Examinando por Autor "Tafur Gutiérrez, Lucinda"

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Characterization of goat production systems in the Amazonian dry tropical forest of Peru through multivariate analysis
(Frontiers, 2025-10-21) Rodríguez Vargas, Aníbal Raúl; Tafur Gutiérrez, Lucinda; Sessarego Davila, Emmanuel Alexander; Alva Tafur, Gudelio; Castañeda Palomino, Katherine Milagros; Haro Reyes, José Antonio; Ruiz Chamorro, José Antonio; Barrantes Campos, Cecilio; Cruz Luis, Juancarlos Alejandro
The study aimed to characterize goat production systems in the tropical dry forest of Peru through multivariate analysis of 25 socioeconomic and productive variables in 60 producers from Bagua Grande, El Milagro, Cajaruro, and Cumba. Descriptive analysis, multidimensional scaling (stress = 0.03272), categorical principal component analysis (CATPCA), and hierarchical clustering analysis (HCA) were applied. A predominance of extensive management (98.3%), with low technical assistance (81.7%), absence of irrigation (90%), and visual selection of animals (100%) was identified. Marketing responds to immediate economic needs (36.7%), while vaccination coverage is poor (88.3% not vaccinated). CATPCA explained 54.5% of the variance (Cronbach's alpha = 0.965), highlighting producer education, infrastructure, and access to water and energy as key factors for improving production efficiency and mitigating commercial seasonality. HCA identified two goat production systems: the improved extensive system (EES) and the traditional extensive system (TES). The EES grouped older and more experienced producers, with larger herds, higher sales weights, greater specialization, forage diversification, better infrastructure, and higher deworming frequency. In contrast, the TES included younger producers with smaller herds, lower sales weights, lower educational levels, agricultural dependence, less forage diversity, limited infrastructure, and limited sanitary measures. These differences highlight the impact of knowledge and technological development on productive sustainability. It is concluded that technological development, access to resources, and production experience are key to improving the efficiency and sustainability of goat systems in the tropical dry forests of Peru.
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.