Examinando por Materia "Vegetables"

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Guía técnica de cultivos hidropónicos
(Instituto Nacional de Innovación Agraria, 2023-11-30) Ingar de la Cruz, Luis Martín; Toledo Choquehuanca, José Jesús Martin; Quispe Condori, Adolfo; Andrés Orizano, Juan Álvaro; Ortiz Morera, Narda Cecilia; Ramírez Rojas, Max Augusto; Macavilca Villar, Pedro Miguel; Solórzano Acosta, Richard Andi; Cruz Luis, Juancarlos Alejandro
El Ministerio de Desarrollo Agrario y Riego (MIDAGRI), a través del Instituto Nacional de Innovación Agraria (INIA), pone a disposición de los productores, técnicos, conservacionistas, profesionales e investigadores, la presente guía "Guía técnica de cultivos hidropónicos". El documento tiene como finalidad orientar de una manera práctica a la población peruana en el uso de la hidroponía como una técnica de producción agrícola para contribuir con la seguridad alimentaria; además de promoverla como una alternativa de emprendimiento.
Módulos hidropónicos en fitotoldos para la producción de hortalizas
(Instituto Nacional de Innovación Agraria (INIA), 2023-10-25) Ingar de la Cruz, Luis Martín; Toledo Choquehuanca, José Jesús Martín; Cruz Luis, Juancarlos Alejandro; Ortiz Morera, Narda Cecilia; Ramirez Rojas, Max Augusto; Quispe Condori, Adolfo; Andrés Orizano, Juan Alvaro
El presente documento informa sobre los materiales, las etapas de producción, los tipos de módulos y beneficios de los "Módulos hidropónicos en fitotoldos para la producción de hortalizas".
Yield estimation based on agronomic traits in vegetables under different biochar levels
(Elsevier B.V., 2025-09-29) Ccopi Trucios, Dennis; Requena Rojas, Edilson Jimmy; Arias Arredondo, Alberto; Taipe Crispin, Maglorio; Marcelo Matero, Jhonny Demis; Pizarro Carcausto, Samuel Edwin
Biochar, a carbon-rich material produced through oxygen-limited pyrolysis of organic biomass, demonstrates exceptional potential as a soil amendment due to its porous structure and stability. This research investigated the impact of guinea pig manure biochar on three vegetable species cultivated in high Andean conditions: spinach (Spinacia oleracea L.), cabbage (Brassica oleracea var.), and chard (Beta vulgaris var.). The study implemented four biochar application rates (0, 10, 20, and 30 t/ha) and measured comprehensive agronomic parameters including leaf count, leaf length, and fresh/dry biomass of both leaves and roots. Simultaneously, UAV-captured multispectral imagery provided spectral indices that were integrated with agronomic data into machine learning models: linear regression, support vector machines (SVM), and regression trees (CART). Results demonstrated significant vegetative growth enhancement and yield increases across all crops, with the 30 t ha-1 application rate producing optimal outcomes. Predictive modeling exhibited remarkable accuracy: spinach analysis via SVM achieved R² = 0.94 and RMSE = 0.32 g; chard analysis through CART delivered R² = 0.92 and RMSE = 0.35 g; and cabbage assessment using CART yielded R² = 0.91 and RMSE = 0.38 g. This research substantiates biochar’s effectiveness as an organic amendment while establishing a reliable framework for crop yield prediction using machine learning algorithms integrated with spectral data. These findings position biochar as a valuable component in sustainable agricultural systems, particularly for vegetable production in challenging high-altitude environments.