Estimation of Chlorophyll Content in Maize Leaves Based on Optimized Area Spectral Index
TANG Yu-zhe, HONG Mei, HAO Jia-yong, WANG Xu, ZHANG He-jing, ZHANG Wei-jian, LI Fei*
College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Inner Mongolia Key Laboratory of Soil Quality and Nutrient Resources, Inner Mongolia Agricultural University, Huhhot 010018, China
Abstract：Spectral index is an important means for real-time estimation of crop leaf chlorophyll. The comprehensive use of spectral technology for real-time and effective diagnosis of crop nutrients is conducive to accurate crop management, ensuring yield and reducing environmental pollution, improving fertilizer utilization, and providing a new way for quantitative estimation of crop biochemical components. However, the estimation results are not satisfactory due to the influence of environmental conditions and internal biochemical components. In order to further improve the anti-interference ability and sensitivity of spectral index in estimating chlorophyll content of crop leaves. In this study, field experiments with different nitrogen gradients were carried out in typical corn-growing areas of Inner Mongolia in 2020. The spectral reflectance and chlorophyll value of leaves were obtained at four key growth stages of corn. The relationship model between the spectral index and chlorophyll value of leaves was established based on area, and the spectral index was optimized and evaluated. It provides an important theoretical basis for the diagnosis of chlorophyll content in maize leaves and an accurate grasp of the nutritional status of crops in a larger area in the future. The results showed that the growth period significantly affected the relationship between area spectral index and leaf chlorophyll value. The published area-based spectral index had a poor estimation effect on leaf chlorophyll content at the seedling stage, but had the best estimation effect on the tasseling stage. In this paper, the area spectral index based on the optimization algorithm significantly improves the accuracy and stability of spectral index in Estimating Leaf Chlorophyll content. The optimized triangle vegetation index (OTVI), optimized chlorophyll absorption integral index (OCAI) and optimized bimodal area normalized difference index (ONDDA) based on the optimization algorithm have stronger performance than the published area spectral index at different growth stages, the coefficient of determination R2 is between 0.94 and 0.99. Compared with OTVI and OCAI, ONDDA is more stable in estimating the chlorophyll content of spring maize leaves at different growth stages. The coefficient of determination R2 of prediction model validation results is 0.94, and the validation error is the smallest, RMSE and RE% are 2.29% and 3.94%, respectively. The validation slope of the model estimated value and the measured value is 0.996, the closest to 1. In conclusion, ONDDA is a practical and suitable area spectral index for estimating leaf chlorophyll content at different growth stages.
Key words：Corn leaf; Chlorophyll content; Area spectral index
唐彧哲，红 梅，郝嘉永，王 旭，张贺景，张炜健，李 斐. 基于优化面积光谱指数的玉米叶片叶绿素值估测[J]. 光谱学与光谱分析, 2022, 42(03): 924-932.
TANG Yu-zhe, HONG Mei, HAO Jia-yong, WANG Xu, ZHANG He-jing, ZHANG Wei-jian, LI Fei. Estimation of Chlorophyll Content in Maize Leaves Based on Optimized Area Spectral Index. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 924-932.
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