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Estimation of Chlorophyll Content in Papaya Leaf using Mathematical Operations
IJCA Proceedings on Machine Learning: Challenges and Opportunities Ahead
© 2014 by IJCA Journal
MLCONF
Year of Publication: 2014
P.karthika, R.hemakarthika, Jaya Chandra and E.joicerathinam. Article: Estimation of Chlorophyll Content in Papaya Leaf using Mathematical Operations. IJCA Proceedings on Machine Learning: Challenges and Opportunities Ahead MLCONF:6-11, April 2014. Full text available. BibTeX
@article{key:article,
author = {P.karthika and R.hemakarthika and Jaya Chandra and E.joicerathinam},
title = {Article: Estimation of Chlorophyll Content in Papaya Leaf using Mathematical Operations},
journal = {IJCA Proceedings on Machine Learning: Challenges and Opportunities Ahead},
year = {2014},
volume = {MLCONF},
pages = {6-11},
month = {April},
note = {Full text available}
}
Abstract
Leaf color is used as a guide for assessments of nutrient status and plant's health. So that a new method is proposed for the detection of Chlorophyll content based on the leaf color. Based on green color present in leaf we can estimate the chlorophyll content in leaf. The proposed equation produced superior results with the true value of chlorophyll content measured in the laboratory compared with existing methods when applied in three types of papaya leaf (dry leaf, Tender leaf, healthy leaf).
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