The traditional measuring method of chlorophyll content is cumbersome and time-consuming. Taking the labview software and IMAQ-Vision toolkit as the platform and the tomato leaves as test materials, this paper adopts the computer vision technology to extract the component value of the tomato leaf image under different color spaces and employs the statistical analysis method to establish the correlation and regression equation between the image component and the chlorophyll content. It is obtained that the regression equation between the SPAD value and the leaf color characteristic parameter H/(S+L) is y=0.0003x2-0.0139x+0.3411, whose maximum coefficient of determination is R2=0.7327. It is indicated that the method is effective and feasible for the prediction of tomato chlorophyll and also lays the foundation for the development of crop growth monitoring instrument.
Tomato leaf, Chlorophyll, Computer vision, Labview
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