An Analysis of Leaf Chlorophyll Measurement Method using Chlorophyll Meter and Image Processing Technique

A regular and periodic monitoring of crop health is essential in any cultivation. An important parameter which act as indices of crop health is the leaf chlorophyll measurement. In the Asian part of the world, Betel vine (Piper betle L., family Piperaceae) ranks second to coffee and tea in terms of daily consumption. Therefore, these important and highly productive crash crop is selected for the purpose of study. The experiment was conducted in an established pan betel vine crop field (Pan boroj). A small review of the popular method of leaf chlorophyll measurement is done and some of the drawbacks of the existing methods are reported. The review point out a need for fast and precise leaf chlorophyll measurement technique. Thus an image processing technique based on trichromatic colors i.e., red green and blue (RGB) model is proposed. For the purpose of analysis of the proposed model, the model outcome was compared with atLEAF+ chlorophyll meter reading. And a regression analysis was performed the result of regression analysis proof that there is a strong correlation between proposed image processing technique and chlorophyll meter reading. Thus, it appears that the proposed image processing technique of leaf chlorophyll measurement will be a good alternative for measuring leaf chlorophyll rapidly and with ease. (C) 2015 The Authors. Published by Elsevier B.V.