Machine Learning to Predict Pregnancy in Dairy Cows: An Approach Integrating Automated Activity Monitoring and On-Farm Data.

Automated activity monitoring (AAM) systems are critical in the dairy industry for detecting estrus and optimizing the timing of artificial insemination (AI), thus enhancing pregnancy success rates in cows. This study developed a predictive model to improve pregnancy success by integrating AAM data with cow-specific and environmental factors. Utilizing data from 1,054 cows, this study compared the pregnancy outcomes between two AI timings-8 or 10 h post-AAM alarm.

Milk and Fresh Cheese Quality of Crossbred Cows Supplemented with Phytogenic Additives and Managed under Thermal Stress.

This investigation aimed to assess the physiological parameters and quality of milk and fresh cheeses produced by cows that were housed in paddocks, either with or without shade, and supplemented with a phytogenic additive. Sixteen crossbred cows were allocated in a 4 × 4 Latin square design, dividing them into paddocks with or without shade, and providing or not providing a phytogenic additive in their feed. This resulted in a total of four treatment groups and sixteen experimental plots, each containing four animals, over four periods of 21 days.

Prediction of dry matter intake by meat sheep on tropical pastures.

This study was undertaken to determine whether equations for prediction of dry matter intake (DMI) by meat sheep are valid for animals raised solely on tropical pastures and to propose a new equation to predict the DMI of sheep raised on tropical pastures. The DMI prediction from published equations was evaluated by regressing the predicted and observed values, using the F test, for the identity of the parameters (β0 = 0 and β1 = 1) of the regression of predicted on observed data. If the null hypothesis is not rejected, the tested equation accurately estimates DMI.

Prediction of Carcass Traits of Santa Inês Lambs Finished in Tropical Pastures through Biometric Measurements.

The aim of this study was to predict carcass traits of Santa Inês lambs finished in tropical pastures by using biometric measurements. Data originated from two experiments involving 56 lambs (32 in experiment I and 24 in experiment II). In both experiments, the sheep were finished in that were finished in pastures of and , experiment I being conducted in the rainy season and experiment II in the dry season.