Fluorescence Spectrum Monitor for Early Warning of Greenhouse Cucumber Aphis Pests
SUI Yuan-yuan, YU Hai-ye*, ZHANG Lei, LUO Han, REN Shun, ZHAO Guo-gang
Key Laboratory of Bionic Engineering, Ministry of Education, School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Abstract：The infection and degree of cucumber aphis pests was studied by analyzing chlorophyllfluorescence spectrum in greenhouse. Based on the configuration of the spectrum, characteristic points were established, in which the intensity of waveband F632 was the first characteristic point between healthy and aphis pests leaves. The second characteristic point was K which was the change rate of spectral curve from waveband F512 to F632. The early warning could be executed on plants depending on these two points. The models of the infection and degrees of aphis pests were established for different wavebands by the least square support vector machine classification method (LSSVMR) radial basis function(RBF). The accuracy rate of classification and prediction of the models was compared by different peaks and valleys value in wavebands. The results indicated that the prediction accuracy of the model established by waveband F632 was the most perfect (96.34%).
Key words：Fluorescence spectrum;LSSVM;Cucumber aphis pests;Change rate of spectral curve
[1] Chunjiang Z, Ming L, Xiao H, et al. Progress of Information Technology in Agriculture, 2010: 527. [2] Lucas J A. Journal of Agricultural Science, 2011, 149: 91. [3] Chowdhury A, Pradhan S, Saha M, et al. Indian Journal of Microbiology, 2008, 48(1): 114. [4] WU Jian, MA Xiao-ming, LI Zhi-qing，et al(吴 坚，马小明，李志清，等). Journal of Forest Research(林业科学研究), 1994, (7): 579. [5] Huihui Q, Yunhui Z, Dengfa C, et al. Acta Entomologica Sinica, 2010, 53(11): 1256. [6] LI Li, LI Dao-liang, ZHOU Zhi-jian，et al(李 丽，李道亮，周志坚，等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2008, 39(3): 116，153. [7] XIE Chun-yan, WU Da-ke(谢春燕，吴达科). Journal of Agricultural Mechanization Research(农机化研究), 2009，(5): 10. [8] ZHANG Shou-ren(张守仁). Chinese Bulletin of Botany(植物学通报), 1999，(16): 444. [9] Cristianini N, Shawe-Taylor J. An Introduction to Support Vector Machines and OtherKerner-based Learning Methods(支持向量机导论). Translated by LI Guo-zheng, WANG Meng, ZENG Hua-jun(李国正，王 猛，曾华军，译). Beijing: Publishing House of Electronics Industry(北京：电子工业出版社), 2004. [10] SUI Yuan-yuan, YU Hai-ye, ZHANG Lei，et al(隋媛媛，于海业，张 蕾，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2011，31(11): 2987. [11] CHEN Yong-bing, YE Shu-guang, WANG Cheng(陈勇兵，叶曙光，王 诚). Meteorology and Diseases, Pests and Weeds of Vegetable(气象与蔬菜病虫害杂草发生、为害和治理). Beijing: China Agriculture Press(北京: 中国农业出版社), 2010. [12] Chatni M R, Yale G, Van Ryckeghem A, et al. Proceedings of SPIE. Orlando, FL: Smart Biomedical and Physiological Sensor Technologies VII.，2010.
