Search Results (242)

Cowpea (Vigna unguiculata (L.) Walp.) is a legume valued in several countries for its nutritional quality, low input requirements, and economic profitability. However, cowpea productivity is significantly constrained by anthracnose disease caused by Colletotrichum species. Enhancing host resistance through the introgression of resistance alleles from landraces and wild relatives offers a promising strategy for durable disease management. This study evaluated 20 cowpea landraces and 18 V. unguiculata ssp. dekindtiana accessions for resistance to anthracnose under natural field infection. The cultivars Ife Brown and V. vexillata line TVNu-428 were included as susceptible and resistant checks, respectively. The experiment was laid in an alpha lattice design (8 × 5) with three replications arranged. Anthracnose symptoms characterized by enlarged light-brown lesions surrounded by reddish-brown halos were produced on all the accessions and the symptoms progressed throughout the assessment period. Five V. unguiculata ssp. dekindtiana accessions (TVNu-113, TVNu-1506, TVNu-1222, TVNu-420, and TVNu-136) and three cowpea landrace accessions (TVu-14076, TVu-17556, and TVu-17567) were identified as promising sources of anthracnose resistance. These accessions represent valuable genetic resources for broadening the cowpea resistance gene pool and support the strategic utilization of wild cowpea germplasm in breeding programs. Full article

Dezhou donkey is a premium indigenous Chinese livestock breed with high economic value for meat, hide and medicinal uses, and growth rate is a core trait determining farming profitability. However, the molecular and metabolic mechanisms underlying divergent growth rates in this breed have not been fully characterized, with no integrated transcriptomic and metabolomic studies reported. Here, 12 age-matched healthy male Dezhou donkeys were assigned to faster-growing (n = 6) and slower-growing (n = 6) groups by average daily gain, followed by plasma transcriptome sequencing and untargeted LC-MS/MS metabolomics. We identified 480 differentially expressed genes, with the slower-growing group enriching in immune/inflammatory/apoptotic pathways, and the faster-growing group in energy metabolism and transmembrane transport. Lipids and lipid-like molecules represented the largest proportion (44.9%) of the differential metabolites; the slower-growing group was enriched in lipid peroxidation and pro-inflammatory mediators, while the faster-growing group was enriched in unsaturated fatty acids and antioxidants. Integrated analysis revealed core pathways (cAMP signaling, arachidonic acid/unsaturated fatty acid biosynthesis) and key candidate genes/metabolites. Our findings clarify that excessive lipid peroxidation and inflammatory imbalance restrict growth, while efficient energy metabolism promotes faster growth, providing theoretical support for genetic improvement and precision nutrition of Dezhou donkeys. Full article

Alpacas have become increasingly popular as farm and companion animals in many countries and were introduced in Hungary approximately 15 years ago. However, reliable data on their population size and management practices have remained limited. Therefore, this study aimed to provide the first nationwide overview of alpaca keeping in Hungary. An anonymous Google Forms-based questionnaire comprising 55 questions was used to collect data on farm characteristics, herd size, husbandry practices, and animal health management. A total of 53 valid responses were analyzed. The results indicated that approximately 260 alpacas are currently kept in Hungary, with most herds being small and typically consisting of 1–5 animals. Most owners planned to expand their herds, primarily through domestic breeding or purchases; however, only a minority considered alpaca keeping economically profitable. Responses related to quarantine, veterinary access, and disease management suggested limited knowledge of biosecurity and animal health. While most owners reported high levels of trust in veterinarians, many had difficulty accessing specialists with expertise in alpacas. In conclusion, alpaca keeping in Hungary is a growing but still small-scale sector. Improving owner education and strengthening professional support may enhance animal welfare and reduce health risks, thereby supporting the One Health approach. Full article

Climate change threatens crop yields and farming profitability, especially in drought-prone regions, requiring a transition to climate-resilient farming systems. Concurrently, growing demand for health-promoting and bio-based materials is creating new market opportunities for farmers. Sulla (Sulla coronaria Medik; syn. Hedysarum coronarium L.), a Mediterranean forage crop, may represent a strategic resource for sustainable intensification by simultaneously providing high-value commodities and a wide range of ecosystem services. This review explores the multifunctional potential of sulla following a holistic approach and is structured in thematic chapters, exploring: i. agronomy, ii. ecosystem services and agroecological value, iii. plant biochemical profile, iv. emerging applications for the bio-based industry, v. genetic diversity (including rhizobia diversity) and breeding perspectives for target environments and end-use. A SWOT analysis synthesizes strengths, research gaps and bottlenecks hindering large-scale adoption and valorization. The review proposes a strategic framework matching research priority with specific, actionable goals. The review aims to increase awareness of the multifaceted value of sulla as a promising model legume to increase sustainability in agriculture, promote product diversification and farming profitability, while assuring important ecosystem benefits. Full article

Reproductive traits are critical for improving productivity and profitability in the pig industry, and genome-wide association studies (GWASs) are a powerful tool in detecting genetic markers related to target traits. Genome imputation provides an effective approach to obtain a greater number of genetic markers from low-density sequencing data. China’s pig industry recently introduced an imputation panel and is now seeking to determine what types of data are required to meet breeding needs. In this study, we collected and analyzed two pig sequencing datasets, including Yorkshire pig (YY), Landrace pig (LL), and Duroc pig (DD), genotyped by either an SNP chip (n = 816) or genotyping-by-targeted sequencing (n = 314), and applied an imputation strategy before validation in a third dataset (n = 2401). The aim of this study was to identify SNPs associated with reproductive traits and compare imputation results of two different types of data to evaluate whether sample size or marker density more strongly impacts imputation-enabled GWAS performance. Through a GWAS, we identified 73 significant SNPs from imputed Chip data across seven reproductive traits, 94 SNPs from imputed GBTS data across three traits, and 34 SNPs from the combined dataset across seven traits. Seven of these SNPs passed validation and were associated with number born alive, number born healthy, and gestation length. Gestation length (GL) and number born alive (NBA) are the most noteworthy traits. LOXL2 and PTPRD are high-confidence candidate genes affecting GL and NBA, respectively. In addition to LOXL2, STC1, NKX2-6, HMGCLL1, MLIP, TINAG, FAM83B, GFRAL, HCRTR2, ENTPD4, MYH8, IER5L, and U5 are associated with GL. Moreover, in addition to PTPRD, KLHL32, U6, MMS22L, and FHL5 are associated with NBA. The results of this study indicate that sample size is of greater importance than marker density in imputation strategies and provide beneficial insights into genes affecting pigs’ reproductive traits. Full article

Feeding behavior in cattle affects feed efficiency, which is important for increasing the profitability of production while simultaneously reducing the environmental impact. Over a six-year period, indigenous beef cows (Afrikaner, Bonsmara, Nguni) were crossed with indigenous and exotic (Angus, Simmental) sires in a hot and arid area, to produce 15 breed groups. After weaning, the bull calves were fed in a feedlot setting wherein daily feed intake and partial body weight were measured. The serial correlations of daily feed intake and partial body weight on consecutive days were estimated for each animal. Analyses of variance for the z-transformed serial correlations of daily feed intake and partial body weight were conducted. The linear model included the fixed effect of test group comprising pen and date at the beginning of the test and a fixed breed group effect. The average serial correlation of daily feed intake (r = 0.10) was interpreted to suggest that a test period of 36 days was sufficient to achieve 80% average accuracy for the animals being tested. The average serial correlation of partial body weight was very high (r = 0.94). Thus, there seems little need to average values over days to achieve an accurate estimate of the weight of an animal at any specific point in time. Variation among animals in the serial correlation of daily feed intake indicates differences in feeding behavior over time, but this variability was not related to breed composition. The results indicate that a test period of 36 days is sufficient to achieve 80% accuracy of the mean for daily feed intake of the animals being tested. Full article

The sustainability of the beef and dairy industry requires a systems approach that integrates environmental stewardship, social responsibility, and economic viability. Over the past two decades, global genetics consortia have advanced data-driven germplasm programs (breeding and conservation programs focusing on genetic resources) to enhance sustainability across cattle systems. These initiatives employ multi-trait selection indices aligned with consumer demands and supply chain trends, targeting production, longevity, health, and reproduction, with outcomes including greenhouse gas mitigation, improved resource efficiency and operational safety, and optimized animal welfare. This study analyzes strategic initiatives, germplasm portfolios, and data platforms from leading genetics companies in the USA, Europe, and Brazil. US programs combine genomic selection with reproductive technologies such as sexed semen and in vitro fertilization to accelerate genetic progress. European efforts emphasize resource efficiency, welfare, and environmental impacts, while Brazilian strategies focus on adaptability to tropical conditions, heat tolerance, and disease resistance. Furthermore, mathematical models and decision support tools are increasingly used to balance profitability with environmental goals, reducing sustainability trade-offs through data-driven resource allocation. Industry-wide collaboration among stakeholders and regulatory bodies underscores a rapid shift toward sustainability-oriented cattle management strategies, positioning genetics and technology as key drivers of genetically resilient and sustainable breeding systems. Full article

This study analyzes the provisioning strategy of the European Scops Owl (Otus scops) via continuous video monitoring of a breeding pair in a peri-urban Mediterranean forest in NE Spain (n = 724 deliveries). Invertebrates dominated numerically, with Orthoptera constituting 64.6%. Although vertebrates were scarce (1.8%), they contributed disproportionately to total biomass (20.8%), with rodents alone accounting for 20.3% of delivered energy. Parental effort followed a bimodal nocturnal rhythm, peaking at darkness onset (22:00 h) and before dawn. Crucially, we found a significant predation bias towards female orthopterans (65.6% vs. 34.3%; p < 0.001). While driven by Meconema thalassinum, selection in larger species like Tettigonia viridissima evidences a strategy focused on biomass profitability. Since Ensifera biomass scales allometrically (W $~ L^{2.797}$), selecting females yields disproportionate energetic gains. We also report the systematic removal of ovipositors prior to delivery, a behavior that optimizes intake but renders high-value females undetectable in traditional pellet analyses. These results suggest O. scops exploits artificial light sources (“streetlight traps”) to maximize foraging efficiency. Full article

Dairy cow longevity is a key driver of farm profitability, animal welfare, and environmental sustainability. Despite genetic progress in milk production, the average herd life has declined in many high-yielding dairy systems, raising concerns about early culling. This study analyzed data from 2057 Holstein–Friesian cows in Hungary to characterize the distribution and timing of culling events and to identify major risk factors affecting productive lifespan. We studied age, parity, milk yield, and culling reason using descriptive statistics, Kruskal–Wallis tests, multinomial logistic regression, and Kaplan–Meier survival analysis. Udder health problems were found to be the most frequent cause of culling (22.8%), followed by metabolic disorders (18.2%), locomotive problems (17.3%), and reproductive disorders (17.1%). Economic reasons such as low milk production contributed to a smaller proportion of culling. Most cows were culled after the second or third lactation, with survival probability dropping sharply within the first 1500–2000 days of life. Cows reaching four or more lactations represented a small but economically and genetically valuable subset of the herd. Our results indicated that in Hungary culling decisions are largely determined by health problems, which represent a greater limitation to the productive potential of dairy cows than economic factors. This research recommends that breeding programs prioritize genetic selection for robustness and that herd management adopts preventive health and reproductive strategies to prolong cow longevity, ultimately enhancing the efficiency and sustainability of dairy production systems. Additionally, prevention of animal wastage to foster animal welfare could be suggested as an additional advantage. Full article

Maize (Zea mays L.) silage’s forage quality significantly impacts dairy animal performance and the profitability of the livestock industry. Recently, using uncrewed aerial vehicles (UAVs) equipped with advanced sensors has become a research frontier in maize high-throughput phenotyping (HTP). However, extensive existing studies only consider a single sensor modality and models developed for estimating forage quality are single-task ones that fail to utilize the relatedness between each quality trait. To fill the research gap, we propose MUSTA, a MUlti-Sensory feature fusion model that utilizes MUlti-Task learning and the Attention mechanism to simultaneously estimate dry matter yield and multiple nutritive values for silage maize breeding hybrids in the field environment. Specifically, we conducted UAV flights over maize breeding sites and extracted multi-temporal optical- and LiDAR-based features from the UAV-deployed hyperspectral, RGB, and LiDAR sensors. Then, we constructed an attention-based feature fusion module, which included an attention convolutional layer and an attention bidirectional long short-term memory layer, to combine the multi-temporal features and discern the patterns within them. Subsequently, we employed multi-head attention mechanism to obtain comprehensive crop information. We trained MUSTA end-to-end and evaluated it on multiple quantitative metrics. Our results showed that it is capable of practical quality estimation results, as evidenced by the agreement between the estimated quality traits and the ground truth data, with weighted Kendall’s tau coefficients (τ_w) of 0.79 for dry matter yield, 0.74 for MILK2006, 0.68 for crude protein (CP), 0.42 for starch, 0.39 for neutral detergent fiber (NDF), and 0.51 for acid detergent fiber (ADF). Additionally, we implemented a retrieval-augmented method that enabled comparable prediction performance, even without certain costly features available. The comparison experiments showed that the proposed approach is effective in estimating maize silage yield and nutritional values, providing a digitized alternative to traditional field-based phenotyping. Full article

Chlorogenic acid (CGA)-rich extracts from Eucommia ulmoides Oliver (CAE) are known for their gut health and antioxidant benefits in livestock. This study examines the effects of CAE supplementation during the peri-implantation period on sow reproductive performance and the gut microbiota. Sixty Dongliao black sows were randomized to receive either no supplementation (control) or CAE at 600 or 2000 mg/kg daily from gestation day −5 through day 15. High-dose CAE intake significantly increased total antioxidant capacity (T-AOC), superoxide dismutase (SOD), catalase (CAT), immunoglobulin A (IgA), and immunoglobulin M (IgM) levels in sow serum but decreased malondialdehyde (MDA) levels. Fecal short-chain fatty acids (SCFAs) also increase significantly. These changes correlate with improved reproductive performance, including a larger litter size, higher numbers of live-born piglets, a greater individual birth weight of live-born piglets, a higher total litter birth weight of live-born piglets, and a lower mortality rate. 16S rRNA sequencing of the fecal microbiota revealed that CAE markedly altered microbial diversity and composition, reducing the abundance of potentially harmful bacteria but increasing the abundance of beneficial bacteria. In conclusion, supplementation with CAE during the peri-implantation phase can reduce oxidative stress, alter the gut microbiota composition, and improve sow reproductive performance, thus potentially increasing breeding farm profitability. Full article

This review synthesizes advances in livestock genomics by examining the interplay between candidate genes, molecular markers (MMs), signatures of selection (SSs), and quantitative trait loci (QTLs) in shaping economically vital traits across livestock species. By integrating advances in genomics, bioinformatics, and precision breeding, the study elucidates genetic mechanisms underlying productivity, reproduction, meat quality, milk yield, fibre characteristics, disease resistance, and climate resilience traits pivotal to meeting the projected 70% surge in global animal product demand by 2050. A critical synthesis of 1455 peer-reviewed studies reveals that targeted genetic markers (e.g., SNPs, Indels) and QTL regions (e.g., IGF2 for muscle development, DGAT1 for milk composition) enable precise selection for superior phenotypes. SSs, identified through genome-wide scans and haplotype-based analyses, provide insights into domestication history, adaptive evolution, and breed-specific traits, such as heat tolerance in tropical cattle or parasite resistance in sheep. Functional candidate genes, including leptin (LEP) for feed efficiency and myostatin (MSTN) for double-muscling, are highlighted as drivers of genetic gain in breeding programs. The review underscores the transformative role of high-throughput sequencing, genome-wide association studies (GWASs), and CRISPR-based editing in accelerating trait discovery and validation. However, challenges persist, such as gene interactions, genotype–environment interactions, and ethical concerns over genetic diversity loss. By advocating for a multidisciplinary framework that merges genomic data with phenomics, metabolomics, and advanced biostatistics, this work serves as a guide for researchers, breeders, and policymakers. For example, incorporating DGAT1 markers into dairy cattle programs could elevate milk fat content by 15-20%, directly improving farm profitability. The current analysis underscores the need to harmonize high-yield breeding with ethical practices, such as conserving heat-tolerant cattle breeds, like Sahiwal. Full article

Reproductive efficiency is a critical determinant of productivity and profitability in sheep farming. Traditional selection methods have largely relied on phenotypic traits and historical reproductive records, which are often limited by subjectivity and delayed feedback. Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. This review synthesizes the current research on AI-powered behavioral monitoring tools and proposes a conceptual model, ReproBehaviorNet, that maps age- and sex-specific behaviors to biological processes and AI applications, supporting real-time decision-making in both intensive and semi-intensive systems. The integration of accelerometers, GPS systems, and computer vision models enables continuous, non-invasive monitoring, leading to earlier detection of reproductive events and greater breeding precision. However, the implementation of such technologies also presents challenges, including the need for high-quality data, a costly infrastructure, and technical expertise that may limit access for small-scale producers. Despite these barriers, AI-assisted behavioral phenotyping has the potential to improve genetic progress, animal welfare, and sustainability. Interdisciplinary collaboration and responsible innovation are essential to ensure the equitable and effective adoption of these technologies in diverse farming contexts. Full article

Citrus fruit are well-known for their characteristic flavour and nutritional value. Global citrus production has increased by 528% between 1961 and 2021, and in Australia, citrus is the most exported fresh fruit product by volume. There are six described Citrus species endemic to Australia: C. australasica (Australian finger lime), C. australis (round lime), C. garrawayi (Mount White lime), C. glauca (desert lime), C. gracilis (Humpty Doo lime), and C. inodora (Russell River lime). Australian Citrus possess unique flavours, aromas, and phytochemical profiles, suggesting a potential use as novelty crops and/or ‘functional foods’. Furthermore, the native Australian Citrus germplasm is a valuable source of desirable traits in citrus breeding, including drought, cold, heat, salinity, and disease resistance. These may help solve some challenges facing citrus growers globally, including disease, a declining soil quality, changing climates, and narrowing profit margins. However, many Australian citrus species’ nutritional value, chemical composition, and bioactive properties remain unknown. This review focuses on these under-investigated native Citrus species, their distribution, production, physiology, disease tolerance, traditional use, taxonomy, flavour, nutritional composition, bioactivity, and commercial production. It concludes with a perspective on the future of these native species in the Australian and global citrus context. Full article

Sheep wool is a natural fiber from various sheep breeds, mainly used in clothing for its insulation properties. It makes up a small share of global fiber production, which is declining as synthetic fibers replace wool and meat farming becomes more profitable. Wool from slaughter sheep, often unsuitable for textiles, is treated as biodegradable waste. The aim of the study was to develop a fully biodegradable composite of natural origin from a polylactide (PLA) matrix reinforced with sheep wool and to select the optimal modifications (chemical) of sheep wool fibers to obtain modified properties, including mechanical properties. The behavior of the composites after exposure to aging conditions simulating naturally occurring stimuli causing biodegradation and thus changes in the material’s performance over its lifespan was also examined. Dynamic thermal analysis was used to describe and parameterize the obtained data and their variables, and the mechanical properties were investigated. The research culminated in a microscopic analysis along with changes in surface properties. The study demonstrated that wool-reinforced composites exhibited significantly improved resistance to UV degradation compared to pure PLA, with samples containing 15% unmodified wool showing a 54% increase in storage modulus at 0 °C after aging. Chemical modifications using nitric acid, iron compounds, and tar were successfully implemented to enhance fiber–matrix compatibility, resulting in increased glass transition temperatures and modified mechanical properties. Although wool fiber is not a good choice for modifications to increase mechanical strength, adding wool fiber does not improve mechanical properties but also does not worsen them much. Wool fibers are a good filler that accelerates degradation and are also a waste, which reduces the potential costs of producing such a biocomposite. The research established that these biocomposites maintain sufficient mechanical properties for packaging applications while offering better environmental resistance than pure polylactide, contributing to the development of circular economy solutions for agricultural waste valorization. So far, no studies have been conducted in the literature on the influence of sheep wool and its modified versions on the mechanical properties and the influence of modification on the degradation rate of PLA/sheep wool biocomposites. Full article