The artificial vision system is a new technology used for the identification of nutritional deficiency in corn leaves, since the methodologies currently used for this purpose, it is not possible to correct the nutrient deficient in the same cycle of culture. The objective of this project is to see if the image processing for artificial vision system (AVS) is effective to diagnose symptoms of nitrogen (N) deficiency and potassium (K) in different hybrids of corn (Zea mays L.) grown in greenhouse, with nutritional deficiency induced to levels of N and K and subsequently grown in the field, aiming to validate the diagnosis of nutritional deficiency by SVA. The experiment is independent for each element and conducted in two steps: 1) in a greenhouse under hydroponic cultivation, the treatments will be in factor 3 (hybrid) x 4 (levels), with four repetitions, with the levels: 0, 20% , 100% and 200% of full dose, and 2) the field in randomized blocks in factorial 3 (hybrid) x 4 (levels of fertilization), and 4 blocks. Nutrient levels are: individual and complete omission of N and K, 50%, 100% and 200% of the recommended levels of the nutrient under study. Evaluations shall be performed in V4 stage of corn and dolled up, be certain growth parameters of maize, dry mass of plants and roots and the levels of macro and micronutrients. At these stages, they will be retrieved images indicative of the leaf of the stadium and the older leaves, which are processed by the SVA. At the end of the crop cycle assessments will be carried productivity and soil chemical analysis.
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