OBJECTIVE This study aimed to report the impact of production practices and sanitary management on the prevalence of Neospora caninum (N caninum) and bluetongue virus (BTV) in Creole goats from the tropical dry forest of Utcubamba, Peru. METHODS 354 blood samples were obtained from male and female goats of diverse ages reared under an extensive productive system. The diagnosis of N caninum and BTV was conducted through a commercial ELISA kit (iD.vet) with readings taken on a Bio-Rad iMark microplate reader at 450 nm. Additionally, a survey was conducted with 18 goat producers to categorize them based on social, technical (production, health, reproduction, nutrition, and infrastructure), environmental, and economic factors. RESULTS The overall seroprevalence of N caninum and BTV in goats was 6.21% and 7.06%, respectively, Notably, group II farmers had the highest prevalence rates at 7.69%...

Goats are an important component of smallholder family farms along the coast and highlands of Peru. The weight of an animal is an important indicator of the production and economy of farmers in rural areas. Therefore, this study aimed to develop predictive models for Body Weight (BW) using Morphometric Measurements (MM) of Creole goats (Capra hircus) in Perú. BW and five MM were collected from 356 goats from the coast and highlands of Peru. Variables were analyzed using correlation and stepwise regression analysis to select the best model based on the coefficient of determination (r²), adjusted r², Residual Standard Error (RSE), and Akaike Information Criterion (AIC) using the RStudio statistical software. The highest correlation was found between BW and TG (0.76), followed by RW (0.67), and RH (0.65). The combinations of MM selected as predictors of BW by stepwise regression were TG,...

Background: Creole goat husbandry for milk and meat improves food security in rural areas in Perú. Body weight (BW) is a key trait for selecting breeding stock, and it is estimated to be using algorithms. Likewise, BW is common in livestock farming. Aim: This study aimed to compare BW prediction models using a data mining algorithm in Creole goats, considering their biometric measurements. Methods: Data from 1,075 females aged between 1 and 4 years were used. Measurements of chest width, thoracic perimeter, wither height, sacrum height, rump width and length, body length, cannon bone perimeter, age, and region of the herd were recorded. The regression trees (classification and regression tree), support vector regression (SVR), and random forest regression (RFR) algorithms were used. Results: The SVR was better at predicting BWs in Creole goat herds. Similarly, the results were stable du...