Digital technologies in dairy cattle breeding to improve the reproductive function of cows and heifers: A case study in Northern Kazakhstan.

Background And Aim: In some countries, the application of digital technologies in dairy cattle breeding is still under development. This study aimed to investigate the use of digital technologies in dairy cattle breeding to improve the reproductive function of cows and heifers in three northern regions of Kazakhstan.

Materials And Methods: This study explores the application of Austrian smaXtec bolus sensors, which enable the daily monitoring of the reproductive functions of cows and heifers in livestock.

Predicting the body weight of crossbred Holstein × Zebu dairy cows using multivariate adaptive regression splines algorithm.

This study aimed to estimate live body weight from body measurements for Holstein × Zebu dairy cows ( = 156) reared under conditions of humid tropics in Mexico using multivariate adaptive regression splines algorithm (MARS) with several train-test proportions. The body measurements included withers height, rump height, hip width, heart girth, body length and diagonal body length. The data were divided into 65:35, 70:30 and 80:20 split data for training and testing sets, respectively.

The influence of productivity indicators on the culling of dairy cows in the sharply continental climate of Kazakhstan.

This article presents the results of the culling of cows of the Simmental and Holstein breeds in the Republic of Kazakhstan. The purpose of the research was to study the actual number of culled cows of dairy productivity in the farms of the Republic of Kazakhstan to determine its norm. The object of research were cows of Simmental (18,462 heads) and Holstein (17,862 heads) breeds in various regions of the republic.