Examinando por Autor "Sessarego Dávila, Emmanuel Alexander"

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Characterization and typology of goat production systems in the Southern Highlands of Peru
(Veterinary World, 2025-01-29) Sessarego Dávila, Emmanuel Alexander; Trillo Zarate, Fritz Carlos; Godoy Padilla, David José; Palomino Guerrera, Walter; Cruz Luis, Juancarlos Alejandro
Background and Aim: Characterizing local animal production systems is crucial for sustainable livestock development. This study aimed to characterize the diversity of goat production systems in the Highlands of Chincha province, Ica, Peru. Materials and Methods: A structured questionnaire was used to gather data from 82 goat breeders in three districts: San Juan de Yanac, San Pedro de Huacarpana, and Chavín. Factor analysis of mixed data and hierarchical classification analysis were conducted to identify typologies of goat production systems using R version 4.4.2. Results: Four distinct goat production types were identified, primarily differentiated by feeding location and deworming frequency. Type 2 (41.5%) was the most prevalent, characterized by grazing on breeders own land, minimal milk production (<1 liter/day, 91.2%), and a focus on cheese and goat kid sales (70.6%). Breeders were predominantly women, with limited resources and extensive management systems. Across all types, mixed breeding was common, and economic reliance on livestock and agriculture prevailed. Conclusion: Despite their diversity, all goat production systems shared extensive management practices and resource constraints, resulting in low productivity. These findings highlight the need for targeted public policies to improve productivity and sustainability in goat farming within the Ica region.
Using biometric analysis to estimate body weight in Creole goats
(Eldaghayes Publisher, 2025-09-30) Trillo Zárate, Fritz Carlos; Paredes Chocce, Miguel Enrique; Salinas Marcos, Jorge; Temoche Socola, Víctor Alexander; Tafur Gutiérrez, Lucinda; Sessarego Dávila, Emmanuel Alexander; Acosta Granados, Irene Carol; Palomino Guerrera, Walter; Cruz Luis, Juancarlos Alejandro; Ruiz Chamorro, Jose Antonio
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 during training (R² = 0.765) and testing (R² = 0.707). However, it should be noted that RFR performed better with training data (R² = 0.942). Conclusion: The proposed predictive models have demonstrated significant potential for accurately predicting BW based on biometric data. Finally, it contributes to better selection, feeding, and sanitary management of Creole goats.