Examinando por Autor "Gongora Bardales, Deiner Jhonel"

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Influence of agroclimatic factors on the efficiency of multi-ovulation in cattle in the Peruvian tropics
(Frontiers Media S.A., 2025-04-01) Segura Portocarrero, Gleni Tatiana; Murga Valderrama, Nilton Luis; Lopez Lapa, Rainer Marco; Saucedo Uriarte, José Américo; Gongora Bardales, Deiner Jhonel; Frias Torres, Hugo; Poclín Rojas, Annie Yoselin; Depaz Hizo, Benjamin; Vasquez Tarrillo, Ronald Will; Heredia Vilchez, Lizeth Amparo; Ampuero Trigoso, Gustavo
Introduction: Agroclimatic conditions are key determinants in the development of animal production and reproduction, with specific breed differences in vulnerability to environmental stress. This research aims to determine the influence of agroclimatic factors on the efficiency of multi-ovulation in cattle in the Peruvian tropics. Methods: The study was conducted at the “El Porvenir” Agricultural Experimental Station (EEA) of the National Institute of Agricultural Innovation (INIA), located in the district of Juan Guerra, province and department of San Martín, Peru. Throughout a year, four collections of structures were made from 12 Bos indicus donor cows from the genetic nucleus of the PROMEG Tropical project every 2 months under intensive breeding conditions. The cows were classified according to their production: milk (five individuals of the Gyr breed and two of the Guzerat breed) and meat (two individuals of the Nelore breed and three of the Brahman breed), with ages of 3 and 4 years, selected based on specific criteria: regular estrous cycles, no deformities or reproductive problems, and certified pedigree registration. During each collection protocol, the number of viable structures (blastocysts and morulas), non-viable structures (unfertilized oocytes-UFO and degenerated), and agroclimatic factors [temperature (°C), relative humidity (%), precipitation (mm), wind speed (m/s), and the Temperature-Humidity Index (THI)] were evaluated at three times (6 a.m., 1 p.m., and 6 p.m.). A longitudinal experimental design was used for the analysis. Statistical tests were applied, including ANOVA and post-hoc tests (Tukey's Test), to assess the significance of differences between variables, such as the humidity index and temperature in relation to the production of viable structures and non-viable structures. Data visualization was achieved using R Studio libraries, including ggplot2, factoextra, and FactoMineR. Results: The analyses highlight the influence of the interaction between humidity and temperature, resulting in THI on bovine stress, revealing complex interactions that primarily affect embryo production. Stress peaks, especially under adverse conditions, were observed to significantly impact animal health. Discussion: This response to stress can affect both overall well-being and productive performance. Additionally, it should be noted that this impact varies according to the adaptability and resilience of the breed. Therefore, it is suggested to continue this study, as the literature on this topic is limited, and to conduct further research to optimize the well-being and productivity of livestock.
Mathematical modeling of the germination and growth of Leucaena leucocephala under different substrates and nursery conditions
(Polish Society of Agricultural Engineering, 2026-05-28) Sauceo Uriarte, José Américo; Milla Pino, Manuel Emilio; Quispe Ccasa, Hurley Abel; Segura Portocarrero, Gleni Tatiana; Vásquez Pérez, Héctor Vladimir; Gongora Bardales, Deiner Jhonel; Maicelo Quintana, Jorge Luis
Livestock production in tropical regions is predominantly extensive and relies heavily on native or monoculture pastures, which often prove insufficient for ruminant nutrition. The incorporation of Leucaena leucocephala into silvopastoral systems represents a promising strategy due to its high forage quality; however, information on its early establishment under nursery conditions remains limited. This study aimed to model the germination dynamics and early seedling growth of L. leucocephala under different substrate compositions during the nursery phase. Germination percentage and daily plant height were recorded over a 30-day period. Treatment effects were evaluated using analysis of variance (ANOVA) and growth dynamics were described using non-linear sigmoidal models (Gompertz, Logistic, von Bertalanffy, and Brody). Significant differences in germination rate among substrates were detected (p<0.05), whereas no significant effect of substrate on plant height was observed during the evaluation period (p>0.05). Among the evaluated models, von Bertalanffy, Gompertz, and Logistic functions provided the best fit for plant height based on R² and AIC criteria. Although some models showed high R² values for germination, elevated AIC values suggest limited biological adequacy. These findings highlight the usefulness of predictive modeling to support nursery management decisions, optimize substrate selection, and facilitate the establishment of L. leucocephala in sustainable silvopastoral systems.