Journal of Animal Science and Technology最新文献

{"title":"Comparative miRNome analysis of colostrum- and mature milk-derived extracellular vesicles from Holstein and Jersey cows.","authors":"Daye Mun, Sangdon Ryu, Dong-Hyun Lim, Sangnam Oh, Younghoon Kim","doi":"10.5187/jast.2024.e84","DOIUrl":"10.5187/jast.2024.e84","url":null,"abstract":"<p><p>MicroRNAs (miRNAs) are small noncoding RNAs that play a pivotal role in the regulation of gene expression. Analysis of miRNAs is important for understanding a variety of biological processes. Sequencing of miRNAs within milk-derived extracellular vesicles (EVs) provides valuable insights into the molecular mechanisms through which these EVs influence recipient cells. Comparative miRNA sequencing of colostrum and mature milk from different cow breeds can demonstrate breed-specific differences and improve the understanding of potential therapeutic applications in immune regulation and gut health. Therefore, this study was conducted to compare the miRNA profiles and characteristics of colostrum- and mature milk-derived EVs from Holstein and Jersey breeds and determine their effects on intestinal epithelial cells. The miRNA profiles of EVs isolated from the colostrum and mature milk of Holstein and Jersey cows were analyzed via small RNA sequencing. Holstein colostrum-derived EVs exhibited the most diverse miRNA profile with 421 identified miRNAs compared with 259 in mature milk-derived EVs. Jersey colostrum EVs had 198 miRNAs, whereas mature milk EVs had 282. Differential expression analysis revealed considerable miRNA differences between colostrum and mature milk, particularly in Holstein cows. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed that miRNAs from colostrum EVs predominantly regulated immune-related pathways. Transcriptomic analysis of human colon cell line HT-29 treated with Holstein colostrum EVs confirmed the modulation of genes associated with immune responses. These findings indicate that colostrum-derived EVs, particularly from Holstein cows, play a pivotal role in immune regulation and could be potential candidates for therapeutic applications.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"67 1","pages":"193-207"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review.","authors":"Md Nasim Reza, Kyu-Ho Lee, Eliezel Habineza, Samsuzzaman, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung","doi":"10.5187/jast.2024.e111","DOIUrl":"10.5187/jast.2024.e111","url":null,"abstract":"<p><p>The growing demands of sustainable, efficient, and welfare-conscious pig husbandry have necessitated the adoption of advanced technologies. Among these, RGB imaging and machine vision technology may offer a promising solution for early disease detection and proactive disease management in advanced pig husbandry practices. This review explores innovative applications for monitoring disease symptoms by assessing features that directly or indirectly indicate disease risk, as well as for tracking body weight and overall health. Machine vision and image processing algorithms enable for the real-time detection of subtle changes in pig appearance and behavior that may signify potential health issues. Key indicators include skin lesions, inflammation, ocular and nasal discharge, and deviations in posture and gait, each of which can be detected non-invasively using RGB cameras. Moreover, when integrated with thermal imaging, RGB systems can detect fever, a reliable indicator of infection, while behavioral monitoring systems can track abnormal posture, reduced activity, and altered feeding and drinking habits, which are often precursors to illness. The technology also facilitates the analysis of respiratory symptoms, such as coughing or sneezing (enabling early identification of respiratory diseases, one of the most significant challenges in pig farming), and the assessment of fecal consistency and color (providing valuable insights into digestive health). Early detection of disease or poor health supports proactive interventions, reducing mortality and improving treatment outcomes. Beyond direct symptom monitoring, RGB imaging and machine vision can indirectly assess disease risk by monitoring body weight, feeding behavior, and environmental factors such as overcrowding and temperature. However, further research is needed to refine the accuracy and robustness of algorithms in diverse farming environments. Ultimately, integrating RGB-based machine vision into existing farm management systems could provide continuous, automated surveillance, generating real-time alerts and actionable insights; these can support data-driven disease prevention strategies, reducing the need for mass medication and the development of antimicrobial resistance.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"67 1","pages":"17-42"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of breed composition in genomic prediction using crossbred pig reference population.","authors":"Euiseo Hong, Yoonji Chung, Phuong Thanh N Dinh, Yoonsik Kim, Suyeon Maeng, Young Jae Choi, Jaeho Lee, Woonyoung Jeong, Hyunji Choi, Seung Hwan Lee","doi":"10.5187/jast.2025.e2","DOIUrl":"10.5187/jast.2025.e2","url":null,"abstract":"<p><p>In contrast to conventional genomic prediction, which typically targets a single breed and circumvents the necessity for population structure adjustments, multi-breed genomic prediction necessitates accounting for population structure to mitigate potential bias. The presence of this structure in multi-breed datasets can influence prediction accuracy, rendering proper modeling crucial for achieving unbiased results. This study aimed to address the effect of population structure on multi-breed genomic prediction, particularly focusing on crossbred reference populations. The prediction accuracy of genomic models was assessed by incorporating genomic breed composition (GBC) or principal component analysis (PCA) into the genomic best linear unbiased prediction (GBLUP) model. The accuracy of five different genomic prediction models was evaluated using data from 354 Duroc × Korean native pig crossbreds, 1,105 Landrace × Korean native pig crossbreds, and 1,107 Landrace × Yorkshire × Duroc crossbreds. The models tested were GBLUP without population structure adjustment, GBLUP with PCA as a fixed effect, GBLUP with GBC as a fixed effect, GBLUP with PCA as a random effect, and GBLUP with GBC as a random effect. The highest prediction accuracies for backfat thickness (0.59) and carcass weight (0.50) were observed in Models 1, 4, and 5. In contrast, Models 2 and 3, which included population structure as a fixed effect, exhibited lower accuracies, with backfat thickness accuracies of 0.40 and 0.53 and carcass weight accuracies of 0.34 and 0.38, respectively. These findings suggest that in multi-breed genomic prediction, the most efficient and accurate approach is either to forgo adjusting for population structure or, if adjustments are necessary, to model it as a random effect. This study provides a robust framework for multi-breed genomic prediction, highlighting the critical role of appropriately accounting for population structure. Moreover, our findings have important implications for improving genomic selection efficiency, ultimately enhancing commercial production by optimizing prediction accuracy in crossbred populations.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"67 1","pages":"56-68"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drone pupae extract enhances Hanwoo myosatellite cell function for cultivated meat production.","authors":"Nayoung Choi, Sanghun Park, Gyutae Park, Sehyuk Oh, Sol-Hee Lee, Junsoo Lee, Hyoyoung Kim, Geul Bang, Jungseok Choi","doi":"10.5187/jast.2024.e98","DOIUrl":"10.5187/jast.2024.e98","url":null,"abstract":"<p><p>In this study, we analyzed effects of drone pupae aqueous extract powder (DEP) on proliferation and differentiation of Hanwoo myosatellite cells (HSC). Results of amino acid, vitamin, and mineral analysis of drone pupae revealed the presence of branched-chain amino acids, Glu, essential amino acids, vitamins B6, C and Mg, K, and so on. Additionally, drone pupae were shown to have an antioxidant ability. HSC were cultured for proliferation by adding 0, 10, 100, 200, and 400 μg/mL DEP to the medium. As a result of MTS analysis, DEP increased the proliferation capacity of HSC, with cell viability being significantly higher after treatment with DEP, especially when DEP was used at 100 μg/mL (p < 0.05). To measure the differentiation ability of HSC, 0 and 100 μg/mL DEP (CON, D100) were added to the medium, and cells were cultured. Myotube formation was confirmed through images using immunofluorescence staining. Fusion index and myotube area in the D100 were higher than those in the CON (<i>p</i> < 0.01). DEP promoted differentiation ability and myotube formation by increasing the expression of <i>MYH2</i>, <i>MYOG</i>, and <i>DES</i> genes and MYH2 and DES proteins in HSC. Additionally, in HSC differentiation culture, proteome expression intensity was higher in D100 than in CON. Proteins upregulated in the D100 group included Myosin, IL18, MYO1D, and so on. In conclusion, characteristics of various components present in DEP could improve the proliferation and differentiation ability of HSC. This suggests that drone pupae can be used as a functional substance to enhance muscle growth.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"67 1","pages":"252-272"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research trends in livestock facial identification: a review.","authors":"Mun-Hye Kang, Sang-Hyon Oh","doi":"10.5187/jast.2025.e4","DOIUrl":"10.5187/jast.2025.e4","url":null,"abstract":"<p><p>This review examines the application of video processing and convolutional neural network (CNN)-based deep learning for animal face recognition, identification, and re-identification. These technologies are essential for precision livestock farming, addressing challenges in production efficiency, animal welfare, and environmental impact. With advancements in computer technology, livestock monitoring systems have evolved into sensor-based contact methods and video-based non-contact methods. Recent developments in deep learning enable the continuous analysis of accumulated data, automating the monitoring of animal conditions. By integrating video processing with CNN-based deep learning, it is possible to estimate growth, identify individuals, and monitor behavior more effectively. These advancements enhance livestock management systems, leading to improved animal welfare, production outcomes, and sustainability in farming practices.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"67 1","pages":"43-55"},"PeriodicalIF":2.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11833198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complete genome sequence of <i>Corynebacterium</i> sp. SCR221107, encoding biosynthesis of vitamin B₁₂ isolated from the rumen fluid of Holstein dairy cows.","authors":"Keun Sik Baik, Sonny C Ramos, Sang Hoon Na, Seon Ho Kim, A Rang Son, Michelle Miguel, Sang Suk Lee","doi":"10.5187/jast.2024.e74","DOIUrl":"10.5187/jast.2024.e74","url":null,"abstract":"<p><p><i>Corynebacterium</i> sp. SCR221107 was isolated from the rumen fluid of healthy male Holstein dairy cows from a research farm at Suncheon, Jeollanam-do, Korea. <i>Corynebacterium</i> sp. SCR221107 is a functional probiotic candidate that produces vitamin B₁₂. All <i>Corynebacterium</i> sp. SCR221107 was sequenced using the PacBio RS II and Illumina HiSeq platforms and assembled <i>de novo</i>. The complete genome sequence of <i>Corynebacterium</i> sp. SCR221107 contained one circular chromosome (3,043,024 bp) with a guanine + cytosine (GC) content of 60.1%. Annotation analysis showed the presence of 2,639 protein-coding sequences, 15 rRNA genes, and 57 tRNA genes. Genome analysis found that <i>Corynebacterium</i> sp. SCR221107 encodes various genes associated with vitamin B12 synthesis and transport. The genomic information provided a detailed understanding of <i>Corynebacterium</i> sp. SCR221107, suggesting that this isolate may have potential probiotic applications.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"66 6","pages":"1291-1295"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of gum Arabic as natural prebiotic on intestinal ecosystem of post-hatched broiler chicks.","authors":"Hani Hasan Al-Baadani, Rashed Abdullah Alhotan, Mahmoud Mustafa Azzam, Ibrahim Abdullah Alhidary, Abdulrahman Salem Alharthi, Abdulaziz Abdullah Al-Abdullatif","doi":"10.5187/jast.2023.e57","DOIUrl":"10.5187/jast.2023.e57","url":null,"abstract":"<p><p>The purpose of the current study was to investigate the effects of gum Arabic supplementation on short-chain fatty acids, cecal microbiota, immune-related gene expression, and small intestinal morphology in post-hatched broiler chicks. On the day of hatching, four hundred thirty-two commercial male broiler chicks were randomly allocated into six treatments with twelve cages as replicates of six chicks each for 24 days. Dietary treatments (T1 to T6) were supplemented with 0.0, 0.12, 0.25, 0.50, 0.75, and 1.0% gum Arabic to the basal diet, respectively. Performance parameters, short-chain fatty acid concentration, quantification of microbiota and immune response gene expression (pre-inflammatory cytokines, mucin-2, and secretory immunoglobulin A), and histomorphometry of the small intestine were measured. According to our results, daily weight gains in T2 and the production efficiency index increased in T2 to T4, whereas daily feed intake decreased in T2, T3, T5, and T6, but feed conversion ratio improved. Concentration of lactate, acetate, butyrate, and total short-chain fatty acid increased in T2, T3, T5, and T6. Propionate ‎in T2 T3, T4, and T6 and format in T2, T5, and T6 also increased. <i>Lactobacillus</i> spp. quantitatively increased from T3 to T6, whereas <i>Bacteroides</i> spp. decreased in T3 and T5. Other microbiota quantitatively showed no effect of dietary supplements. <i>IL-1β</i>, <i>TNF-α</i>, and <i>MUC-2</i> decreased in T2 to T6 and IL-12 in T3, whereas <i>INF-Y</i> increased in T4 to T6 and <i>SIgA</i> in T4. All histometeric parameters of the duodenum, jejunum, and ileum improved with dietary supplementation. We conclude that the administration of gum Arabic resulted in an improvement in overall performance, fermentation metabolites, and modification of microbiota and immune response with improved histomorphometry in the intestines of young chicks.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"47 1","pages":"1203-1220"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85683263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing animal breeding through quality control in genomic data - a review.","authors":"Jungjae Lee, Jong Hyun Jung, Sang-Hyon Oh","doi":"10.5187/jast.2024.e92","DOIUrl":"10.5187/jast.2024.e92","url":null,"abstract":"<p><p>High-throughput genotyping and sequencing has revolutionized animal breeding by providing access to vast amounts of genomic data to facilitate precise selection for desirable traits. This shift from traditional methods to genomic selection provides dense marker information for predicting genetic variants. However, the success of genomic selection heavily depends on the accuracy and quality of the genomic data. Inaccurate or low-quality data can lead to flawed predictions, compromising breeding programs and reducing genetic gains. Therefore, stringent quality control (QC) measures are essential at every stage of data processing. QC in genomic data involves managing single nucleotide polymorphism (SNP) quality, assessing call rates, and filtering based on minor allele frequency (MAF) and Hardy-Weinberg equilibrium (HWE). High-quality SNP data is crucial because genotyping errors can bias the estimates of breeding values. Cost-effective low-density genotyping platforms often require imputation to deduce missing genotypes. QC is vital for genomic selection, genome-wide association studies (GWAS), and population genetics analyses because it ensures data accuracy and reliability. This paper reviews QC strategies for genomic data and emphasizes their applications in animal breeding programs. By examining various QC tools and methods, this review highlights the importance of data integrity in achieving successful outcomes in genomic selection, GWAS, and population analyses. Furthermore, this review covers the critical role of robust QC measures in enhancing the reliability of genomic predictions and advancing animal breeding practices.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"66 6","pages":"1099-1108"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nutritional value of common carbohydrate sources used in pet foods.","authors":"Hyun-Woo Cho, Kangmin Seo, Min Young Lee, Sang-Yeob Lee, Kyoung-Min So, Ki Hyun Kim, Ju Lan Chun","doi":"10.5187/jast.2024.e91","DOIUrl":"10.5187/jast.2024.e91","url":null,"abstract":"<p><p>Diet digestibility can vary based on factors such as the type of ingredients, processing techniques, formulation, fiber content, and nutrient interactions. Unlike proteins and fats, there is no specific carbohydrate requirement, which typically constitutes 30%-60% of commercial dried dog foods. Because of the significant proportion of carbohydrates in dog food, this study aimed to evaluate the differences in nutrient digestibility among barley, brown rice, corn, mung bean, and rice, which are common carbohydrate sources in commercial dog foods. All experimental diets had consistent chemical compositions. The digestibility of each carbohydrate source was evaluated using the total feces collection method in four castrated male and four neutered female beagles with an average age of 4.58 ± 0.14 years. The average daily dry matter intake of the five experimental diets was 203.0 ± 3.23 g/day. The percentage of dry matter digestibility of the apparent total tract digestibility (ATTD) was the highest for rice and corn at 92.45% and 92.95%, respectively, followed by brown rice (91.61%), barley (88.81%), and mung beans (80.74%). The percentage of nitrogen-free extract digestibility was also high for rice, corn, and brown rice at 97.08%, 96.14%, and 95.56%, respectively, followed by barley at 90.10% and mung bean at 83.38%. Amino acid digestibility analysis revealed no statistically significant differences between rice, corn, brown rice, and barley, except for methionine, which is an essential amino acid. Although the ATTD and amino acid profile of the mung bean-based diet were less efficient than those of the other test diets, the overall digestibility was satisfactory and there were no significant differences in palatability. The differences in digestibility observed in mung bean-based diets compared to other grain-based diets can be attributed to variations in the starch and fiber content of the raw materials. By leveraging these characteristics, mung bean-based diets may offer strategic benefits for glycemic control and weight management in dogs. Our results may serve as a basis for formulating appropriate diets for dogs.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"66 6","pages":"1282-1290"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647412/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Greenhouse gas emissions from livestock: sources, estimation, and mitigation.","authors":"Eska Nugrahaeningtyas, Jong-Sik Lee, Kyu-Hyun Park","doi":"10.5187/jast.2024.e86","DOIUrl":"10.5187/jast.2024.e86","url":null,"abstract":"<p><p>The increase in greenhouse gas (GHG) emissions has resulted in climate change and global warming. Human activities in many sectors, including agriculture, contribute to approximately 9.2% of total GHG emissions from Annex I countries. An argument on issues of livestock being the highest contributor to GHG emissions has grown since FAO's 2006 report Livestock's Long Shadow. The issue has continued growing, conflicting the importance of the industry in terms of food security and livelihoods, thus, monitoring GHG emission from this sector is vital. The most commonly used methods for calculating GHG emissions from the livestock sector are life cycle assessment (LCA) and the GHG inventory. Although the LCA presents information on the impacts of the livestock industry on the environment, the GHG inventory is the main tool used internationally for GHG reporting. This review comprehensively discusses the source of GHG emissions from the livestock industry and its estimation methodology, as well as the current strategies for mitigating these emissions.</p>","PeriodicalId":14923,"journal":{"name":"Journal of Animal Science and Technology","volume":"66 6","pages":"1083-1098"},"PeriodicalIF":2.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}