Examinando por Autor "Zagaceta, Luis H."

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Agronomic and nutritional evaluation of INIA 910—Kumymarca ryegrass (Lolium multiflorum Lam.): An alternative for sustainable forage production in department of Amazonas (NW Peru)
(MDPI, 2025-01-01) Vásquez, Héctor V.; Valqui, Leandro; Bobadilla, Leidy G.; Meseth Macchiavello, Enrique; Trigoso, Milton J.; Zagaceta, Luis H.; Valqui Valqui, Lamberto; Saravia Navarro, David; Barboza, Elgar; Maicelo, Jorge L.
Grassland ecosystems cover about 25% of the Earth’s surface, providing essential ecosystem services that benefit nature, people, and food security. This study evaluated agronomic and nutritional parameters of ryegrass (Lolium multiflorum Lam.) based on fertilization levels and cutting frequency in the Amazonas department. The INIA 910—Kumymarca variety was used with nitrogen fertilization rates (0, 60, 120, 180 kg/ha) and cutting intervals of 30 and 45 days for agronomic traits and 30, 45, and 60 days for nutritional traits. A randomized complete block design with eight treatments and three replications was applied. Repeated measures analysis and Tukey’s mean comparison tests (p < 0.005) were performed, along with Pearson correlation and response surface analysis using the central composite design in R. The results showed that applying 180 kg/ha of nitrogen with a 45-day cutting interval provided the highest dry matter yield (460 kg/m2 ) and superior agronomic traits, including plant height (96.73 cm), number of tillers, and stem diameter. Non-fertilized treatments had the highest crude protein content (17.45%) and digestibility, while higher nitrogen doses increased crude fiber and acid detergent fiber, reducing digestibility. Significant correlations were observed between fresh and dry weight with plant height (p = 0.000; r = 0.84), fiber contents (p = 0.000; r = 1), and ash and protein content (p = 0.000; r = 0.85). The optimal management practice was cutting every 45 days with 180 kg/ha of nitrogen (T8), maximizing forage yield and quality. Proper fertilization and cutting management can improve ryegrass production, benefiting livestock feeding and rural economies.
Cloud computing application for the analysis of land use and land cover changes in dry forests of Peru
(International Information and Engineering Technology Association (IIETA), 2024-09-30) Barboza, Elgar; Salazar Coronel, Wilian; Gálvez Paucar, David; Valqui Valqui, Lamberto; Valqui, Leandro; Zagaceta, Luis H.; Gonzales, Jhony; Vásquez, Héctor V.; Arbizu, Carlos I.
Dry forests are ecosystems of great importance worldwide, but in recent decades they have been affected by climate change and changes in land use. In this study, we evaluated land use and land cover changes (LULC) in dry forests in Peru between 2017 and 2021 using Sentinel-2 images, and cloud processing with Machine Learning (ML) models. The results reported a mapping with accuracies above 85% with an increase in bare soil, urban areas and open dry forest, and reduction in the area of crops and dense dry forest. Protected natural areas lost 2.47% of their conserved surface area and the areas with the greatest degree of land use impact are located in the center and north of the study area. The study provides information that can help in the management of dry forests in northern Peru.