Open Access7 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: C3857098319/19©BEIESP DOI:10.35940/ijrte.C3857.098319 Journal Website: www.ijrte.org An Effect of Nutrient Deficiency on Yield Estimation
Author(s) -
Sushila Shidnal,
Mrityunjaya V. Latte
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c3857.098319
Subject(s) - segmentation , yield (engineering) , agricultural engineering , phosphorus , agriculture , nutrient , crop , potassium , nitrogen , image segmentation , crop yield , market segmentation , agronomy , computer science , environmental science , mathematics , artificial intelligence , business , ecology , chemistry , biology , engineering , materials science , organic chemistry , marketing , metallurgy
By taking corrective measures to improve the farming quality, agricultural sector need a thoroughly explained and systematic theory for crop yield prediction. Any yield of the crop is usually depending on the crop unhealthy and healthy conditions. These conditions mainly occur due to major nutrients like nitrogen, Phosphorus and Potassium (NPK). Nitrogen deficiency will make the fields in some parts look Yellowish. Potassium deficiency may lead to have spots in the leaf and Phosphorous will make the fields some part look brownish. Hence segmenting this defected area is the major challenge to evaluate the total yield in the input paddy field image. The proposed model focus on segmentation of these regions using an efficient hierarchical model. This model uses segmentation methods like FCM and Color segmentation techniques there by improving the accuracy of the system and comparing with the ground truth values