Universidad Nacional Agraria La Molina. Escuela de Posgrado. Maestría en Producción Animal

Introduction: Tithonia diversifolia, also known as Mexican sunflower, is a tropical shrub with high forage potential, but limited information exists on the optimal harvest stage to balance yield and nutritional value. Methods: A 3 × 3 factorial design was implemented under tropical dry forest conditions in northern Peru, combining three regrowth stages (30, 45, and 60 days) with three plant fractions (leaf, stem, and leaf–stem mixture), with four replicates per treatment. Agronomic traits, dry matter yield, proximate composition, and in vitro dry matter digestibility (IVDMD) were evaluated. Results: Biomass yield increased significantly with harvest age, reaching 11.93 kg fresh weight and 3.45 kg dry matter per plant at 60 days, although with reduced nutritional quality due to a higher stem proportion. Leaves harvested at 30 days had the highest crude protein (16.5%) and soluble carbo...

Endoparasitosis is a critical health challenge in the management of Creole goats under extensive production systems due to its negative impact on animal health and productivity. This study determined the occurrence of endoparasites and identified associated risk factors in Creole goats from the southern coast of Peru. Fecal samples were collected from 129 goats in two localities of the Pisco province to detect the presence of oocysts from Eimeria spp. and eggs from trichostrongyles, Skrjabinema spp., Trichuris spp., and Fasciola hepatica. Data were analyzed using logistic regression models and adjusted through bootstrapping and stepwise selection methods, with locality, feeding type, age, and body condition as predictive variables. The results revealed a high occurrence of Eimeria spp. (86.0%) and trichostrongyles (65.1%), while Fasciola hepatica (14.0%) and Skrjabinemaspp. (7.0%) were e...

Creole goats have adapted to the harsh Andean environment, yet the physiological impacts of high-altitude production systems remain underexplored. This study assessed seasonal and dietary influences on the hematological and biochemical profiles of 45 Creole goats in the Peruvian Andes. The animals were assigned to three diets: D1 (grazing), D2 (grazing + 2000 g hay), and D3 (grazing + 400 g concentrate), across rainy and dry seasons. Biweekly blood sampling measured urea, cholesterol, total protein, albumin, ALP, ALT, WBCL, NeuP, LymP, HGB, and MCV. Season exerted the strongest influence (p < 0.001), with modest dietary effects and a consistent effect of sampling time. Urea, total protein, and albumin increased during the rainy season, though only urea responded significantly to diet. Leukocytosis rose in the dry season and with higher-protein diets, suggesting heightened immune activati...

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...