Abstract:

Grain protein content is a key index for evaluating rice quality. We investigated the quantitative relationships between grain protein content and canopy reflectance spectra at different growth stages in rice (Oryza sativa L.) on the basis of the data from the field experiments involving different cultivars and nitrogen levels in four years. Experiment 1 and 2 were both conducted with one cultivar, Wuxiangjing 9, and five N application levels of 0, 75, 150, 225, and 300 kg ha^-1 in 2002 and 2003. Experiment 3 included three cultivars (Wuxiangjing 9, Huajing 2, Nipponbare) with four N application levels of 0, 105, 210, and 315 kg ha^-1 in 2004. Experiment 4 was designed with two cultivars (Wuxiangjing 14, 27123), and four N application levels of 0, 90, 270, and 420 kg ha^-1 in 2005. Canopy spectral reflectance (460–1 650 nm) date at jointing, booting, heading, filling, and ripening stages of rice in the different field experiments were measured with MSR-16 multi-spectral radiometer, and corresponding leaf area index and grain protein content were also determined. Then the relationships of grain protein content to canopy reflectance of single band and all two-band combinations were analyzed.
The results showed that there were significant negative correlation between grain protein content and canopy spectral reflectance at 460–710 nm and positive correlation at 760–1 220 nm after jointing, with best performance from the relationship at 760 nm and booting stage. The relationships of grain protein content to the ratio, differential and normalized difference vegetation indices of all bands and red edge parameters were also analyzed, then fifteen parameters were selected. Through step regression analysis on 16 better spectral parameters, the differential vegetation index of R1500 and R950 was found to be the best parameter for predicting grain protein content (GPC) in rice. The derived equation, GPC =0.15 × DVI (1 500, 950) + 3, was tested with the observed data from the other independent experiments. The estimation precision was 0.56–0.86, estimation accuracy was 0.85–1.18, and RMSE was 3.51%–19.9%, indicating a good fit between the predicted and observed values of grain protein content. It is concluded that the present spectral index model is feasible and useful for estimating grain protein content in rice with different cultivars and nitrogen levels.

Key words: Rice, Grain protein content, Canopy reflectance spectra, Vegetation index