Examinando por Autor "Salinas Marcos, Jorge"

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Endozoochory by Goats and White-Tailed Deer: Type of Ruminant Affect Recovery and Germination of Neltuma pallida Seeds
(Preprints.org / MDPI, 2025-11-25) Salinas Marcos, Jorge; Cruz Luis, Juancarlos Alejandro; Aguirre, Lucrecia
The "algarrobo", Neltuma pallida is a key tree species in the seasonally dry tropical forests in Equatorial Pacific South America, currently at risk. Its regeneration depends on endozoochorous seed dispersal, in which seeds are ingested and later defecated by animals, helping to release and scarify them. This study compared the role of the native white-tailed deer (Odocoileus virginianus) and the introduced goat (Capra hircus) in seed dispersal. Seeds were recovered from the dung of both species after experimental feeding and from free-ranging goats grazing in fruiting N. pallida forests. Seed recovery was higher in deer dung (9.4%) than in goat dung (3.1%). Retention time was also shorter in deer (peak at 48 hours) than in goats (peak at 84 hours). Only deer scarification significantly improved germination percentage (Tukey test, p < 0.001) and germination speed (T25 = 8.98 days). Goats reduced germination speed under experimental conditions (T25 = 19.25 days), but slightly improved it under forest conditions (T25 = 12.81 days). These differences are attributed to the morphophysiological traits of each species. Although goats did not enhance overall germination, they maintained it at ~44% and contributed to seed dispersal and dormancy release.
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.