Investigation of leaf biochemistry by statistics

Abstract The biochemical concentration (total protein, cellulose, lignin, and starch) of 73 plant leaves has been related to their optical properties through statistical relationships. Both fresh and dry plant material, leaves and needles, were used in this study. Stepwise multiple regression analyses have been performed on reflectance, transmittance, and absorptance values (individual leaves) as well as on reflectance values of optically thick samples (stacked leaves + needles), on measured values and on transformations of them such as the first derivative or the logarithm of the reciprocal of the reflectance. They underscored good prediction performances for protein, cellulose, and lignin with high squared multiple correlation coefficients (r2) values. Starch, whose concentration in the leaf was smaller compared to the other components, was estimated with less accuracy. As expected, dry material and optically thick samples provided respectively stronger correlations than fresh material and individual leaves.

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