The yak rumen microflora has more efficient fiber-degrading and energy-harvesting abilities than that of low-altitude cattle; however, few studies have investigated the effects of dietary energy levels on the rumen bacterial populations and the relationship between rumen bacteria and the intramuscular fatty acid profile of fattening yaks. In this study, thirty yaks were randomly assigned to three groups. Each group received one of the three isonitrogenous diets with low (3.72 MJ/kg), medium (4.52 MJ/kg), and high (5.32 MJ/kg) levels of net energy for maintenance and fattening. After 120 days of feeding, results showed that increasing dietary energy significantly increased ruminal propionate fermentation and reduced ammonia concentration. The 16S rDNA sequencing results showed that increasing dietary energy significantly increased the ratio of Firmicutes to Bacteroidetes and stimulated the relative abundance of Succiniclasticum, Saccharofermentans, Ruminococcus, and Blautia populations. The quantitative real-time PCR analysis showed that high dietary energy increased the abundances of Streptococcus bovis, Prevotella ruminicola, and Ruminobacter amylophilus at the species level. Association analysis showed that ruminal acetate was positively related to some intramuscular saturated fatty acid (SFA) contents, and Prevotella was significantly positively related to intramuscular total polyunsaturated fatty acid content and negatively related to intramuscular total SFA content. This study showed that high dietary energy mainly increased ruminal amylolytic and propionate-producing bacteria populations, which gave insights into how the effects of dietary energy on rumen bacteria are related to intramuscular fat fatty acids of fattening yaks.

In this study, we aimed to classify 7 cow behavior patterns automatically with an inertial measurement unit (IMU) using a fully convolutional network (FCN) algorithm. Behavioral data of 12 cows were collected by attaching an IMU in a waterproof box on the neck behind the head of each cow. Seven behavior patterns were considered: rub scratching (leg), ruminating-lying, lying, feeding, self-licking, rub scratching (neck), and social licking. To simplify the data and compare classification performance with or without magnetometer data, the 9-axis IMU data were reduced using the square root of the sum of squares to develop 2 datasets. Comparing the classification accuracy of the 3 models using a window size of 64 with 6-axis data and a window size of 128 with both 6-axis and 9-axis data, the best overall accuracy (83.75%) was achieved using the FCN model with a window size of 128 (12.8 s) using all IMU data. This model achieved classification accuracies of 83.2, 96.5, 92.8, 98.1, 82.9, 87.2, and 45.2% for ruminating-lying, lying, feeding, rub scratching (leg), self-licking, rub scratching (neck), and social licking, respectively. As a sequence of varied and intensive movement, the classification accuracy of behavior patterns related to skin disease was lower; better classification of these behavior patterns could be achieved with full IMU data and a larger window size. In the future, additional data will take into account different data types, such as audio and video data, to further enhance performance. In addition, an adaptive sliding window size will be used to improve model performance.

The experiment was conducted to compare the growth performance, rumen fermentation, nutrient digestibility, and ruminal and fecal bacterial community between yaks and cattle-yaks. Ten male yaks (36-month-old) were used as the yak (YAK) group and 10 male cattle-yaks with similar age were selected as the cattle-yak (CAY) group. All the animals were fed same ration and the experiment lasted for 60 days. The results showed that the average daily gain and dry matter intake of CAY group were higher (P < 0.05) than those of YAK group. The ruminal concentrations of total volatile fatty acids, acetate, and butyrate were higher (P < 0.05) in CAY group than those in YAK group. However, the neutral detergent fiber and acid detergent fiber digestibility exhibited an opposite between two groups. In the rumen, the relative abundances of Prevotella 1 and Prevotellaceae UCG-001 were higher (P < 0.05) and Succiniclasticum and Butyrivibrio 2 were lower (P < 0.05) in YAK group compared to CAY group. In the feces, the unclassified Lachnospiraceae, Lachnospiraceae NK4A136 group, and Lachnospiraceae AC2044 group were significantly enriched (P < 0.05) in YAK group, whereas the Ruminococcaceae UCG-010, Ruminococcaceae UCG-013, and Succiniclasticum were significantly enriched (P < 0.05) in CAY group. Overall, under the same diet, the yaks have higher fiber utilization and cattle-yaks have higher energy utilization.

Live body weight (LBW) is one of the most important parameters for supervising the growth and development of livestock. The yak (Bos grunniens) is a special species of cattle that lives on the Qinghai-Tibetan Plateau. Yaks are more untamed than regular cattle breeds, thus it is more challenging to measure their LBW. In this study, a YOLOv8 yak detection and LBW estimation models were used to automatically estimate yak LBW in real-time. First, the proper posture (normal posture) and individual yak identification was confirmed and then the YOLOv8 detection model was used for LBW estimation from 2-dimensional (2D) images. Yak LBW was estimated through yak body parameter extraction and a simple linear regression between the estimated yak LBW and the actual measured yak LBW. The results showed that the overall detection performance of yak normal yak posture was described by precision, recall, and mean Average Precision 50 (mAP50) indicators, reaching 81.8, 86.0, and 90.6%, respectively. The best yak identification results were represented by precision, recall, and mAP50 values of 97.8, 96.4, and 99.0%, respectively. The yak LBW estimation model achieved better results for the 12 mo old yaks with shorter hair with R², root mean square error (RMSE), mean absolute percentage error (MAPE), and Multiple R values of 0.96, 2.43 kg, 1.69%, and 0.98, respectively. The results demonstrate that yak LBW can be estimated and monitored in real-time using this approach. This study has the potential to be used for daily yak LBW monitoring in an unstressed manner and to save considerable labor resources for large-scale livestock farms. In the future, to reduce the limitations caused by the impacts of yak hair and light condition data sets of dairy cows and yaks of different ages will be used to improve and generalize the model.

Background: This study investigated changes in rumen protozoal and methanogenic communities, along with the correlations among microbial taxa and methane (CH₄) production of six Belmont Red Composite beef steers fed tea seed saponins (TSS). Animals were fed in three consecutive feeding periods, a high-grain basal diet for 14 d (BD period) then a period of progressive addition of TSS to the basal diet up to 30 g/d for 20 d (TSS period), followed by the basal diet for 13 d without TSS (BDP post-control period). Results: The study found that TSS supplementation decreased the amount of the protozoal genus Entodinium and increased Polyplastron and Eudiplodinium genera. During BDP period, the protozoa community of steers did not return to the protozoal profiles observed in BD period, with higher proportions of Metadinium and Eudiplodinium and lower Isotricha. The addition of TSS was found to change the structure of methanogen community at the sub-genus level by decreasing the abundance of methanogens in the SGMT clade and increasing the abundance of methanogens in the RO clade. The correlation analysis indicated that the abundance of SGMT clade methanogens were positively correlated with Isotricha, and Isotricha genus and SGMT clade methanogens were positively correlated with CH₄ production. While RO clade were positively correlated with the proportion of Metadinium genus, which was negatively correlated with CH₄ emission. Conclusions: These results suggest that different genera of rumen protozoa ciliates appear to be selectively inhibited by TSS, and the change in methanogen community at the subgenus level may be due to the mutualistic relationships between methanogens and rumen ciliates.

Yak is the main livestock in the highlands of China. The low reproductive rate of yaks is a serious constraint on their production and utility. N-carbamylglutamate (NCG) can increase arginine synthesis in mammals and has been shown to improve reproductive performance. Twelve multiparous and simutaneous anoestrous female yaks were randomly divided into two groups, one of which was fed the basal diet (Control, n = 6), and the other was fed the basal diet supplemented with NCG at 6 g/day/yak (NCG, n = 6). All yaks were slaughtered on the 32nd day (the time predicted for the selection of the last wave of dominant follicles), and their ovarian tissues were collected and follicles were classified. NCG supplementation increased the number of large ovarian follicles (diameter > 10 mm), as well as caused significant changes in the transcriptional and metabolic levels in yak ovaries which due to the differential expression of 889 genes and 94 metabolites. Integrated analysis of the transcriptomics and metabolomics data revealed that the differentially expressed genes and differential metabolites were primarily involved in the process of energy metabolism, amino acid metabolic pathways, carbohydrate metabolic pathways, and lipid metabolic pathways. The highlighted changes were associated with amino acid synthesis and metabolism, ovarian steroid hormone synthesis, the pentose phosphate pathway, and the tricarboxylic acid cycle, suggesting that NCG supplementation may promote estrogen synthesis and help regulate follicular development by altering the pathways associated with glucose catabolism. The results present important clues for understanding the mechanisms by which NCG supplementation promotes follicular development in yaks. The findings of this study provide a basis for the development and application of NCG in optimizing animal reproduction, including yak reproductive performance, which may help optimize livestock management and uplift the pastoral economy.