Adjusting the timing of inseminations to the time lag on luteolysis alerts results in higher conception in dairy cattle.

Dairy cow fertility is a complex trait that depends on the cow's physiological status, the farm's environmental and management conditions, and their interactions. Already the slightest improvement in fertility can positively impact a farm's profitability and sustainability. In research, milk progesterone (P4) has often been used as an accurate and feasible way to identify a dairy cow's reproduction status.

PROSAC as a selection tool for SO-PLS regression: A strategy for multi-block data fusion.

Background: Spectral data from multiple sources can be integrated into multi-block fusion chemometric models, such as sequentially orthogonalized partial-least squares (SO-PLS), to improve the prediction of sample quality features. Pre-processing techniques are often applied to mitigate extraneous variability, unrelated to the response variables. However, the selection of suitable pre-processing methods and identification of informative data blocks becomes increasingly complex and time-consuming when dealing with a large number of blocks.

Added Value of Sensor-Based Behavioural Monitoring in an Infectious Disease Study with Sheep Infected with .

Sensor technologies are increasingly used to monitor laboratory animal behaviour. The aim of this study was to investigate the added value of using accelerometers and video to monitor the activity and drinking behaviour of three rams from 5 days before to 22 days after inoculation with . We computed the activity from accelerometer data as the vectorial dynamic body acceleration (VDBA).

Comparison of 3 mathematical models to estimate lactation performance in dairy cows.

Milk yield dynamics and production performance reflect how dairy cows cope with their environment. To optimize farm management, time series of individual cow milk yield have been studied in the context of precision livestock farming, and many mathematical models have been proposed to translate raw data into useful information for the stakeholders of the dairy chain. To gain better insights on the topic, this study aimed at comparing 3 recent methods that allow one to estimate individual cow potential lactation performance, using daily data recorded by the automatic milking systems of 14 dairy farms (7 Holstein, 7 Italian Simmental) from Belgium, the Netherlands, and Italy.

Near-infrared spectra dataset of milk composition in transmittance mode.

Monitoring of milk composition can support several dimensions of dairy management such as identification of the health status of individual dairy cows and the safeguarding of dairy quality. The quantification of milk composition has been traditionally executed employing destructive chemical or laboratory Fourier-transform infrared (FTIR) spectroscopy analyses which can incur high costs and prolonged waiting times for continuous monitoring. Therefore, modern technology for milk composition quantification relies on non-destructive near-infrared (NIR) spectroscopy which is not invasive and can be performed on-farm, in real-time.