60 genotypes using SSR (simple sequence repeat) markers collected from several regions of the world and select 13 of them as more genetically diverse to be re-evaluated under field conditions to study drought stress by estimating 30 agro-physio-biochemical traits. Genetic parameters and multivariate analysis were used to compare genotype traits and identify which traits are increasingly efficient at detecting wheat genotypes of drought tolerance. Hierarchical cluster (HC) analysis of SSR markers divided the genotypes into five main categories of drought tolerance: four high tolerant (HT), eight tolerant (T), nine moderate tolerant (MT), six sensitive (S), and 33 high sensitive (HS). Six traits exhibit a combination of high heritability (>60%) and genetic gain (>20%). Analyses of principal components and stepwise multiple linear regression together identified nine traits (grain yield, flag leaf area, stomatal conductance, plant height, relative turgidity, glycine betaine, polyphenol oxidase, chlorophyll content, and grain-filling duration) as a screening tool that effectively detects the variation among the 13 genotypes used. HC analysis of the nine traits divided genotypes into three main categories: T, MT, and S, representing three, five, and five genotypes, respectively, and were completely identical in linear discriminant analysis. But in the case of SSR markers, they were classified into three main categories: T, MT, and S, representing five, three, and five genotypes, respectively, which are both significantly correlated as per the Mantel test. The SSR markers were associated with nine traits, which are considered an assistance tool in the selection process for drought tolerance. So, this study is useful and has successfully detected several agro-physio-biochemical traits, associated SSR markers, and some drought-tolerant genotypes, coupled with our knowledge of the phenotypic and genotypic basis of wheat genotypes.

Genetic variation, genetic advance, heritability and correlation analysis of phenotypic traits in tetraploid wheat (Triticum turgidum spp.) landraces and some improved cultivars of Ethiopia

AbstractTetraploid wheat species from Ethiopia hold ample genetic variation, which could provide a source for improvement of wheat. A total of 196 Ethiopian tetraploid wheat (Triticum turgidum spp.) accessions, including 174 landraces and 22 improved cultivars, were evaluated at Sinana and Debrezeit to assess morphological variation, genetic advance, heritability and correlation based on 11 phenotypic traits. Except for spike length, highly significant variation (P < 0.001) among genotypes for all traits was observed. The observed mean and range values of the phenotypic traits revealed high variability in the accessions. Phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values were high for grain yield, biomass yield and harvest index. Seed yield showed highly significant (P < 0.001) negative correlation with days to booting and days to maturity and positive correlation with all traits. The estimates of heritability (H2) for grain yield and the number of spikelets per spike respectively ranged from 41.78 to 84.62%. The genetic advance as a percentage of mean was low for the number of seeds per spikelet, days to booting and days to maturity; intermediate for plant height, thousand kernel weight and spike length and high for the number of spikelets per spike, the number of effective tillers per plant, grain yield, biomass yield and harvest index, respectively. The number of spikelets per spike gave a high value of genetic advance and heritability implying high genetic gain from its selection.

Comparison of pooled semen insemination and single colony insemination as sustainable honeybee breeding strategies.

Instrumental insemination of honeybees allows for two opposing breeding strategies. In single colony insemination (SCI), all drones to inseminate a queen are taken from one colony. In pooled semen insemination (PSI), sperm of many genetically diverse drones is mixed and queens are fertilized from the resulting drone pool. While SCI allows for maximum pedigree control, proponents of PSI claim to reduce inbreeding and maintain genetic variance. Using stochastic simulation studies, we compared genetic progress and inbreeding rates in small honeybee populations under SCI and PSI. Four different selection criteria were covered: estimated breeding values (EBV), phenotypes, true breeding values (TBV) and random selection. Under EBV-based truncation selection, SCI yielded 9.0% to 44.4% higher genetic gain than PSI, but had vastly increased inbreeding rates. Under phenotypical or TBV selection, the gap between SCI and PSI in terms of genetic progress narrowed. Throughout, PSI yielded lower inbreeding rates than SCI, but the differences were only substantial under EBV truncation selection. As a result, PSI did not appear as a viable breeding strategy owing to its incompatibility with modern methods of genetic evaluation. Instead, SCI is to be preferred but instead of strict truncation selection, strategies to avoid inbreeding need to be installed.

Heritability of yield and fruit characteristics in Solanum quitoense Lam.

The lulo (Solanum quitoense Lam.) is a fruit tree of great importance for southern Colombia, given its demand and its potential as an exotic fruit in the international market. However, there is no information on variation and heritability, fundamental aspects for evaluating selection. The objective of this research was to estimate the heritability of yield, fruit weight (FW), total soluble solids (TSS) and maturity index (MI) in half-sib families (HSF) of lulo from the first cycle of recurrent selection. Strict sense heritability ( h e 2 ) across four locations in the 50 HSF were low for yield, MI and for FW, while for TSS it was high. The 50 FMH showed a high h e 2 in yield in Arboleda, Cartago, Tangua and La Unión. TSS was high in all four locations. For FW it was moderate in Cartago, Tangua, La Unión and Arboleda. In MI it was high in Tangua and La Unión and low in Arboleda and Cartago. The h e 2 in 10 HSF selected across four locations presented values ​​higher than 50 HSF, with a high value for yield in Arboleda, moderate in Cartago and Tangua and low in La Unión; In FW it was high in Arboleda, Tangua and La Unión, and moderate in Cartago. The results indicate the existence of adequate genetic variance to be able to select and achieve high genetic gain in the traits evaluated in HSF of lulo.

Tomato: Breeding and Genomics

Tomato is an important vegetable of the human diet. In tomatoes, through conventional breeding methods, many cultivars with desirable traits have been developed. With the advancement in sequencing technologies combined with reducing cost per sample, high-throughput genotyping platforms and bioinformatics pipelines have revolutionized tomato improvement. After the tomato genome sequencing in 2012, thousands of cultivated and wild species have been sequenced with respect to studies on population structure, genetic diversity, high-density maps and structural variants analysis so on. Now, genomics-assisted research would aim to discover of QTLs/genes and associated single nucleotide polymorphisms (SNP) markers by genome-wide association studies (GWAS) using high-throughput genotyping (SNP array or genotyping-by-sequencing) for rapid breeding. Moreover, genome editing and genomics selection tools would increase breeding efficiency and higher genetic gain in tomatoes.

Variability and heritability study in some selected Brassica rapa L. genotypes

A field experiment was conducted in the research field of Sher-e-Bangla Agricultural University (SAU), Dhaka, Bangladesh to study variability and heritability in Brassica rapa L. for developing short durable, high yielding varieties. The experiment had laid out in a randomized complete block design with three replications and consisted of seven genotypes viz., G1 (BARI Sarisha-14), G2 (Brown Special), G3 (Yellow Special), G4 (Tori-7), G5 (BARI Sarisha-17), G6 (BARI Sarisha-15) and G7 (BARI Sarisha-6). The result revealed that G7 had the highest yield plant-1 (6.91 g) and longest duration (108.00 days) while G4 had the lowest yield plant-1 (4.12 g) and G2 had the shortest duration (79.33 days). High genotypic and phenotypic coefficient of variation for number of secondary branches plant-1 (95.35% and 99.39%), number of siliqua plant-1 (29.52% and 30.23%), plant height (25.19% and 25.38%) and number of seeds siliqua-1 (26.76% and 27.12%) had estimated. High heritability with high genetic advance and gain had observed for days to 80% maturity (99.92%, 20.99% and 23.36 %), plant height (98.55%, 53.99% and 51.53%) and number of siliqua plant-1 (95.33%, 101.25% and 59.37%). While high heritability with low genetic advance and high genetic gain were observed for number of primary branches plant-1 (92.02%, 0.70% and 188.43%), number of secondary branches plant-1 (92.02%, 7.47% and 188.43%), length of siliqua (98.23%, 1.104% and 29.96), 1000 seed weight (84.61%, 1.23% and 32.01%) and yield plant-1 (97.41%, 2.01% and 38.47%). Days to 80% maturity, plant height and number of siliqua plant-1 showed high heritability with high genetic advance and genetic gain indicated additive gene action and selection could be useful for these traits. While high heritability with low genetic advance had observed for number of primary and secondary branches plant-1, length of siliqua, 1000 seed weight and yield plant-1 indicated non additive gene action and selection might be ineffective for these traits. Bangladesh J. Agri. 2023, 48(2): 106-118

Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance

Key messageSchemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain and less depletion of genetic varianceOne of the most common methods to improve hybrid performance is reciprocal recurrent selection (RRS). Genomic prediction (GP) can be used to increase genetic gain in RRS by reducing cycle length, but it is also possible to use GP to predict single-cross hybrid performance. The impact of the latter method on genetic gain has yet to be previously reported. Therefore, we compared via stochastic simulations various phenotypic and genomics-assisted RRS breeding schemes which used GP to predict hybrid performance rather than reducing cycle length, which allows minimal changes to traditional breeding schemes. We also compared three breeding sizes scenarios that varied the number of genotypes crossed within heterotic pools, the number of genotypes crossed between heterotic pools, the number of hybrids evaluated, and the number of genomic predicted hybrids. Our results demonstrated that schemes that used genomic prediction of hybrid performance outperformed the others for the average interpopulation hybrid population and the best hybrid performance. Furthermore, updating the testers increased hybrid genetic gain with phenotypic RRS. As expected, the largest breeding size tested had the highest rates of genetic improvement and the lowest decrease in additive genetic variance due to the drift. Therefore, this study demonstrates the usefulness of single-cross prediction, which may be easier to implement than rapid-cycling RRS and cyclical updating of testers. We also reiterate that larger population sizes tend to have higher genetic gain and less depletion of genetic variance.

Comparison of genomic prediction models for general combining ability in early stages of hybrid breeding programs

AbstractThis study evaluates the impact of genomic prediction models on selecting inbred lines as parents in hybrid breeding programs. New parents in a hybrid breeding program are typically selected from early‐stage yield trials based on general combining ability (GCA) from testcrosses. Genomic studies have largely focused on predicting hybrid performance in the late stages of the breeding pipeline and largely ignored the selection of inbred lines as parents of the subsequent breeding cycles. Here, we used stochastic simulations of a maize (Zea mays L.) hybrid breeding program for 20 years to evaluate the performance of genomic prediction models for selecting parents based on their predicted GCA. Five genomic prediction models were evaluated in terms of achieved genetic gain and heterosis under two different single nucleotide polymorphism (SNP) marker densities and the true quantitative trait loci genotypes. The results show that using high‐density SNP markers generated more genetic gain and heterosis than the low‐density SNP markers. The relative performance of genomic prediction models differed across marker scenarios. For genetic gain, we observed more differences between the models at low than high marker density. For heterosis, we observed the opposite, more differences between the models at high than low marker density. Overall, models that fitted the average or additive effects specific to each heterotic pool and dominance effects provide a better fit and hence higher genetic gain in hybrid breeding programs.

Genetic variability and correlation studies of yield and yield related attributes in BC2F2 population of sweet corn

The present study was carried out to study the genetic variability, heritability, genetic advance as percent of mean, correlation, skewness, and kurtosis of the backcross population BC2F2 derived from the cross SCM-Se-Sh-2 × DBT 17. High heritability coupled with high genetic advance was observed for cob girth, number of kernels per row, cob weight, 100 grain weight and single plant yield, suggesting additive gene action and selection of progenies based on this trait will result in higher genetic gain. Association studies showed that single plant yield was positively correlated with all yield attributes, viz., cob weight, number of kernels per row, 100 grain weight and plant height. These results depicted that cob weight, numbers of kernels per row and 100 grain weight may be used as reliable criteria for improving grain yield. Single plant yield, 100 grain weight, cob weight and plant height showed positive skewness and platykurtic distribution. This indicates that traits are governed by a large number of genes, and most of the genes exhibited complementary gene action, suggesting rigorous selection to achieve genetic gain. Overall, it is seen that this population has potential for yield improvement with enriched beta-carotene content.

The Potential of Instrumental Insemination for Sustainable Honeybee Breeding.

Mating control is crucial in honeybee breeding and commonly guaranteed by bringing virgin queens to isolated mating stations (IMS) for their nuptial flights. However, most breeding programs struggle to provide sufficiently many IMS. Research institutions routinely perform instrumental insemination of honeybees, but its potential to substitute IMS in breeding programs has not been sufficiently studied. We performed stochastic simulations to compare instrumental insemination strategies and mating on IMS in terms of genetic progress and inbreeding development. We focused on the role of paternal generation intervals, which can be shortened to two years with instrumental insemination in comparison to three years when using IMS. After 70 years, instrumental insemination yielded up to 42% higher genetic gain than IMS strategies-particularly with few available mating sites. Inbreeding rates with instrumental insemination and IMS were comparable. When the paternal generation interval in instrumental insemination was stretched to three years, the number of drone producers required for sustainable breeding was reduced substantially. In contrast, when shortening the interval to two years, it yielded the highest generational inbreeding rates (up to 2.28%). Overall, instrumental insemination with drones from a single colony appears as a viable strategy for honeybee breeding and a promising alternative to IMS.

Genetic Variability and Diversity in Red Onion (Allium cepa L.) Genotypes: Elucidating Morpho-Horticultural and Quality Perspectives

Onion (Allium cepa L.) is a prominent spice and vegetable crop farmed commercially worldwide. Variability is viewed as a key signal for any red onion enhancement effort. The current study was, therefore, carried out to learn about genetic variability and diversity among selected genotypes of 20 red onions at the C Block Farm, Bidhan Chandra Krishi Viswavidyalaya, India, during the winter (rabi) season of 2021–2022, in Randomized Complete Block Design (RCBD) with three replications. The characters, viz., average weight of bulbs (kg), neck thickness (cm), total soluble solids (°Brix), total sugar (%), and reducing sugar (%) demonstrated high heritability (97.38–99.97%) coupled with high genetic gain. Such traits were the least influenced by environmental effects, and additive gene action played a pivotal role in the manifestation of such characters. Traits with high heritability values (51.37–67.94%) demonstrate that the observed variability was under genetic control and provide an enormous range of possibilities for accomplishing selection depending on their phenotypic performances. For traits with moderate heritability, viz., bolting (%) and doubling (%), selection would be less effective but can still be given great importance. Based on correlation analysis, the character’s neck thickness, equatorial diameter, and polar diameter unveiled highly positive genetic correlation with the average weight of bulbs (0.120, 0.112; 0.194, 0.210 and 0.120, 0.112 for phenotypic and genotypic correlation coefficient values, respectively), which indicates that the average weight of a bulb would be increased by an increase in such components. According to path coefficient analysis, the equatorial diameter exhibited the most positive direct effect on the average weight of bulbs (0.968), followed by polar diameter (0.687) and neck thickness (0.159). A wide range of variations for qualitative traits, including foliage colour, leaf width, foliage behaviour, the degree of leaf waxiness, the shape of the bulb, and bulb skin colour were observed. Based on Mahalanobish D2 analysis, the genotypes were divided into four clusters. The highest number of genotypes was found in cluster I (eleven), followed by cluster IV (six genotypes) and cluster II (two genotypes). Cluster III had a single genotype and was monogenic. The study confirmed that a wide genetic variation prevailed in the onion genotypes taken under study, which could thereby be utilized in breeding programmes.