This study compared the accuracy of several models for obtaining genetic evaluations of calving difficulty. The models were univariate threshold animal (TAM), threshold sire-maternal grandsire (TSM), linear animal (LAM), and linear sire-maternal grandsire (LSM) models and bivariate threshold-linear animal (TLAM), threshold-linear sire-maternal grandsire (TLSM), linear-linear animal (LLAM), and linear-linear sire-maternal grandsire (LLSM) models for calving difficulty and birth weight. Data were obtained from the American Gelbvieh Association and included 84,420 first-parity records of both calving difficulty and birth weight. Calving difficulty scores were distributed as 73.4% in the first category (no assistance), 18.7% in the second, 6.3% in the third, and 1.6% in the fourth. Included in the animal models were fixed sex of calf by age of dam subclasses, random herd-year-season effects, and random animal direct and maternal breeding values. Sire-maternal grandsire models were similar to the animal models, with animal and maternal effects replaced by sire and maternal grandsire effects. Models were compared using a data splitting technique based on the correlation of estimated breeding values from two samples, with one-half of the calving difficulty records discarded randomly in the first sample and the remaining calving difficulty records discarded in the second sample. Reported correlations are averages of 10 replicates. The results obtained using animal models confirmed the slight advantage of TAM over LAM (0.69 vs 0.63) and TLAM over LLAM (0.90 vs 0.86). Bivariate analyses greatly improved the accuracy of genetic prediction of direct effects on calving difficulty relative to univariate analyses. Similar ranking of the models was found for maternal effects, but smaller correlations were obtained for bivariate models. For sire-maternal grandsire models, no differences between sire or maternal grandsire correlations were observed for TLSM compared to LLSM, and small differences were observed between TSM and LSM. The threshold model offered advantages over the linear model in animal models but not in sire-maternal grandsire models. For genetic evaluation of calving difficulty in beef cattle, the threshold-linear animal model seems to be the best choice for predicting both direct and maternal effects.

The objective was to estimate the allelic and genotypic frequencies, genetic diversity and polymorphic information content for the β-casein, κ-casein and β-lactoglobulin genes. Blood and frozen semen samples were collected from 453 Jersey individuals registered by the Mexican Jersey Cattle Association. Twenty eight breed specific SNP primers for whole genes were used. The B allele of κ-casein had higher frequency (0.69) than the A (0.26) and E (0.05). For β-lactoglobulin, the highest frequency was for B (0.72), followed by A and C alleles (0.26 and 0.02, respectively). The β-casein allele with the highest frequency was A2 (0.71), followed by A1 (0.19), A3 (0.05), B (0.04) and C (0.01). The average genetic diversity (He) was 0.53. The average locus effective allele number was 1.79. These results indicate a high allelic diversity for κ-caseín, β-casein and β-lactoglobulin that could be included in breeding programs in the population studied, aimed to improve the milk quality traits of economic importance

The objective of this study was to evaluate the effects of bee pollen (BP) and propolis (PRO) supplementation on rabbits’ productive performance and serum metabolites through a meta-analysis. Sixteen peer-reviewed publications were included in the data set. The rabbit strains used in the studies included in the data set were New Zealand White, V-line, Rex, and V-line crosses. Weighted mean differences (WMD) between treatments supplemented with BP or PRO and control treatments were used to assess the magnitude of the effect. BP supplementation decreased (p < 0.001) daily feed intake (DFI) and feed conversion ratio (FCR); however, increased (p < 0.001) average daily gain (ADG) and hot carcass yield (HCY). PRO supplementation reduced DFI (p = 0.041) and FCR (p < 0.001), and increased ADG (p < 0.001) and HCY (p = 0.005). In blood serum, BP supplementation increased total antioxidant capacity (TAC; p = 0.002) and decreased serum creatinine concentration (p = 0.049). Likewise, decreased serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and malondialdehyde (MDA) were detected in response to BP supplementation (p < 0.05). PRO supplementation increased the TAC in blood serum (p = 0.018); however, decreased serum concentrations of AST, ALT, and MDA were observed (p < 0.05). In conclusion, BP or PRO supplementation can be used as a natural growth promoter in rabbits, and both can also improve rabbits' antioxidant status. However, BP or PRO supplementation does not affect rabbits' renal or hepatic health status.

The ultimate goal of genetic selection is to improve genetic progress by increasing favorable alleles in the population. However, with selection, homozygosity, and potentially harmful recessive alleles can accumulate, deteriorating genetic variability and hampering continued genetic progress. Such potential adverse side effects of selection are of particular interest in populations with a small effective population size like the Romosinuano beef cattle in Mexico. The objective of this study was to evaluate the genetic background and inbreeding depression in Mexican Romosinuano cattle using pedigree and genomic information. Inbreeding was estimated using pedigree ($F_{PED}$) and genomic information based on the genomic relationship matrix ($F_{GRM}$) and runs of homozygosity ($F_{ROH}$) of different length classes. Linkage disequilibrium ($LD$) was evaluated using the correlation between pairs of loci, and the effective population size ($N_e$) was calculated based on $LD$ and pedigree information. The pedigree file consisted of 4875 animals born between 1950 and 2019, of which 71 had genotypes. $LD$ decreased with the increase in distance between markers, and $N_e$ estimated using genomic information decreased from 610 to 72 animals (from 109 to 1 generation ago), the $N_e$ estimated using pedigree information was 86.44. The reduction in effective population size implies the existence of genetic bottlenecks and the decline of genetic diversity due to the intensive use of few individuals as parents of the next generations. The number of runs of homozygosity per animal ranged between 18 and 102 segments with an average of 55. The shortest and longest segments were 1.0 and 36.0 Mb long, respectively, reflecting ancient and recent inbreeding. The average inbreeding was 2.98 ± 2.81, 2.98 ± 4.01, and 7.28 ± 3.68% for $F_{PED}$, $F_{GRM}$, and $F_{ROH}$, respectively. The correlation between $F_{PED}$ and $F_{GRM}$ was −0.25, and the correlations among $F_{PED}$ and $F_{ROH}$ of different length classes were low (from 0.16 to 0.31). The correlations between $F_{GRM}$ and $F_{ROH}$ of different length classes were moderate (from 0.44 to 0.58), indicating better agreement. A 1% increase in population inbreeding decreased birth weight by 0.103 kg and weaning weight by 0.685 kg. A strategy such as optimum genetic contributions to maximize selection response and manage the long-term genetic variability and inbreeding could lead to more sustainable breeding programs for the Mexican Romosinuano beef cattle breed.

The food cold chain is an effective tool that allows food markets to maintain food quality and reduce losses. Poor logistics may result in foodborne disease outbreaks and greenhouse gas emissions caused by organic matter decay. The ongoing pandemic of COVID-19 makes it necessary to study the chances of SARS-CoV-2 transmissions in food products. This study reviews cold chain logistics as a handy tool for avoiding food safety risks, including COVID-19. The cold chain of perishables and its proper management make it possible to maintain quality and safety at any stage of the food supply chain. The technology covers each link of the food chain to prevent microbial spoilage caused by temperature fluctuations and the contamination with SARS-CoV-2 associated with perishable foods. Given the lack of knowledge in this field in Latin America, the region needs new research to determine the impact of the cold chain on perishable foodstuffs. The perishable cold chain is only as strong as its weakest link, and the national and international markets require new traceability protocols to minimize the effect of COVID-19.

A genome-wide association study (GWAS) was performed to elucidate genetic architecture of growth traits in Braunvieh cattle. Methods: The study included 300 genotyped animals by the GeneSeek^® Genomic Profiler Bovine LDv.4 panel; after quality control, 22,734 SNP and 276 animals were maintained in the analysis. The examined phenotypic data considered birth (BW), weaning (WW), and yearling weights. The association analysis was performed using the principal components method via the egscore function of the GenABEL version 1.8-0 package in the R environment. The marker rs133262280 located in BTA 22 was associated with BW, and two SNPs were associated with WW, rs43668789 (BTA 11) and rs136155567 (BTA 27). New QTL associated with these liveweight traits and four positional and functional candidate genes potentially involved in variations of the analyzed traits were identified. The most important genes in these genomic regions were MCM2 (minichromosome maintenance complex component 2), TPRA1 (transmembrane protein adipocyte associated 1), GALM (galactose mutarotase), and NRG1 (neuregulin 1), related to embryonic cleavage, bone and tissue growth, cell adhesion, and organic development. This study is the first to present a GWAS conducted in Braunvieh cattle in Mexico providing evidence for genetic architecture of assessed growth traits. Further specific analysis of found associated genes and regions will clarify its contribution to the genetic basis of growth-related traits.