Key Parameters for Maize Leaf Moisture Measurement Using NIR Camera With Filters Based on Hyperspectral Data
LI Peng-cheng1, 2, LIU Han1, 2, ZHAO Long-lian1, 2, LI Jun-hui1, 2*
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University，Beijing 100083, China
Abstract：To provide effective technical means for the study of the crop growth in water stress response mechanism, drought monitoring, and precision irrigation, moisture content detection in different regions of maize live crop leaves and near the canopy is achieved.The large volume, large weight, low luminous flux hyperspectrometer is difficult to achieve live detection in the field. The small volume, small weight, high luminous flux NIR camera with filters to make it wavelength-resolved is expected to achieve live leaf moisture content imaging detection in the field. Based on the near-infrared hyperspectral data of live maize leaves, this study is to investigate the key parameters, including the characteristic wavelength position and number, bandwidth and offset limit. Among them, the simulation data of different bandwidths are based on the filter light transmission distribution function; the simulation data of the center wavelength shift under fixed bandwidths are based on the interpolation method. The research results showed that the feature wavelengths are 1 150 and 1 400 nm respectively, and the bandwidth is less than 100 nm, which can meet the requirements and find the filter products that meet the parameter conditions. When the bandwidth was 25 nm, the model set’s determination coefficient (R2) and root mean square error (RMSE) were 0.968 and 1.245%, respectively, and the prediction set was 0.960 and 1.298%, respectively. To infer that the model built with the filters is affected by the ambient temperature, the model within a fixed center wavelength is used to predict the simulation data of different offsets. When the drift was 0.05 nm, the model prediction errorunder non-drift conditions was about 3%, which could be neglected. The relationship between the center wavelength drift of the filter and the temperature is equivalent to that the ambient temperature in the range of 50 ℃ has little effect on the detection results. Thisresearch provides important technical parameter support and working range for the NIR camera with filters to form a multispectral imaging system detection device. The device’s construction has been started, and the realization of the device can provide new and effective means for modern agricultural crop physiology and production research.
李朋成，刘 含，赵龙莲，李军会. 基于高光谱数据研究应用近红外相机加装滤光片实现玉米叶片水分测量的关键参数[J]. 光谱学与光谱分析, 2021, 41(10): 3184-3188.
LI Peng-cheng, LIU Han, ZHAO Long-lian, LI Jun-hui. Key Parameters for Maize Leaf Moisture Measurement Using NIR Camera With Filters Based on Hyperspectral Data. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3184-3188.
[1] Boyer J S. Science, 1982, 218(4571): 443.
[2] DU Ling-tong, TIAN Qing-jiu, WANG Lei, et al(杜灵通，田庆久，王 磊，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2014, 30(9): 126.
[3] Jia B, Wang W, Ni X, et al. Chemometrics and Intelligent Laboratory Systems, 2020, 198(3): 103936.
[4] ZHU Yuan-yuan，GAO Jiao-bo，GAO Ze-dong, et al(朱院院，高教波，高泽东，等). Optical Technique(光学技术), 2016, 42(2): 97.
[5] Ge Y, Bai G, Stoerger V, et al. Computers and Electronics in Agriculture, 2016, 127(10): 625.
[6] Angelino K, Edlund D A, Shah P. IEEE Journal of Translational Engineering in Health and Medicine, 2017，5(5): 2168.
[7] Zhang M, Gong M, Chan Y. Applied Soft Computing, 2018, 70(1): 604.
[8] He H, Sun D. Trends in Food Science & Technology, 2015, 46(1): 99.
[9] GAO Jian-shu, ZHENG Da-chuan, YU Zhi-jing(高建树，郑大川，于之靖). Laser and Infrared(激光与红外), 2014, 44(4): 391.
[10] Ishii K, Nagao R, Matsui D, et al. Advanced Biomedical Engineering, 2015. 4(9): 158.
[11] Yan L，Pang L，Wang H，et al. Journal of Food Process Engineering, 2020, 43(4): 13416.
[12] YANG Xiu, WANG Jin-feng, LEI Yan-hui, et al(杨 秀，王劲峰，类延辉，等). Urban Studies(城市发展研究), 2019, 7(26): 81.
[13] LIU Qing, ZHOU Jin-song, NIE Yun-feng, et al(柳 青，周锦松，聂云峰，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(4): 1142.
[14] FAN Bin, LI Gang-zheng, CHENG Xin-bin, et al(范 滨，李刚正，程鑫彬, 等) . Opt. Instr.(光学仪器), 2006, (4): 95.
[15] Takashashi H. Appl. Opt., 1995, 34(4): 667.
[16] YAN Yan-lu(严衍禄). Principle, Technology and Application of NIR Spectra Analysis(近红外光谱分析的原理、技术与应用). Beijing: China Light Industry Press(北京: 中国轻工业出版社), 2013.
