Joint Models to Predict Dairy Cow Survival from Sensor Data Recorded during the First Lactation.

Early predictions of cows' probability of survival to different lactations would help farmers in making successful management and breeding decisions. For this purpose, this research explored the adoption of joint models for longitudinal and survival data in the dairy field. An algorithm jointly modelled daily first-lactation sensor data (milk yield, body weight, rumination time) and survival data (i.e., time to culling) from 6 Holstein dairy farms. The algorithm was set to predict survival to the beginning of the second and third lactations (i.e., second and third calving) from sensor observations of the first 60, 150, and 240 days in milk of cows' first lactation. Using 3-time-repeated 3-fold cross-validation, the performance was evaluated in terms of Area Under the Curve and expected error of prediction. Across the different scenarios and farms, the former varied between 45% and 76%, while the latter was between 3.5% and 26%. Significant results were obtained in terms of expected error of prediction, meaning that the method provided survival probabilities in line with the observed events in the datasets (i.e., culling). Furthermore, the performances were stable among farms. These features may justify further research on the use of joint models to predict the survival of dairy cattle.

An end to endemic disease on farm?

The Animal Health and Welfare Pathway, which is set to launch in 2022, aims to reduce endemic disease in livestock by creating an all-encompassing approach to health and welfare, with vets at the heart. Here, Josh Loeb speaks to Jonathan Statham and Michael Seals about how this initiative will work.

High-throughput characterisation of bull semen motility using differential dynamic microscopy.

We report a high-throughput technique for characterising the motility of spermatozoa using differential dynamic microscopy. A movie with large field of view (∼10mm2) records thousands of cells (e.g. ≈ 5000 cells even at a low cell density of 20 × 106 cells/ml) at once and yields averaged measurements of the mean ([Formula: see text]) and standard deviation (σ) of the swimming speed, head oscillation amplitude (A0) and frequency (f0), and the fraction of motile spermatozoa (α). Interestingly, we found that the measurement of α is facilitated because the swimming spermatozoa enhance the motion of the non-swimming population. We demonstrate the ease and rapidity of our method by performing on-farm characterisation of bull spermatozoa motility, and validate the technique by comparing laboratory measurements with tracking. Our results confirm the long-standing theoretical prediction that [Formula: see text] for swimming spermatozoa.

Cattle veterinary services in a changing world.

In the first of a series of feature articles in Veterinary Record discussing the state of different sectors of the veterinary profession in the UK and what the future might hold, Jonathan Statham and Martin Green give their perspective on developments affecting the provision of cattle veterinary services.