| 光谱学与光谱分析 |
|
|
|
|
|
| Research on Distinguishing Weed from Crop Using Spectrum Analysis Technology |
| CHEN Shu-ren,LI Yi-xin,MAO Han-ping,SHEN Bao-guo,ZHANG Yu-zhu,CHEN Bin |
| Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education & Jiangsu Province, Jiangsu University, Zhenjiang 212013, China |
|
|
|
|
Abstract Automatic detection of weeds is necessary for site-specific application of herbicides or precise physical weed control. Leaf reflectance is mainly determined by photosynthetic pigments, leaf structural properties and water content, so spectral reflectance characteristics can be used for weed discrimination. The spectral reflectance of cotton, rice and weeds was determined in the range from 350 to 2 500 nm using the Analytical Spectral Device Full Range FieldSpec Pro (ASD) in laboratory. The discrimination analysis was done using the statistical software package SAS. The characteristic wavelengths were selected by using STEPDISC procedure. With the selected characteristic wavelengths, discriminant models were developed using the DISCRIM procedure in SAS. For distinguishing spine-greens from cotton, three characteristic wavelengths, 385, 415, and 435 nm, were selected, and good classification performance (100% accuracy) was achieved. The combination of characteristic wavelengths 415 and 435 nm has the biggest contribution to discrimination model. For distinguishing barnyard-grass from rice, five characteristic wavelengths, 375, 465, 585, 705, and 1 035 nm, were selected, and also good classification performance (100% accuracy) was obtained. The transition point from yellow to orange wavelength (585 nm) and the wavelength 705 nm in the red edge contributed more to discrimination model.
|
|
Received: 2007-10-06
Accepted: 2008-01-06
|
|
|
|
Corresponding Authors:
CHEN Shu-ren
E-mail: srchen@uij.edu.cn
|
|
[1] Brown R B, Steckler J -P G A, Anderson G W. Transactions of the ASAE, 1994, 37(1): 297.
[2] Goel P K, Prasher S O, Patel R M, et al. Transactions of the ASAE, 2002, 45(2): 443.
[3] Vrindts E, De Baerdemaeker J, Ramon H. Precision Agriculture, 2002, 3: 63.
[4] Slaughter D C, Lanini W T, Giles D K. Transactions of the ASAE, 2004, 47(6): 1907.
[5] MAO Wen-hua, WANG Yue-qing, WANG Yi-ming, et al(毛文华，王月青，王一鸣，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(6): 984.
[6] QIANG Sheng, WEI Shou-hui, HU Jin-liang(强 胜，魏守辉，胡金良). Journal of Nanjing Agricultural University(南京农业大学学报), 2000, 23(2): 18.
[7] LI Dong-po, WU Zhi-jie(李东坡，武志杰). Chinese J. Rice. Sci.(中国水稻科学), 2002, 16(4): 378.
[8] Knipling E B. Remote Sensing of Environment, 1970, 1: 155.
[9] Terashima I, Saeki T. Plant and Cell Physiology, 1983, 24: 1493.
[10] DeLucia E H, Nelson K, Vogelmann T C, et al. Plant Cell and Environment, 1996, 19: 159.
[11] Gausman H W. Photogrammetric Engineering and Remote Sensing, 1974, 40: 183.
[12] CHI Guang-yu, LIU Xin-hui, LIU Su-hong, et al(迟光宇，刘新会，刘素红，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(7): 1272.
[13] FENG Lei, FANG Hui, ZHOU Wei-jun, et al(冯 雷，方 慧，周伟军，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(9): 1749.
[13] CHEN Shu-ren, LI Yi-xin, MAO Han-ping, et al(陈树人, 栗移新, 毛罕平, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2008, 39(a): 96.
[14] CHEN Shu-ren, LI Yi-xin, MAO Han-ping, et al(陈树人, 栗移新, 毛罕平, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2008, 39(a): 96.
|
| [1] |
FAN Ping-ping，LI Xue-ying，QIU Hui-min，HOU Guang-li，LIU Yan*. Spectral Analysis of Organic Carbon in Sediments of the Yellow Sea and Bohai Sea by Different Spectrometers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 52-55. |
| [2] |
YANG Chao-pu1, 2, FANG Wen-qing3*, WU Qing-feng3, LI Chun1, LI Xiao-long1. Study on Changes of Blue Light Hazard and Circadian Effect of AMOLED With Age Based on Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 36-43. |
| [3] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [4] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [5] |
LIANG Jin-xing1, 2, 3, XIN Lei1, CHENG Jing-yao1, ZHOU Jing1, LUO Hang1, 3*. Adaptive Weighted Spectral Reconstruction Method Against
Exposure Variation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3330-3338. |
| [6] |
MA Qian1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, CHENG Hui-zhu1, 2, ZHAO Yan-chun1, 2. Research on Classification of Heavy Metal Pb in Honeysuckle Based on XRF and Transfer Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2729-2733. |
| [7] |
HUANG Chao1, 2, ZHAO Yu-hong1, ZHANG Hong-ming2*, LÜ Bo2, 3, YIN Xiang-hui1, SHEN Yong-cai4, 5, FU Jia2, LI Jian-kang2, 6. Development and Test of On-Line Spectroscopic System Based on Thermostatic Control Using STM32 Single-Chip Microcomputer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2734-2739. |
| [8] |
ZHENG Yi-xuan1, PAN Xiao-xuan2, GUO Hong1*, CHEN Kun-long1, LUO Ao-te-gen3. Application of Spectroscopic Techniques in Investigation of the Mural in Lam Rim Hall of Wudang Lamasery, China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2849-2854. |
| [9] |
WANG Jun-jie1, YUAN Xi-ping2, 3, GAN Shu1, 2*, HU Lin1, ZHAO Hai-long1. Hyperspectral Identification Method of Typical Sedimentary Rocks in Lufeng Dinosaur Valley[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2855-2861. |
| [10] |
WANG Jing-yong1, XIE Sa-sa2, 3, GAI Jing-yao1*, WANG Zi-ting2, 3*. Hyperspectral Prediction Model of Chlorophyll Content in Sugarcane Leaves Under Stress of Mosaic[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2885-2893. |
| [11] |
WANG Yu-qi, LI Bin, ZHU Ming-wang, LIU Yan-de*. Optimizations of Sample and Wavelength for Apple Brix Prediction Model Based on LASSOLars Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1419-1425. |
| [12] |
LI Shuai-wei1, WEI Qi1, QIU Xuan-bing1*, LI Chuan-liang1, LI Jie2, CHEN Ting-ting2. Research on Low-Cost Multi-Spectral Quantum Dots SARS-Cov-2 IgM and IgG Antibody Quantitative Device[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1012-1016. |
| [13] |
JIN Cui1, 4, GUO Hong1*, YU Hai-kuan2, LI Bo3, YANG Jian-du3, ZHANG Yao1. Spectral Analysis of the Techniques and Materials Used to Make Murals
——a Case Study of the Murals in Huapen Guandi Temple in Yanqing District, Beijing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1147-1154. |
| [14] |
DING Kun-yan1, HE Chang-tao2, LIU Zhi-gang2*, XIAO Jing1, FENG Guo-ying1, ZHOU Kai-nan3, XIE Na3, HAN Jing-hua1. Research on Particulate Contamination Induced Laser Damage of Optical Material Based on Integrated Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1234-1241. |
| [15] |
ZHANG Bao-ping1, NING Tian1, ZHANG Fu-rong1, CHEN Yi-shen1, ZHANG Zhan-qin2, WANG Shuang1*. Study on Raman Spectral Characteristics of Breast Cancer Based on
Multivariable Spectral Data Analysis Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 426-434. |
|
|
|
|
