SheepEye: a based-web app for real-time diagnosis of sheep anemia.

is an extremely harmful blood-feeding nematode affecting small ruminants, leading to anemia, weight loss, and, in severe cases, animal death. Traditional methods of monitoring anemia in sheep, such as regular physical examinations by veterinarians and laboratory tests, can be expensive and time-consuming. In this work, we propose an anemia monitoring system that uses a web-based app.

Image analysis to automatically classify anemia based on Famacha score in sheep using ocular conjunctiva images.

is the most pathogenic blood-feeding parasitic in sheep, causing anemia and consequently changes in the color of the ocular conjunctiva, from the deep red of healthy sheep to shades of pink to practically white of non-healthy sheep. In this context, the Famacha method has been created for detecting sheep unable to cope with the infection by , through visual assessment of ocular conjunctiva coloration. Thus, the objectives of this study were (1) to extract ocular conjunctiva image features to automatically classify Famacha score and compare two classification models (multinomial logistic regression-MLR and random forest-RF) and (2) to evaluate the applicability of the best classification model on three sheep farms.

Classification Performance of Machine Learning Methods for Identifying Resistance, Resilience, and Susceptibility to Infections in Sheep.

This study investigated the feasibility of using easy-to-measure phenotypic traits to predict sheep resistant, resilient, and susceptible to gastrointestinal nematodes, compared the classification performance of multinomial logistic regression (MLR), linear discriminant analysis (LDA), random forest (RF), and artificial neural network (ANN) methods, and evaluated the applicability of the best classification model on each farm. The database comprised 3654 records of 1250 Santa Inês sheep from 6 farms. The animals were classified into resistant (2605 records), resilient (939 records), and susceptible (110 records) according to fecal egg count and packed cell volume.

Cluster analysis to explore additive-genetic patterns for the identification of sheep resistant, resilient and susceptible to gastrointestinal nematodes.

Infection caused by gastrointestinal nematodes is an important issue for animal health and production. Controlling worm infections improves the sustainability of the sheep industry. Genetic selection of animals that are resistant to gastrointestinal nematodes is another strategy to render sheep production more sustainable by decreasing the use of anthelmintics.

Expression of candidate genes for residual feed intake in tropically adapted Bos taurus and Bos indicus bulls under thermoneutral and heat stress environmental conditions.

The objectives of this study were to measure the relative expression of the ATP1A1, NR3C1, POMC, NPY, and LEP genes in Caracu (Bos taurus) and Nelore (Bos indicus) bulls submitted to feed efficiency tests at high environmental temperatures, and to evaluate differences in adaptability to tropical conditions between breeds. Thirty-five Caracu and 30 Nelore bulls were submitted to a feed efficiency test using automated feeding stations. At the end of the test, the animals were subjected to thermoneutral (TN) and heat stress (HS) conditions.