Journal of Dairy Science最新文献

Knowledge is lacking on separation strategies that can best prepare calves to final separation from the dam in cow-calf contact (CCC) systems. This controlled trial compared the effects of 2 different methods to gradually reduce cows' access to their calf termed “debonding” on calf growth in a cow-driven CCC system. Initially, cows (Norwegian Red breed) had 24 h/d computer-controlled access to their calves. In the long debonding (LDB) treatment (n = 16), a gradual reduction of cows' access to their calves was initiated 28 d after calving over a total duration of 28 d; first to 12 h/d (14 d), and then to 6 h/d (14 d). In the short debonding (SDB) treatment (n = 14), reduction was initiated 45 d after calving over a total duration of 10 d; first to 12 h/d (5 d), and then to 6 h/d (5 d). From 6 h/d, access was finally reduced to 0 h/d for 4 d for both treatments, resulting in a study period of 60 d in total. Calves had ad libitum access to concentrate, hay and water throughout the study. Independent of treatment, ad libitum access to whole milk from an automatic feeder was granted once cow access was reduced. Cows and calves had the possibility for fence line contact at all times. The primary outcome variable calf weight gain was registered biweekly. Calf ADG was analyzed with a linear mixed model. The ADG was similar across treatments during 24 h/d access (1.04 ± 0.07 kg). Debonding treatment affected calf growth differently with each gradual reduction in cow access (12 h/d, 6 h/d and 0 h/d); however, no main effect of treatment was detected. The SDB calves had a pattern of increased ADG with the first reduction in access (+0.39 ± 0.18kg), followed by significant growth checks as access was reduced further to 6 h/d and 0 h/d (−0.41 ± 0.20 kg and −1.15 ± 0.31 kg, respectively). The LDB calves only showed significant weight checks at the final reduction in access (0 h/d access), yet at a lower degree (−0.46 ± 0.21 kg) than SDB calves. As expected, ADG was negatively associated with health events but positively associated with intake of concentrate and supplemental milk. Collectively, the results from the present study might point toward a long adaptation to separation which is initiated at a younger age being more favorable for calf performance.

Complete self-assembly and reassembly behavior of bitter peptide-protein necessitates multilevel theories that encompass phenomena ranging from the self-assembly of recombinant complex to atomic trajectories. An extension to the level of mechanism method was put forth, involves limited enzymatic digestion and bottom-up proteomics to dissect inherent heterogeneity within β-LG and β-LG-PPGLPDKY complex and uncover conformational and dynamic alterations occurring in specific local regions of the model protein. Bitter peptide PPGLPDKY spontaneously bound to IIAEKTK, IDALNENK, and YLLFCMENSAEPEQSLACQCLVR regions of β-LG in a 1:1 stoichiometric ratio to mask bitterness perception. Molecular dynamic simulation and free energy calculation provided time-varying atomic trajectories of the recombinant complex and found that a peptide was stabilized in the upper region of the hydrophobic cavity with the binding free energy of −30.56 kJ mol⁻¹ through 4 hydrogen bonds (Glu74, Glu55, Lys69, and Ser116) and hydrophobic interactions (Asn88, Asn90, and Glu112). Current research aims to provide valuable physical insights into the macroscopic self-assembly behavior between proteins and bitter peptides, and the meticulous design of highly acceptable taste characteristics in goat milk products.

In dairy cattle production, it is important to understand how inbreeding affects production, fertility, and health traits. However, there is still limited use of genomic information to estimate inbreeding, despite advancements in genotyping technologies. To address this gap, we investigated the effect of inbreeding on German Holstein dairy cattle using both pedigree-based and genomic-based inbreeding estimators. We employed one method based on pedigree information (F_ped) together with 6 genomic-based methods, including 3 genome-wide complex trait analysis software estimators (F_hat1, F_hat2, F_hat3), VanRaden's first method (F_VR1, with observed allele frequencies, and F_VR0.5, when allele frequencies are set to 0.5), and one based on runs of homozygosity (F_roh). Data from 24,489 cows with both phenotypes and genotypes were used, with a pedigree including 232,780 animals born between 1970 and 2018. We analyzed the effects of inbreeding depression on production, fertility, and health traits separately, using single-trait linear animal models as well as threshold models to account for the binary nature of the health traits. For the health traits, we transformed solutions from the liability scale to a probability scale for easier interpretation. Our results showed that the mean inbreeding coefficients from all estimators ranged from −0.003 to 0.243, with negative values observed for most genomic-based methods. We found out that a 1% increase in inbreeding caused a depression ranging from 25.94 kg (F_hat1) to 40.62 kg (F_hat3), 1.18 kg (F_hat2) to 1.70 kg (F_hat3), 0.90 kg (F_hat2) to 1.45 kg (F_roh and F_hat3), 0.19 (F_ped) to 0.34 d (F_hat3) for 305-d milk yield, fat, protein, and calving interval, respectively. The health traits showed very slight gradual changes when inbreeding was increased steadily from 0% to 50%, with digital dermatitis showing a rather contrasting trend to that of mastitis, which increased the more an animal was inbred. Overall, our study highlights the importance of considering both pedigree-based and genomic-based inbreeding estimators when assessing the impact on inbreeding, emphasizing that not all inbreeding is harmful.

The objectives of this study were to assess the effects of feeding 2 different diets, a diet with low dietary cation-anion difference (DCAD) or a diet with synthetic zeolite A, to multiparous Holstein cows during the close-up period on dry matter intake (DMI) and energy metabolism, as well as to evaluate colostrum and milk production. A total of 121 multiparous Holstein cows, blocked by lactation number and expected parturition date were enrolled at 254 d of gestation and randomly assigned to 1 of 3 dietary treatments: control (CON; +190 mEq/kg; n = 40), negative DCAD (−DCAD, −65 mEq/kg; n = 41; Ultra Chlor; Vita Plus, Lake Mills, WI), or a diet containing sodium aluminum silicate zeolite (XZ; +278 mEq/kg, fed at 3.3% dry matter, targeting 500 g/d; n = 40; X-Zelit, Protekta Inc., Lucknow, ON, Canada/Vilofoss, Graasten, Denmark). Prepartum DMI was measured daily using Insentec roughage intake control (RIC) gates (RIC System, Holofarm Group, the Netherlands). All cows received the same postpartum diet. Blood and urine samples were collected daily beginning 14 d before parturition (d −14) until parturition (d 0), and on 1, 2, 3, 6, 9, 12, 15, 18, 21, 35, and 49 d postpartum. Colostrum collected within 6 h of parturition, weighed, and based on samples' Brix value, IgG concentrations, and nutrient composition were analyzed. Prepartum, cows fed the XZ diet had decreased DMI (11.70 ± 0.26, 13.88 ± 0.26, and 13.45 ± 0.25 kg/d for XZ, CON, and −DCAD, respectively) and lower rumination (487 ± 8.1, 531 ± 8.3, and 527 ± 8.5 min for XZ, CON, and −DCAD, respectively) compared with CON and −DCAD. However, rumination was not different postpartum due to treatment. No prepartum or postpartum differences were observed for glucose or BHB concentrations in blood between dietary treatments. Colostrum collected from cows fed XZ had the highest IgG concentrations (91.10 ± 2.63, 78.00 ± 2.63, and 78.90 ± 2.63 mg/mL for XZ, CON, and −DCAD, respectively), but yield did not differ between dietary treatments. Additionally, cows in their third lactation or greater fed XZ had the highest milk production (51.0 ± 1.1 kg) during the first 49 d in milk. This study demonstrates that despite a decrease in DMI and rumination in cows fed XZ prepartum, blood BHB concentrations were not altered. Additionally, cows fed XZ had higher colostral IgG concentrations and cows in their third lactation or greater fed XZ produced the most milk. These data suggest that feeding XZ prepartum may improve colostrum quality and milk yield in mature cows, and does not affect energy metabolism.

The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12–15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1–3, 13–17, 22, and 25–26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2–3, 11, 13, 14, 16, 18, 20, and 25–26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits (e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G) overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population.

As the stress-inducible isoform of the heat-shock protein 90 (HSP90), the HSP90AA1 gene encodes HSP90α and plays an important role in heat stress (HS) response. Therefore, this study aimed to investigate the role of the HSP90AA1 gene in cellular responses during HS and to identify functional SNPs associated with thermotolerance in Holstein cattle. For the in vitro validation experiment of acute HS, cells from the Madin-Darby bovine kidney cell line were exposed to 42°C for 1 h, and various parameters were assessed, including cell apoptosis, cell autophagy, and the cellular functions of HSP90α by using its inhibitor 17-allylamino-17-demethoxygeldanamycin (17-AAG). Furthermore, the polymorphisms identified in the HSP90AA1 gene and their functions related to HS were validated in vitro. Acute HS exposure induced cell apoptosis, cell autophagy, and upregulated expression of the HSP90AA1 gene. Inhibition of HSP90α by 17-AAG treatment had a significant effect on the expression of the HSP90α protein and increased cell apoptosis. However, autophagy decreased in comparison to the control treatment when cells were exposed to 42°C for 1 h. Five SNPs identified in the HSP90AA1 gene were significantly associated with rectal temperature and respiration score in Holstein cows, in which the rs109256957 SNP is located in the 3′ untranslated region (3′ UTR). Furthermore, we demonstrated that the 3′ UTR of HSP90AA1 is a direct target of bta-miR-1224 by cell transfection with exogenous microRNA (miRNA) mimic and inhibitor. The luciferase assays revealed that the SNP rs109256957 affects the regulation of bta-miR-1224 binding activity and alters the expression of the HSP90AA1 gene. Heat stress–induced HSP90AA1 expression maintains cell survival by inhibiting cell apoptosis and increasing cell autophagy. The rs109256957 located in the 3′ UTR region is a functional variation and it affects the HSP90AA1 expression by altering its binding activity with bta-miR-1224, thereby associating with the physiological parameters of Holstein cows.

The objective of this study was to examine the aroma profiles of 12 Gouda cheeses sold in China and to determine which aromas were preferred by young Chinese consumers (n = 110). The consumers selected 11 descriptors of the aromas of the Gouda cheeses in a check-all-that-apply questionnaire. These 11 descriptors were used by a panel of experts for sensory analysis to perform a quantitative descriptive analysis of the cheeses. A principal component analysis of the data from the quantitative descriptive analysis revealed that the characteristic aromas of young Gouda cheeses, medium-aged Gouda cheeses, and aged Gouda cheeses were “milky” and “whey”; “creamy” and “sour”; and “rancid” and “nutty,” respectively. The results of a penalty analysis combined with the check-all-that-apply results and the preference scores showed that the 3 groups of young Chinese consumers (those who often ate cheese, occasionally ate cheese, and never ate cheese) preferred the Gouda cheeses with “milky” or “creamy” aromas and did not enjoy those with “sour” or “rancid” aromas. Occasional cheese eaters comprised the majority of the young Chinese consumers, and they were more tolerant of the Gouda cheeses with “whey” and “sulfury” aromas than those who often or never ate cheese. In addition, we identified a positive correlation between the consumers' preferences for the aromas of the Gouda cheeses and their willingness to pay for them. Overall, the results of this study should help promote the development of Gouda cheeses and associated products that meet the preferences of young Chinese consumers.

Colostrum is a rich source of nutritional and non-nutritional components and is recognized as essential to transfer passive immunity to newborn calves. Because of the individual and seasonal variability in colostrum yield and composition, maintaining an adequate supply of high-quality colostrum year-round remains a challenge for commercial dairy producers. In this narrative review, we described the individual, seasonal, and herd-level variability of colostrum production and summarized the association between individual animal factors such as parity, sex of the calf, calf birth weight, as well as indicators of the cow's metabolic status and the yield and composition of colostrum. Further, we reviewed the current knowledge on the influence of prepartum nutrition and management strategies on colostrum production. Research on the metabolizable energy and protein supplied in the prepartum diet as well as on the inclusion and source of vitamins, minerals, and feed additives suggests prepartum nutrition influences the yield, quality, and composition of colostrum. Furthermore, the prepartum environment and dry period length remain influential factors in the production of colostrum. However, additional research is needed to understand the mechanisms by which prepartum nutrition and management affect colostrum production. Finally, time from calving to colostrum harvest and oxytocin administration as well as the current knowledge on the effect of heat treatment and colostrum storage strategies on colostral components were discussed. To conclude, we identify critical gaps in knowledge for future focus of investigation in colostrum research.

Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction methods and deep learning algorithms for genomic prediction of milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows measured by automatic milking systems (milking robots). A total of 1,993,509 daily records from 4,511 genotyped Holstein cows were collected by 36 milking robot stations. After quality control, 57,600 SNPs were available for the analyses. Four genomic prediction methods were considered: Bayesian least absolute shrinkage and selection operator (LASSO), multiple layer perceptron (MLP), convolutional neural network (CNN), and GBLUP. We implemented the first 3 methods using the Keras and TensorFlow libraries in Python (v.3.9) but the GBLUP method was implemented using the BLUPF90+ family programs. The accuracy of genomic prediction (mean square error) for MREF and MFAIL was 0.34 (0.08) and 0.27 (0.08) based on LASSO, 0.36 (0.09) and 0.32 (0.09) for MLP, 0.37 (0.08) and 0.30 (0.09) for CNN, and 0.35 (0.09) and 0.31(0.09) based on GBLUP, respectively. Additionally, we observed a lower reranking of top selected individuals based on the MLP versus CNN methods compared with the other approaches for both MREF and MFAIL. Although the deep learning methods showed slightly higher accuracies than GBLUP, the results may not be sufficient to justify their use over traditional methods due to their higher computational demand and the difficulty of performing genomic prediction for nongenotyped individuals using deep learning procedures. Overall, this study provides insights into the potential feasibility of using deep learning methods to enhance genomic prediction accuracy for behavioral traits in livestock. Further research is needed to determine their practical applicability to large dairy cattle breeding programs.

Automated milk feeders (AMF) allow farmers to raise calves in groups while generating individual records on milk consumption, drinking speed, and frequency of visits. Calves raised in groups benefit from social interaction, which facilitates learning and adapting to novelty. However, calves in large groups (>12 calves/feeder) experience a higher risk of disease transmission and competition than those housed individually or in smaller groups. Therefore, if group size, grouping strategy, and disease detection are not optimal, the health and performance of calves can be compromised. The objectives of this narrative literature review, from publications available as of February 2023, are to (1) describe the use of AMF in group housing systems for calves and the associated feeding behavior variables they automatically collect, (2) linking feeding behavior collected from AMF to disease risk in calves, (3) describe research on social behavior in AMF systems, and (4) introduce social networks as a promising tool for the study of social behavior and disease transmission in group-housed AMF-fed calves. Existing research suggests that feeding behavior measures from AMF can assist in detecting bovine respiratory disease and enteric disease, which are common causes of morbidity and mortality for preweaning dairy heifers. Automated milk feeder records show reduced milk intake, drinking speed, or frequency of visits when calves are sick. However, discrepancies exist among published research about the sensitivity of feeding behavior measures as indicators of sickness, likely due to differences in feeding plans and disease-detection protocols. Therefore, considering the influence of milk allowance, group density, and individual variation on the analysis of AMF data is essential to derive meaningful information used to inform management decisions. Research using dynamic social networks derived from precision data show potential for the use of social network analysis to understand disease transmission and the effect of disease on social behavior of group-housed calves.