The study was done to determine additive, maternal and common permanent environmental effects and best-suited model for some production traits using six univariate animal models that differed in the (co)variance components fitted to assess the importance of maternal effect using likelihood ratio test in Murrah buffaloes. Data from 614 Murrah buffaloes related to production traits were collected from history pedigree sheets maintained at the buffalo farm, Department of Livestock Production and Management (LPM), LUVAS, Hisar. The production traits under this study were 305 days milk yield (305DMY), peak yield (PY), lactation length (LL), dry period (DP), lactation milk yield (LMY) and wet average (WA). The heritability estimates were in the range of 0.33-0.44 for 305DMY, 0.25-0.51 for PY, 0.05-0.13 for LL, 0.03-0.23 for DP, 0.17-0.40 for LMY and 0.37-0.66 for WA. Model 1 was considered best for most of the traits, viz., 305DMY, PY, LL, LMY and WA followed by model 2 for DP. Covariance and correlated values within the traits caused inflation of heritability in model 3 and model 6. The maximum covariance between the additive and maternal effect was found in trait LMY, which was 14,183.90 in model 3 and the minimum value was also reported in the same trait for model 6, valued at -3522.37. Multivariate analysis showed that all production traits were moderate to high and positively correlated with each other except for DP, which was low and negative genetic and phenotypic correlated. Spearman's rank correlation coefficients of breeding value among all six models were high and significant, ranged from 0.78 to 1.00 for all the traits except DP, therefore any of the models could be taken into account depending upon the availability of data.
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http://dx.doi.org/10.1111/jbg.12852 | DOI Listing |
Int J Med Sci
January 2025
Medical Oncology Department of Gastrointestinal Cancer, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital & Institute, No.44 Xiaoheyan Road, Dadong District, Shenyang 110042, Liaoning Province, China.
Gastric cancer (GC) remains a significant global health challenge. This study aimed to comprehensively analyze GC epidemiology and risk factors to inform prevention and intervention strategies. We analyzed the Global Burden of Disease Study 2021 data, conducted 16 different machine learning (ML) models of NHANES data, performed Mendelian randomization (MR) studies on disease phenotypes, dietary preferences, microbiome, blood-based markers, and integrated differential gene expression and expression quantitative trait loci (eQTL) data from multiple cohorts to identify factors associated with GC risk.
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Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China.
New genotypes of hybrid from the and sections, which encompass economically important species of L., have great potential to significantly enhance genetic gain from selection. Growth and its functional and structural determinants exhibiting a high level of variability are not only controlled by genetics, but also affected by environment, as well as genotype and environment interaction (G×E).
View Article and Find Full Text PDFPhysiol Plant
January 2025
College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China.
Salt is a major abiotic factor significantly affecting plant growth and development. Alfalfa (Medicago sativa L.), a crucial perennial crop for livestock feed, shows significant differences in salt tolerance among different varieties.
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Wheat (Triticum aestivum L.) production is vital for global food security, providing energy and protein to millions of people worldwide. Recent advancements in wheat research have led to significant increases in production, fueled by technological and scientific innovation.
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January 2025
Plant Production Department, College of Food and Agricultural Sciences, King Saud University, P.O. Box. 2460, Riyadh, 11451, Saudi Arabia.
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