Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network-Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes.

The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions.

Machine learning models for predicting the use of different animal breeding services in smallholder dairy farms in Sub-Saharan Africa.

This study is concerned with developing predictive models using machine learning techniques to be used in identifying factors that influence farmers' decisions, predict farmers' decisions, and forecast farmers' demands relating to breeding service. The data used to develop the models comes from a survey of small-scale dairy farmers from Tanzania (n = 3500 farmers), Kenya (n = 6190 farmers), Ethiopia (n = 4920 farmers), and Uganda (n = 5390 farmers) and more than 120 variables were identified to influence breeding decisions. Feature engineering process was used to reduce the number of variables to a practical level and to identify the most influential ones.

Correlation of particular bacterial PCR-denaturing gradient gel electrophoresis patterns with bovine ruminal fermentation parameters and feed efficiency traits.

The influence of rumen microbial structure and functions on host physiology remains poorly understood. This study aimed to investigate the interaction between the ruminal microflora and the host by correlating bacterial diversity with fermentation measurements and feed efficiency traits, including dry matter intake, feed conversion ratio, average daily gain, and residual feed intake, using culture-independent methods. Universal bacterial partial 16S rRNA gene products were amplified from ruminal fluid collected from 58 steers raised under a low-energy diet and were subjected to PCR-denaturing gradient gel electrophoresis (DGGE) analysis.