Desarrollo de sistemas instrumentales para el diagnóstico nutricional de plantas y suelos en campo
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Abstract
The growing global demand for food requires improved agricultural productivity and the efficient use of fertilizers, which excessively applied may possess environmental concerns. To stimulate the local development of systems to support the rational use of fertilizers, this research presents two preliminary open-source instrumental developments for crops nutritional diagnosis. The first is a 3D printing prototype coupled to a smartphone's ambient light sensor, which was evaluated to estimate the chlorophyll content in oil palm leaves (Elaeis guineensis Jacq), potato (Solanum tuberosum; L.), coffee (Coffea arabica L.), cocoa (Theobroma cacao L.), and kikuyu grass (Pennisetum clandestinum Hochst. ex Chiov.). This device presented a performance comparable to chlorophyll measurements taken with a SPAD 502™ meter or a spectrophotometer, used here as comparison gold standards. A system for analyzing nutrients based on multispectral images of leaf samples is also presented. Statistical models for leaf nutrient estimation based on light bands reflection by dried samples of cocoa (Theobroma cacao L.), rubber (Hevea brasiliensis), chrysanthemum (Dendranthema grandiflorum) and banana (Musa paradisiaca L.) indicated a reasonable estimate of 11 nutrients, with a coefficient of determination greater than 0.84 for nitrogen, phosphorous and potassium, along with a lower performance to estimate other nutrients. Not without the drawbacks tied to incipient yet open prototyping, these results are expected to stimulate the local development of technologies for less developed regions, which support the efficient use of fertilizers and agricultural productivity. Increased access to these open-source technologies would promote digital agriculture and local instrument development.
Palabras clave propuestas
Análisis de plantas; imágenes multiespectrales; hardware abierto; agricultura digital; sensores de teléfonos inteligentes; impresión 3D en agricultura; monitoreo de cultivos; Plant analysis; multispectral imaging; open hardware; digital farming; Smartphone sensors; 3D printing in agriculture; Crop sensingo
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ilustraciones, diagramas, fotografías