Influence of Calving Ease on In-Line Milk Lactose and Other Milk Components

Birth Traits Associated with Pre-Adulthood Disease Manifestations in Calves

The objective of this study was to explore the relationship between calf birth traits and their susceptibility to diseases before reaching adulthood. A total of 5253 birth traits of Chinese Holstein calves were examined, including gestation length (GL), calf weight at birth (CW), and calving ease score (CES), which ranges from 1 (easy) to 5 (very difficult). Furthermore, monthly medical records were scrutinized for pneumonia and diarrhea in these calves. The study assessed five aspects of disease manifestation in calves: age at first onset, frequency of illness, longest duration of treatment, and total duration of treatment. The link between age at onset and disease manifestation prior to adulthood was analyzed using general linear models and regression models. The GL of calves significantly correlated with the risk of pneumonia, with the risk decreasing as the GL increases. A higher CES was associated with a later onset of diarrhea in calves. Furthermore, the CES was significantly negatively correlated with the duration of diarrhea treatment in calves. These results suggest that implementing different preventive measures for calves with different birth traits and modifying treatment protocols for affected calves could enhance the productivity of dairy cows and reduce losses on farms.

Pre-insemination prediction of dystocia in dairy cattle

Dystocia or difficult calving in cattle is detrimental to the health of the afflicted cows and has a negative economic impact on the dairy industry. The goal of this study was to create a data-driven tool for predicting the calving difficulty of non-heifer cows using input variables that are known prior to the moment of insemination. Compared to past studies, we excluded input variables that can only be known during or after insemination, such as birth weight and gestation length. This makes the model suitable for informing mating decisions that could reduce the incidence of difficult calvings or mitigate their consequences. We used a dataset consisting of 131,527 calving records of Holstein cattle, from which we derived a total of 274 phenotypic features and estimated breeding values. The distribution of classes in the dataset was 96.7 % normal calvings, and 3.3 % difficult calvings. We used a gradient boosted trees (XGBoost) as the learning model and a bagging ensemble approach to deal with the extreme class imbalance. The model achieved an average area under the ROC curve of 0.73 on unseen test data. Using feature importance analysis, we identified a number of features that have a high discriminatory value for calving difficulty, including maternal and paternal breeding values, and past phenotypic measurements of the cow.