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Development of algorithms for detecting citrus canker based on hyperspectral reflectance imaging
Author(s) -
Li Jiangbo,
Rao Xiuqin,
Ying Yibin
Publication year - 2011
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.4550
Subject(s) - citrus canker , hyperspectral imaging , canker , multispectral image , principal component analysis , reflectivity , computer science , artificial intelligence , remote sensing , mathematics , environmental science , horticulture , optics , biology , geology , physics , genetics , bacteria
BACKGROUND: Automated discrimination of fruits with canker from other fruit with normal surface and different type of peel defects has become a helpful task to enhance the competitiveness and profitability of the citrus industry. Over the last several years, hyperspectral imaging technology has received increasing attention in the agricultural products inspection field. This paper studied the feasibility of classification of citrus canker from other peel conditions including normal surface and nine peel defects by hyperspectal imaging. RESULTS: A combination algorithm based on principal component analysis and the two‐band ratio ( Q 687/630 ) method was proposed. Since fewer wavelengths were desired in order to develop a rapid multispectral imaging system, the canker classification performance of the two‐band ratio ( Q 687/630 ) method alone was also evaluated. The proposed combination approach and two‐band ratio method alone resulted in overall classification accuracy for training set samples and test set samples of 99.5%, 84.5% and 98.2%, 82.9%, respectively. CONCLUSION: The proposed combination approach was more efficient for classifying canker against various conditions under reflectance hyperspectral imagery. However, the two‐band ratio (Q 687/630 ) method alone also demonstrated effectiveness in discriminating citrus canker from normal fruit and other peel diseases except for copper burn and anthracnose. Copyright © 2011 Society of Chemical Industry