Data from: Vis/NIR reflectance spectroscopy for hybrid rice variety identification and chlorophyll content evaluation for different nitrogen fertilizer levels

Nitrogen is one of the most important nutrient indicator for the growth of crops, which is closely related to chlorophyll content of leaves and thus influences the photosynthetic ability of crops. In this study, visible and near infrared (vis/NIR) reflectance spectroscopy combined with multi-variate analysis was used to identify hybrid rice varieties and nitrogen fertilizer levels, as well as to detect chlorophyll content associated with nitrogen levels. The support vector machine (SVM) algorithm was applied to identify five varieties of hybrid rice and six levels of nitrogen fertilizer. The results demonstrated that different varieties of hybrid rice for each nitrogen level can be well distinguished except for the highest nitrogen level, and no nitrogen level for each rice variety can be completely identified from the other five nitrogen levels. Further, several spectral indices combined with partial least squares (PLS) analysis were applied for estimating chlorophyll content of rice leaves from plants subject to different nitrogen levels, and a coefficient of determination (R2) of 97.8% and a ratio of performance to deviation (RPD) of 4.6 for all rice varieties indicated this as a preferable procedure. Experimental results demonstrated that vis/NIR spectroscopy can have a great potential for identification of rice varieties and evaluation of nitrogen fertilizer levels.