Examinando por Autor "Taboada Mitma, Víctor Hugo"

Mostrando 1 - 3 de 3

Desempenho e valor nutricional da forragem hidropônica de cevada verde na alimentação de porquinhos-da-índia
(Revista Acadêmica Ciência Animal, 2025-02-03) Taboada Mitma, Víctor Hugo; Sarria Bardales, José Antonio; Cruz Luis, Juancarlos Alejandro; Huamaní Bedoya, Daniel; Buendía Molina, Marilyn Aurora
O objetivo do estudo foi avaliar o desempenho e o valor nutricional da forragem verde hidropônica de cevada (FVH) na alimentação de cobaias, além de comparar diferentes sistemas de alimentação para determinar seu efeito no crescimento, conversão alimentar, mortalidade e desempenho de carcaça de porquinhos-da-índia. Utilizou-se delineamento inteiramente casualizado e teste de Duncan a 5%. Utilizaramse 100 cobaias machos com 14 ± 5 dias, distribuídos em cinco tratamentos (T1: concentrado; T2: FVH; T3: chala; T4: concentrado + FVH; T5: concentrado + chala), com cinco repetições. O peso, ganho de peso, consumo de ração, conversão alimentar e percentagem de carcaça foram avaliados durante 49 dias. O ganho de peso por dia em T4 (16,11 g), T1 (15,95 g) e T5 (15,65 g) foi significativamente maior do que o obtido em T2 (5,51 g) e T3 (4,95 g) (p < 0,05). T5 e T4 apresentaram os maiores consumos de ração em base seca (3538,9 e 3239,9 g, respectivamente; p < 0,05), seguidos por T1 (2973,4 g). As melhores conversões alimentares foram apresentadas em T1 (3,81), T4 (4,11) e T5 (4,63), e as cobaias de T5 (74,79%), T4 (74,26%) e T1 (73,66%) obtiveram as maiores porcentagens de carcaça (p < 0,05). Em conclusão, o sistema de alimentação integral e misto tem uma influência positiva sobre os parâmetros produtivos.
Integration of agronomic information, vegetation indices (VIs), and meteorological data for phenological monitoring and yield estimation of rice (Oryza sativa L.)
(Elsevier, 2025-07-15) Fernandez Jibaja, Jorge Antonio; Atalaya Marin, Nilton; Álvarez Robledo, Yeltsin Abel; Taboada Mitma, Víctor Hugo; Cruz Luis, Juancarlos Alejandro; Tineo Flores, Daniel; Goñas Goñas, Malluri; Gómez Fernández, Darwin
Rice (Oryza sativa L.) is a staple crop for sustaining global food security and is particularly important in tropical and subtropical regions. In this context, precision agriculture enables more efficient crop management to increase productivity and sustainability. This study proposes an integrated framework for monitoring the phenological development and estimating the yield of O. sativa by combining agronomic variables, vegetation indices (VIs), and meteorological data. Six rice varieties (Victoria, Esperanza, Bellavista, Puntilla, Capoteña, and Valor) were evaluated across six phenological stages using field data, 20 VIs and meteorological parameters. Field data revealed greater tillering of the Puntilla and Valor varieties (9–28 tillers), with Esperanza having the most stable chlorophyll values (21.5–38.7, σ = 10.46) during ripening. The temporal dynamics of the VIs consistently increased from the seedling to inflorescence emergence stage, followed by a decrease during flowering and ripening, which aligns with known physiological transitions in rice; however, significant differences in the NDVI index were detected during ripening (p > 0.05). For yield estimation, feature selection was performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) to increase model efficiency and interpretability. Among the regression algorithms tested, support vector regression (SVR) demonstrated the highest predictive accuracy (R² = 0.81) for the Bellavista variety at the maximum tillering stage. Furthermore, the Valor variety presented the highest grain yield (13.70 t/ha). These results underscore the potential of integrating multisource data with machine learning techniques for high-resolution phenological monitoring and varietal performance assessment.
Sustainable rice–fish farming systems: a systematic review and meta‐analysis
(John Wiley & Sons Ltd., 2025-06-12) Fernández Zatrate, Franklin Hitler; Pérez Delgado, Luis Jhoseph; Coronel Bustamante, David; Huanca Silva, Leisy; Taboada Mitma, Víctor Hugo; Quispe Carhuapoma, Mariela Judith; Oliva Alvarez, Yashira Steffani; Ramirez Antaurco, Maximo Fabricio; Anchayhua Torres, Janella Jelyn; Huaccha Castillo, Annick Estefany; Seminario Cunya, Alejandro; Tineo Flores, Daniel; Gomez Fernandez, Darwin; Goñas Goñas, Malluri; Cruz Luis, Juancarlos Alejandro
The rice–fish farming system is an efficient ecological model with economic, ecological, and social benefits, reduces environmental impacts and optimizes the use of resources. The objective of the research was to explore and analyze scientific publications through a systematic review and meta-analysis related to rice–fish intercropping. A review of publications hosted in the Scopus and PubMed database from January 2000 to April 2025 was conducted. Research articles were selected, excluding review articles, com-mentaries, book chapters, and letters, and only documents published in English were analyzed. The analysis shows that the countries with the highest number of publications were China and Bangladesh, with a proportion of 48% and 24% respectively, followed by Thailand with 10% and Pakistan, Indonesia, Malaysia, and India with 5% each. The fish species used in rice–fish systems were reported to be Cyprinus carpio (37%), Oreochromis niloticus (29%), Barbonymus gonionotus, Micropterus salmoides and Pelteobagrus fulvidraco (8%), Amblypharyngodon mola (5%), and Labeo rohita and Monopterus albus (3%). On average, fish settle in the rice–fish system 27 days after rice planting, with a density of 13,390 fish/ha. Between rice planting and harvesting 132 days pass, obtaining an average yield of 4397 kg of rice/ha and 1383 kg of fish/ha. It is recommended to prioritize integrated research on unstudied fish species, optimal densities, fertilization, culture models, and emerging technologies in rice–fish systems, considering regional variations to improve sustainability, productivity, and food security at a global level.