Abstract

Reflectance data and relative chlorophyll content for Phyllostachys violascens at leaf scale were measured during the growth period from April, 5th to June, 18th using a portable Analytical Spectral Devices (ASD) field spectrometer and a hand-held Chlorophyll Content Meter (CCM)-200. Correlation analyses were conducted between hyper-spectral vegetation indices and chlorophyll content based on the data. Then individual univariate linear inversion models were developed for chlorophyll content and hyper-spectral vegetation indices, such as red edge indexes GM, Vog3, double difference index DD, modified normalized differential vegetation index mND705, modified simple ratio mSR705, and Red-edge positions (REP). Also multivariate linear models for selected hyper-spectral vegetation indices and chlorophyll content were tested. Multivariate linear models are designed in two methods, strategy A is based on the 20 Phyllostachys violascens samples, and each data for the sample is the average for all the 14 times. On the contrary, strategy B is based on the data of 14 times, which average the 20 samples for each time. Results over the entire growth period showed (1) significant (P<0.01) correlations between chlorophyll content and hyper-spectral vegetation indices, GM (r = 0.866 3), Vog3 (r = 0.927 4 ), DD (r = 0.880 6), mND705 (r = 0.917 9), mSR705 (r = 0.924 9), and REP (r =0.895 4). At the end of the growth period, all vegetation indices had a favorable relationship with chlorophyll content, showing as the high correlation coefficients, although some indexes perform bad in most other time periods;(2) Using the univariate linear model, correlation for hyper-spectral vegetation indices and chlorophyll content showed r > 0.85. The multivariate linear models of the six hyper-spectral vegetation indices listed above and chlorophyll content using two strategies, both accurately predicted chlorophyll content of Phyllostachys violascens [with correlation coefficients between predicted values and measured values that were all above r = 0.89]. The multivariate linear models can be used to predicte chlorophyll content in the leaf of Phyllostachys violascens. Considering the calculate method, strategy B is more fit for the dynamic change of chlorophyll content for Phyllostachys violascens at leaf scale. [Ch, 4 fig. 2 tab. 45 ref.]

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