چکیده (انگلیسی):

The leaf analysis in a crop can present the need of a nutrient determined in the plant. The macronutrients
deficiency in the cotton crop can be identified by specific type of colors variation by leaves images. Early
identification of macronutrients deficiency can help in the growing suitable of the crop and reduce the use
of agricultural inputs. This study investigates the image segmentation of the cotton leaves with deficiency of
the phosphor. The segmentation is performed by difference of leaf pigmentation, according with the pattern
related to macronutrient type in deficit and the cultivate. The image segmentation is made by an artificial
neural network and the Otsu method. The results show satisfactory values with an optimized artificial neural
network and better than the Otsu method. The results are presented by images and distinct parameters of
quality analysis in the segmentation.