光谱学与光谱分析 |
|
|
|
|
|
Rapid Diagnostics of Early Phosphorus Deficiency in Mini-Cucumber Plants under Protected Cultivation by Near Infrared Spectroscopy |
SHI Ji-yong1, ZOU Xiao-bo1*, ZHAO Jie-wen1, MAO Han-ping2, WANG Kai-liang1, CHEN Zheng-wei1, HUANG Xiao-wei1 |
1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China 2. Key Laboratory of Modern Agricultural Equipment and Technology, Jiangsu University, Zhenjiang 212013, China |
|
|
Abstract The morphological symptom of phosphorus deficiency at early stage is similar to the appearance of leaf aging process in preliminary phase, so that visual diagnostics of phosphorus deficiency in mini-cucumber plants at early stage is practically impossible. Near infrared reflectance spectra contain information about differences in compositions of leaf tissues between phosphorus-deficient plants and healthy plants. In the present paper, near infrared reflectance spectroscopy was used to provide diagnostic information on phosphorus deficiency of mini-cucumber plants grown under non-soil conditions. Near infrared spectra was collected from 90 leaves of mini-cucumber plants. Raw cucumber spectra was preprocessed by SNV and divided into 27 intervals. The top 10 principal components (PCs) were extracted as the input of BP-ANN classifiers by principal component analysis (PCA) while the values of nutrient deficient were used as the output variables of BP-ANN and three layers BP-ANN discrimination model was built. The best experiment results were based on the top 3 principal components of No.7 interval when the spectra was divided into 27 intervals and identification rates of the ANN model are 100% in both training set and the prediction set. The overall results show that NIR spectroscopy combined with BP-ANN can be efficiently utilized for rapid and early diagnostics of phosphorus deficiency in mini-cucumber plants.
|
Received: 2011-02-23
Accepted: 2011-06-18
|
|
Corresponding Authors:
ZOU Xiao-bo
E-mail: zou_xiaobo@ujs.edu.cn
|
|
[1] CAO Wei-xing,ZHU Yan,TIAN Yong-chao, et al(曹卫星,朱 艳,田永超 , 等). Scientia Agricultura Sinica(中国农业科学), 2006,(2): 281. [2] Milton N M, Eiswerth B A, Ager C M. Remote Sensing of Environment, 1991, 36(2): 121. [3] YAO Q, YANG K, PAN G, et al. Agricultural Sciences in China, 2007, 6(5): 559. [4] ZHANG Li-xia,PENG Jian-ming,MA Jie(张丽霞,彭建明,马 洁). Chinese Agricultural Science Bulletin(中国农学通报), 2010,(8): 157. [5] LU Jian-ping,PENG Jian,SHI Jian-rong, et al(陆建平,彭 剑,石建荣 , 等). Chinese Journal of Analytical Chemistry(分析化学), 2008,36(2): 238. [6] Johnston M E, Gikaara D M, Edwards D G. Scientia Horticulturae, 2006, 110(3): 298. [7] MAO Han-ping, WU Xue-mei,LI Ping-ping(毛罕平,吴雪梅,李萍萍). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2005,21(8): 106. [8] MAO Han-ping,XU Gui-li,LI Ping-ping(毛罕平,徐贵力,李萍萍). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2003,34(2): 73. [9] MAO Han-ping,XU Gui-li,LI Ping-ping(毛罕平,徐贵力,李萍萍). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2003, 19(2): 133. [10] Wiwart M, Fordonski G, Zuk-Golaszewska K, et al. Computers and Electronics in Agriculture, 2009, 65(1): 125. [11] Petisco C, García-Criado B, de Aldana B R V, et al. Analytical and Bioanalytical Chemistry, 2005, 382(2): 458. [12] Li X, He Y, Fang H. Journal of Food Engineering, 2007, 81(2): 357. [13] CHANG Wei-wei,GUO Lei,FU Zhao-yang, et al(常威威,郭 雷,付朝阳, 等). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2010, 29(3): 205. [14] Dou Y, Sun Y, Ren Y, et al. Analytica Chimica Acta, 2005, 528(1): 55. [15] Zou X B, Zhao J W, Povey M J W, et al. Analytica Chimica Acta, 2010, 667(1-2): 14. [16] AN Na,XU Hui,SUN Zhou-ping, et al(安 娜,须 晖,孙周平 , 等). Journal of Shenyang Agricultural University(沈阳农业大学学报), 2006, 37(3): 495. [17] Zou X B, Zhao J W, Li Y X. Vibrational Spectroscopy, 2007, 44(2): 220. [18] SHAN Yang,ZHU Xiang-rong,XU Qing-song, et al(单 杨,朱向荣,许青松, 等). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2010,29(2): 128. [19] WU Yan,WAN Wei(武 妍,万 伟). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2007, 26(1): 65.
|
[1] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
[2] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
[3] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
[4] |
WU Mu-lan1, SONG Xiao-xiao1*, CUI Wu-wei1, 2, YIN Jun-yi1. The Identification of Peas (Pisum sativum L.) From Nanyang Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1095-1102. |
[5] |
GENG Ying-rui1, SHEN Huan-chao1, NI Hong-fei2, CHEN Yong1, LIU Xue-song1*. Support Vector Machine Optimized by Near-Infrared Spectroscopic
Technique Combined With Grey Wolf Optimizer Algorithm to
Realize Rapid Identification of Tobacco Origin[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2830-2835. |
[6] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
[7] |
LI Yan-yan1, 2, LUO Hai-jun1, 2*, LUO Xia1, 2, FAN Xin-yan1, 2, QIN Rui1, 2. Detection of Craniocerebral Hematoma by Array Scanning Sensitivity Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 392-398. |
[8] |
GUO Mei1, 2, ZHANG Ruo-yu2, 3, ZHU Rong-guang2, 3, DUAN Hong-wei1, 2*. Quantitative Determination of Water-Soluble P in Biochar Based on NELIBS Technology and EN-SVR Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(07): 2301-2306. |
[9] |
WANG Chao1, LI Peng-cheng2, YANG Kai1, ZHANG Tian-tian2, LIU Yi-lin2, LI Jun-hui2*. Rapid Detection of Tobacco Quality Grade and Analysis of Grade Characteristics by Using Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(03): 943-947. |
[10] |
LI Zi-wen1, LI Zong-peng1, MAI Shu-kui1, SHENG Xiao-hui1, YIN Jian-jun1, LIU Guo-rong2, WANG Cheng-tao2, ZHANG Hai-hong3, XIN Li-bin4, WANG Jian1*. Determination of Fat in Walnut Beverage Based on Least Squares Support Vector Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(12): 3916-3920. |
[11] |
SHENG Xiao-hui1, LI Zi-wen1, LI Zong-peng1, ZHANG Fu-yan2, ZHU Ting-ting3, WANG Jian1*, YIN Jian-jun1, SONG Quan-hou1. Determination of Korla Pear Hardness Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(09): 2818-2822. |
[12] |
HUA Jin1, ZHAO You-you1, GAO Yuan-hui1, ZHANG Li-hua1, HAO Jia-xue2, SONG Huan1, ZHAO Wen-ying2*. Rapid Detection of Fat Content in Meat with Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(11): 3424-3429. |
[13] |
LENG Wen-xiu, ZHAN Hong-lei, GE Li-na. Optical Analysis of Two-Component Alkane Mixtures Based on Terahertz Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(07): 2010-2013. |
[14] |
ZHA Yu-tong1, LIU Guang-da1, WANG Yong-xiang1, WANG Te2, CAI Jing1, ZHOU Ge1, SHANG Xiao-hu1*. Noninvasive Cerebral Blood Flow Measurement Based on NIRS-ICG[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(04): 1069-1073. |
[15] |
CHU Xuan1, WANG Wei2, ZHAO Xin1, JIANG Hong-zhe1, WANG Wei1*, LIU Sheng-quan1 . Detection of Camellia Oleifera Oil Adulterated with Sunflower Oil with Near Infrared (NIR) Spectroscopy and Characteristic Spectra [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(01): 75-79. |
|
|
|
|