Examinando por Autor "Acosta Granados, Irene Carol"

Mostrando 1 - 3 de 3

Morphometric and phaneroptic characteristics of creole goats in the dry forest of Peru
(UNEMAT, 2025-04-21) Acosta Granados, Irene Carol; Carrero Flores, Jhonatan Enrique; Acosta Vidaurre, Rogelio; Cruz Luis, Juancarlos Alejandro; Ruíz Chamorro, José Antonio
The study aimed to describe morphometric and phaneroptic parameters in goat herds from the northern region of Lambayeque, Peru. A total of 295 goats over two years old, without evidence of crossbreeding with specialized breeds, were used. For each animal, 19 morphometric and eight phaneroptic measurements were recorded, and zoometric indices were calculated using a scale, measuring tape, and zoometric stick. This was performed using R software version 4.3.1. The results showed an average live weight of 41 ± 7.5 kg and a proportionality index of 99.6, highlighting their suitability for meat or dual-purpose production (IDT: 13.4, ICO: 88.7), adapted to the local environment. Regarding phaneroptic characteristics, monochromatic coat colors predominated in 55.6% of the animals, 43.7% were hornless (72.7% of the horns observed were parallel), 20.7% had beards, and 10.5% presented wattles. Additionally, 14.7% had supernumerary teats, and 46% of males displayed testicular bifurcation. In conclusion, the Creole goat of the Dry Forest in northern Peru is medium-sized, with robust limbs and a meat-production aptitude, as reflected by the proportionality index. It is also characterized by predominantly dark coats and parallel horns when present. These features demonstrate their adaptation to this environment and their potential for meat production.
Short Communication: Prediction of body weight using morphometric measurements in Creole goats from Peru
(Society for Indonesian Biodiversity, 2025-07-15) Paredes Chocce, Miguel Enrique; Sessarego Davila, Emmanuel Alexander; Tafur Gutierrez, Lucinda; Temoche Socola, Victor Alexander; Salinas Marco, Jorge; Acosta Granados, Irene Carol; Ruiz Chamorro, Jose Antonio; Cruz Luis, Juancarlos Alejandro; Trillo Zarate, Fritz Carlos
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, RH, and RW, with r² 0.640. The selected candidate model met all established tests and, upon validation, reached an r² of 0.66 (p<0.001), indicating that the model can adequately predict the BW of Peruvian Creole goats and serve as a practical tool to support selection programs, feeding strategies, and market decision-making in smallholder systems.
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.