文献类型： 外文期刊

作者： Song, Di ¹ ; Qiao, Lang ¹ ; Gao, Dehua ¹ ; Li, Song ¹ ; Li, Minzan ¹ ; Sun, Hong ¹ ; Ma, Junyong ³ ;

作者机构： 1.China Agr Univ, Key Lab Modern Precis Agr Syst Integrat Res, Minist Educ, Beijing 100083, Peoples R China

2.China Agr Univ, Key Lab Agr Informat Acquisit Technol, Minist Agr & Rural Affairs, Beijing 100083, Peoples R China

3.Hebei Acad Agr & Forestry Sci, Dry Land Farming Inst, Shijiazhuang 053000, Hebei, Peoples R China

关键词： Chlorophyll content; Multi-band sensor; Interference filtering; Spectral analysis; Non-destructive detection

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：5.565； 五年影响因子：5.494 ）

ISSN： 0168-1699

年卷期： 2021 年 187 卷

页码：

收录情况： SCI

摘要： To achieve a non-destructive detection of chlorophyll content in field crops based on the reflectance characteristics of chlorophyll in the visible and near-infrared spectrum (400 nm-1000 nm), a crop chlorophyll detector based on an interference filter optical sensor was designed. The hardware part of this detector mainly comprises a microcontroller unit, a sensor module, an input/output module, and a power module. The software is written in Python language and includes main functions, acquisition sub-functions, data processing sub-functions, and data storage sub-functions. Calibration and test experiments were carried out to evaluate the performance of the sensor. Results show that the sensor has a good responsivity of light intensity changes, so as to measure the reflected radiation from crops with the absorption of chlorophyll content. Field verification experiments of corn crops were also carried out, and chlorophyll content detecting models were built by using four combinations of characteristic wavelengths, including 3 peak bands, 9 bands selected via the stepwise regression analysis method, 8 bands selected via the Monte Carlo uninformed variable elimination method, and all 18 bands. Among them, the stepwise regression method obtained the best modeling results. The model showed better performance after calibration than before the calibration with RC2 of 0.72, RV2 of 0.61, RMSEc of 2.35 mg/L, and RMSEv of 2.43 mg/ L. The crop chlorophyll detector based on the interference filter optical sensor was used for filed estimation of chlorophyll content which showed a potential for the analysis of crop growth differences.