Improve Breeding Efficiency Research Articles

Genome Scan Analysis for Advancing Knowledge and Conservation Strategies of Primitivo Clones (Vitis vinifera L.)

The success of the Primitivo variety underscores the critical need for the managing of clone genetic conservation, utilization, and improvement. By combining genomic and environmental data, breeders can better predict the performance of varieties, thereby improving breeding efficiency and enabling more targeted development of high-quality grapevine cultivars. In this study, 35 Primitivo clones were analysed, including selected and certified clones that have been propagated over several years in Apulia. Genetic variability among the Primitivo clones was assessed through genotyping by sequencing. Using 38,387 filtered SNPs, pairwise identity-by-state (IBS) analysis demonstrated the uniqueness of the 35 clones (IBS < 0.75), indicating a high degree of variability among the samples. Genetic diversity analysis revealed three primary groups, which were differentiated based on geographic origin. The clones from Gioia del Colle were grouped into two distinct clusters, which aligns with the observed variation in grape-related traits. The fixation index (FST > 0.50) identified numerous loci putatively associated with stress responses and developmental traits, including genes involved in key plant biological processes, stress response regulation, and adaptation to environmental conditions such as glutamate receptors, auxin, and ethylene signalling.

Research Progress and Prospects of Molecular Breeding in Bermudagrass (Cynodon dactylon).

Bermudagrass (Cynodon dactylon L.) is a warm-season grass species of significant ecological and economic importance. It is widely utilized in turf management and forage production due to its resilience to drought, salt, and other environmental stresses. Recent advancements in molecular breeding, particularly through genomics technology and gene editing, have enabled the efficient identification of key genes associated with stress tolerance and turf quality. The use of techniques such as overexpression and CRISPR/Cas has enhanced resistance to drought, salt, cold, and heat, while the application of molecular markers has accelerated the development of superior varieties. The integration of multi-omics, such as genomics, transcriptomics, and proteomics, provides deeper insights into the molecular mechanisms of bermudagrass, thereby improving breeding efficiency and precision. Additionally, artificial intelligence is emerging as a powerful tool for analyzing genomic data, predicting optimal trait combinations, and accelerating breeding processes. These technologies, when combined with traditional breeding methods, hold great potential for optimizing bermudagrass varieties for both turf and forage use. Future research will focus on further integrating these tools to address the challenges of breeding posed by climate change to breeding climate-resilient turf and forage crops.

High temperature exposure causes sexual dimorphism in immune responses against largemouth bass ranavirus (LMBV) in Micropterus salmoides

High temperature exposure causes sexual dimorphism in immune responses against largemouth bass ranavirus (LMBV) in Micropterus salmoides

Improving Breeding Efficiency of Local Population of Black Soldier Fly (Hermetia Illucens) (Stratiomyidae: Diptera) by Crossing with a Distant Thrissur Population and Evaluation of the Progeny

Improving Breeding Efficiency of Local Population of Black Soldier Fly (Hermetia Illucens) (Stratiomyidae: Diptera) by Crossing with a Distant Thrissur Population and Evaluation of the Progeny

Research on Key Technologies of Smart Breeding Platform Based on 5G

Abstract In modern animal husbandry, the application of 5G technology opens a new era of farming management, especially in intelligent farming. The high-speed and low-latency communication characteristics make remote monitoring, data transmission, and thoughtful decision-making possible, significantly improving breeding efficiency and management. It has great potential for monitoring animal health, preventing and controlling diseases, and improving production efficiency. This paper explores the application of 5G technology in an intelligent farming management platform and its key technologies. By analyzing the needs of smart farming, we clarify the key application areas of 5G technology. To identify sick pigs, measure their weight accurately using binocular vision technology, and combine with machine learning algorithms, the YOLO v3 algorithm is utilized. The accuracy of sick pig identification based on YOLO v3 reaches 98%, the error of pig weight measurement is controlled within ±2%, and the real-time data transmission and processing realized by 5G technology significantly improves the efficiency of disease prevention and control.5G technology can effectively support the efficient operation of the intelligent farming platform, which is of great significance to enhance the level of farming management and promote the sustainable development of the animal husbandry industry.

Detection and molecular typing of epidemic Brucella strains among camels, sheep, and cattle in Xinjiang, China.

Brucellosis is a zoonotic disease that can result in symptoms including infertility, abortion, testicular inflammation, and arthritis in affected sheep and cattle. The disease can spread through a range of mechanisms, making outbreaks difficult to control such that affected farms often suffer severe economic losses. In addition, humans can be affected by brucellosis, and the number of cases continues to rise annually. As rates of brucellosis in Xinjiang, China have been increasing substantially in recent years, this study was developed to assess brucellosis seroprevalence among herds of cattle, sheep, and camels in Xinjiang through the use of common diagnostic procedures like the Rose Bengal test (RBT) and PCR. A cross-sectional approach was used to analyze the seroprevalence of brucellosis across 720 total farm animals (320 camels, 250 sheep, and 150 cattle). RBT incidence rate for brucellosis was detected in 60 serum samples, 14 (4.38%) from camels, 45 (18%) from sheep, and 1 (0.67%) from cattle. PCR was performed as a confirmatory approach for these RBT-positive samples, with 55 ultimately being confirmed to be positive 13 (4.06%), 41 (16.4%), and 1 (0.67%) samples from camels, sheep, and cattle, respectively. In this survey, sheep exhibited the highest brucellosis seroprevalence using these two analytical techniques, while cattle exhibited the lowest seroprevalence and camels exhibited an intermediate rate. AMOS-PCR analyses identified Brucella melitensis as the unknown bacterium in some of these samples. These results offer new insight regarding brucellosis seroprevalence among farm animals that can be used to formulate more appropriate prevention and control policies, while also improving awareness of epidemic prevention efforts, the need for routine quarantine and disinfection, the benefits of scientific breeding and management, and approaches to improving breeding efficiency for the camel, cattle, and sheep industries.

Role of Eruca sativa L. seeds in boosting the reproductive performance of male Japanese quails (Coturnix c. japonica).

Herein we attempt to shed light on the potential improving effect of Eruca sativa seeds (ESS) on the reproductive aspects of male Japanese quails. To accomplish this objective, two groups of quails were supplemented with ESS powder at doses of 5 and 10 g/kg feed from 7 days to 140 days of age, in addition to the control group, which did not receive treatment. Forty males were reared singly in cages to evaluate sperm characters and 32 males were raised with 64 females to evaluate fertility and sperm penetrability. Sixty-six phytochemical compounds were found according to gas chromatography-mass spectrometry analysis of ESS. The most plentiful ones are 13-docosenoic acid methyl ester, 9-octadecenoic acid methyl ester, and linoleic acid methyl ester. Both 5 g/kg and 10 g/kg doses of ESS showed similar effectiveness in enhancing various reproductive parameters, including gonadal index, sperm characteristics, fertility, libido, and cloacal gland attributes. However, some aspects like sperm concentration and testosterone levels exhibited a dose-dependent response. There is no significant change in mortality rate of supplemented groups compared to the control one. ESS also caused a reduction in feed intake and an enhancement in feed conversion ratio without affecting final body weight and body weight gain. This suggests potential nutritional benefits beyond reproductive health. The low-dose-fed group showed a significant reduction in total cholesterol and malondialdehyde compared to the high-dose-fed and unfed groups. The higher dose notably increased total antioxidant capacity compared to the lower dose and control group. Despite the positive effects on male reproductive parameters, there wasn't a significant impact on hatchability percentage, indicating that while male fertility improved, it might not have directly affected the viability of the eggs. Overall, the study suggests that ESS could be a safe and promising addition to the diet of male Japanese quails to enhance their reproductive capabilities without adverse effects. The findings could have implications for poultry farming by potentially improving breeding efficiency and health outcomes in quails.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Key Determinants of the Physiological and Fruit Quality Traits in Sweet Cherries and Their Importance in a Breeding Programme

Australia produces high-quality sweet cherries and generates revenue from local and export markets. Due to increased demand in the markets, the area of sweet cherry production has increased in Australia. Sweet cherry breeding and production have challenges such as self-incompatibility genotypes and phenotyping of agronomic, physiological, and quality traits. Understanding these traits and their interaction with environmental factors would increase production and provide better economic returns for the industry. This review paper covered the challenges of current sweet cherry production, breeding efforts, the basis for understanding of plant traits, the influence of environmental factors on the traits, and opportunities for new sweet cherry breeding in the future. The period of flowering and maturity along with firmness of the fruit are key traits in cherry production. Breeding techniques such as haplotype breeding will contribute to improving breeding efficiency and deliver better cultivars of sweet cherry.

Development and validation of functional markers (Tetra-primer ARMS and KASP) for the bacterial blight resistance gene xa5 in rice

Functional markers, which are designed using polymorphic sites in gene sequences and which result in phenotypic variation, have high efficiency in marker-assisted selection (MAS). xa5 is a recessive gene that confers broad-spectrum resistance to bacterial blight, and it has been widely used in rice breeding projects in all tropical regions. In this study, two functional markers [Tetra primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR) and kompetitive allele specific PCR (KASP)] were developed based on the variation of two bases in the coding region of the xa5 allele. The specificity and applicability of the two functional markers were verified in a breeding segregating population and a rice micro-core germplasm resource population. We conclude that these two newly-developed functional markers can effectively determine the homozygosity and heterozygosity of the target gene under different laboratory conditions. Thus, they can be used for genotyping the xa5 gene in molecular breeding programmes, thereby improving breeding efficiency.

Evidence of epistatic suppression of repeat fruiting in cultivated strawberry

BackgroundConsumers purchase fresh strawberries all year long. Extending the fruiting season for new strawberry cultivars is a common breeding goal. Understanding the inheritance of repeat fruiting is key to improving breeding efficiency. Several independent research groups using multiple genotypes and analytic approaches have all identified a single genomic region in strawberry associated with repeat fruiting. Markers mapped to this region were used to evaluate breeding parents from the United States Department of Agriculture – Agricultural Research Service (USDA-ARS) strawberry breeding program at Beltsville, Maryland.ResultsMarkers mapped to repeat fruiting identified once-fruiting genotypes but not repeat-fruiting genotypes. Eleven of twenty-three breeding parents with repeat-fruiting marker profiles were actually once fruiting, indicating at least one additional locus acting epistatically to suppress repeat fruiting. Family segregation ratios could not be predicted reliably by the combined use of parental phenotypes and marker profiles, when using a single-gene model. Expected segregation ratios were calculated for all phenotypic and marker-profile combinations possible from the mapped locus combined with a hypothetical dominant or recessive suppressor locus. Segregation ratios specific to an epistatic suppressor acting on the mapped locus were observed in four families. The segregation ratios for two families were best explained by a dominant suppressor acting on the mapped locus, and, for the other two, by a recessive suppressor. Not all of the observed ratios could be explained by one model or the other, and when multiple families with a common parent were compared, there was no predicted genotype for the common parent that would lead to all of the observed segregation ratios.ConclusionsConsidering all lines of evidence in this study and others, repeat-fruiting in commercial strawberry is controlled primarily by a dominant allele at a single locus, previously mapped by multiple groups. At least two additional genes, one dominant and one recessive, exist that act epistatically to suppress repeat fruiting. Environmental effects and/or incomplete penetrance likely affect phenotype through the suppressor loci, rather than the primary mapped locus. One of the dominant suppressors acts only in the first year, the year the plant is germinated from seed, and not after the plant has experienced a winter.

Improving Breeding Efficiency of a Hybrid Maize Breeding Program Using a Three Heterotic‐Group Classification

Core Ideas Maize breeding efficiency can be greatly improved by adopting three heterotic groups in hybrid breeding. Using three heterotic groups improves maize breeding efficiency for using genetic resources. General breeding efficiency is used to measure efficiency of genetic resource usage, and specific breeding efficiency is to obtain maximum output with inputs. Suwan1 is an important heterotic group from tropical/subtropical and should be explore more worldwide. Heterotic group classification has a crucial impact on maize (Zea mays L.) breeding efficiency in a hybrid‐based breeding program. The objectives of this study were to: (i) investigate whether or not breeding efficiency could be improved using a three heterotic‐group (TriHG) classification (Reid and non‐Reid, and Suwan1 heterotic groups) system instead of a usual two heterotic‐group (DiHG) classification (Reid and non‐Reid heterotic groups) system; and (ii) estimate the impact of TriHG and DiHG systems on breeding efficiency, utilizing the same data in computing specific breeding efficiency (SBE) and general breeding efficiency (GBE) in a subtropical breeding program in southern China. Twenty‐five adapted tropical and subtropical lines were crossed to six testers using a line × tester mating design. Data on grain yield were used to calculate SBE and GBE for comparing DiHG‐ and TriHG‐based strategies. The TriHG classification system increased GBE by 77.8% over the DiHG system without a significant loss in SBE. We concluded that the TriHG system was better than the DiHG system for improving maize‐breeding efficiency. Therefore, maize breeders may re‐think their breeding strategy for improving breeding efficiency in long‐term breeding programs by adopting the suggested TriHG system. Hybrid maize improvement programs, especially in the early stages of breeding for identifying hybrids with high yield potential, can be become more efficient by using three testers with one from each of Reid, nonReid, and Suwan1 heterotic groups. This would improve the chances of developing high‐yielding hybrids in a breeding program with the available, diverse germplasm.

Genome-Wide Association and Prediction of Grain and Semolina Quality Traits in Durum Wheat Breeding Populations.

Grain yield and semolina quality traits are essential selection criteria in durum wheat breeding. However, high phenotypic screening costs limit selection to relatively few breeding lines in late generations. This selection paradigm confers relatively low selection efficiency due to the advancement of undesirable lines into expensive yield trials for grain yield and quality trait testing. Marker-aided selection can enhance selection efficiency, especially for traits that are difficult or costly to phenotype. The aim of this study was to identify major quality trait quantitative trait loci (QTL) for marker-assisted selection (MAS) and to explore potential application of genomic selection (GS) in a durum wheat breeding program. In this study, genome-wide association mapping was conducted for five quality traits using 1184 lines from the North Dakota State University (NDSU) durum wheat breeding program. Several QTL associated with test weight, semolina color, and gluten strength were identified. Genomic selection models were developed and forward prediction accuracies of 0.27 to 0.66 were obtained for the five quality traits. Our results show the potential for grain and semolina quality traits to be selected more efficiently through MAS and GS with further refinement. Considerable opportunity exists to extend these techniques to other traits such as grain yield and agronomic characteristics, further improving breeding efficiency in durum cultivar development.

Improving breeding efficiency through application of appropriate experimental designs and analysis models: A case of lentil (Lens culinaris Medikus subsp. culinaris) yield trials

Abstract Lentil (Lens culinaris Medikus subsp. culinaris) is an important staple pulse and rich source of protein, especially to the economically resource-poor consumers of the developing world. Experimental and analytic technology and statistical tools are needed to enhance lentil breeding progress. One of the concerns of field experimentation is to design experiments in suitable block designs and model the data to account for any left-over trend in the field layout and for correlations in the plot errors. Elite breeding lines of lentil developed through conventional breeding methods at ICARDA were evaluated in three contrasting environments in northern Syria and Lebanon during 1999–2005. This study examines the data on seed and straw yields from 226 trials conducted in randomized complete block (RCB) and in square lattice designs. Suitable models incorporating blocking structures, linear trends and spatially correlated plot-errors were fitted to the individual datasets. The results indicated that the spatial analysis model, which accounts for the spatial pattern of the field, was better than the commonly used RCB design model. The spatial analyses gave substantial increases in precision of predicted means for the genotypes. An average efficiency of pairwise genotype means comparison over RCB was 141% for seed yield and 158% for straw yield from the trials conducted in incomplete blocks and where found superior to RCB. It also enhanced estimates of broad sense heritability on mean-basis, with an average of 72% for seed and 70% for straw yield under the superior models, compared to 62 and 55% for RCB model, respectively. The percentage genetic gain due to selection at 10% intensity was 26% for seed and 20% for straw yield based on those models, which were 2–3% higher than those from the RCB model. In general, it is recommended to continue the use of incomplete block designs for variety trials in lentils and use the most suitable spatial pattern for statistical analysis to assist field crop breeders to enhance precision in selection of desirable genotypes. These results are consistent with findings of a number of other variety trials in lentil.

Improving breeding efficiency in potato using molecular and quantitative genetics.

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.