Chlorophyll Assessment and Sensitive Wavelength Exploration for Tea (Camellia sinensis) Based on Reflectance Spectral Characteristics

Abstract

A nondestructive method for the determination of chlorophyll index for the tea plant based on reflectance spectral characteristics was investigated. Spectral data were collected from 184 samples with a spectroradiometer in a field experiment. Multivariate analysis techniques, including partial least squares (PLS) and multiple linear regression (MLR), were used for developing calibration models for the determination of chlorophyll index of the tea plant. The best calibration model was achieved using the PLS technique with a correlation coefficient (r) of 0.95, a se of prediction of 3.40, and a bias of 1.9e−06. When the model was used for predicting the unknown samples, good performance was also obtained with r of 0.91, se of calibration of 4.77, and bias of 0.02. Sensitive wavelengths were selected through loading analysis of latent variables in the optimal PLS model, and the validity of these wavelengths was proved by MLR and statistical analysis. Three fingerprint wavelengths (488, 695, and 931 nm) were determined and could potentially be used for developing a simple, low-cost, and efficient instrument for the measurement of chlorophyll index. The results proved the feasibility of reflectance spectra for measurement of chlorophyll index of the tea plant.