Examinando por Autor "Trillo Zárate, Fritz Carlos"

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Characterization of dairy goat production systems in coastal valleys of the Lima region
(Springer, 2024-10-23) Paredes Chocce, Miguel Enrique; Ramírez Vergara, Raúl Omar; Trillo Zárate, Fritz Carlos; Cruz Luis, Juancarlos Alejandro
Goat farming in Peru is a husbandry activity that, although it is considered secondary in the country, has a great economic and social impact on the rural population, that is why government efforts to develop is so important. The objective of this study was to characterize dairy goat rearing systems in the coastal valleys of the Lima region to identify gaps and opportunities for improvement. This cross-sectional research was conducted in four provinces located in the Lima region, Peru. A total of 62 goat farmers participated in the trial. For data collection, a standard survey was prepared with open and closed questions distributed across two components (socioeconomic and productive). The surveys were processed for qualitative variables using a multiple correspondence analysis (MCA) followed by a hierarchical cluster analysis (HCA) to differentiate the types of farming systems prevalent based on the survey population. The hierarchical cluster analysis resulted in the formation of three separate groups of goat farmers, which can be classified as extensive systems differentiated by management practices and their production and marketing objectives. The test showed a significant difference; therefore, it can be affirmed that they are associated with the groups or clusters formed. These results will allow actors related to goat farming, such as state and regional entities, to focus efforts on addressing specific demands of the different types of goat farmers found in this study.
Production and nutritional value of milk from Creole goats fed with different levels of sweet potato vine flour (Ipomoea batata)
(Network for the Veterinarians of Bangladesh, 2026-06-22) Trillo Zárate, Fritz Carlos; Sessarego Davila, Emmanuel Alexander; Acosta Granados, Irene Carol; Ruíz Chamorro, José Antonio; Rodríguez Vargas, Aníbal Raúl; Cruz Luis, Juancarlos Alejandro
Objectives: In South America, goats largely depend on natural pastures, which often lack adequate nutrition. This innovative study ventured into uncharted areas by examining the potential of incorporating sweet potato vine flour (SPVF) into goat diets, specifically focusing on its effects on both the quantity and quality of milk produced. Materials and Methods: A carefully monitored cohort of twelve female Creole goats, aged between 2 and 3 years, participated in a sophisticated completely randomized factorial design study. The research assessed varying levels of SPVF inclusion—spanning from the control group to significant incorporations of 2.5%, 5.0%, and 7.5%—observed meticulously over an eight-week period. Results: The primary variables under detailed examination included daily milk yield, body weight, and milk quality. The latter underwent precise evaluation utilizing the advanced Milko Scan “FOSS”. Notably, the highest milk yield of 411 ± 7.92 ml/day was recorded at the 7.5% flour inclusion level, resulting in a statistically significant increase (p < 0.05) compared to the control group. Interestingly, an inclusión level of just 2.5% significantly enhanced the protein content to 3.84 ± 0.0159% and increased lactose levels to 4.54 ± 0.108%, with significant deviations in protein levels observed (p < 0.05). Conclusions: SPVF improved milk production, but over 5% altered nutrition. Replacing corn with discarded sweet potato tubers is key for boosting milk production for small-scale goat farmers in Perú.
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.