NITROGEN DEFICIENCY CALCULATION OF LEAVES USING ARTIFICIAL NEURAL NETWORK

Abstract

In this proposed work, we are estimating the nitrogen content and calculating the nitrogen deficiency in pomegranate leaves. We collect different Nitrogen deficient leaves. We had measured the chlorophyll content of the collected leaves. We captured the images of collected leaves under the closed environment. These leaves are sent to the chemical analysis for the nitrogen estimation. Extracting the statistical features of images and creating the database. The captured images are compared with database and then find the nitrogen deficiency of leaf. For irrigated crops, plant analysis can be used as an aid in making decisions about nutrient applications such as nitrogen and some micronutrients. One example is petiole testing in irrigated potatoes. Nitrate nitrogen levels in the potato petiole are determined weekly, and the information is used to help make nitrogen fertilization decisions all season long. Plant analysis is also used in fruit and vegetable crops as a guide for nutrient application during the season.