Fast detection and visualization of early decay in citrus using Vis-NIR hyperspectral imaging

文献类型： 外文期刊

第一作者： Li, Jiangbo

作者： Li, Jiangbo;Huang, Wenqian;Tian, Xi;Wang, Chaopeng;Fan, Shuxiang;Zhao, Chunjiang;Li, Jiangbo;Huang, Wenqian;Tian, Xi;Wang, Chaopeng;Fan, Shuxiang;Zhao, Chunjiang;Li, Jiangbo;Huang, Wenqian;Zhao, Chunjiang

作者机构：

关键词： Fruit detection;Citrus fruit;Orange;Hyperspectral imaging;Image processing;Decay

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：5.565； 五年影响因子：5.494 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest phase. The automation of this task is still a challenge for the citrus industry. In this study, the potential application of hyperspectral imaging, which combines conventional imaging and spectroscopy to simultaneously acquire both spatial and spectral information from an object, was evaluated for automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit. Hyperspectral images of sound and decayed navel oranges were acquired in the wavelength range of 325-1100 nm. Principal component analysis (PCA) was applied to a dataset comparing of average spectra from decayed and sound tissue to reduce the dimensionality of data and to observe the ability of visible near infrared (Vis-NIR) hyper-spectra to discriminate data from two classes. And, a mean normalization step is applied prior to PCA to reduce the effect of sample curvature on spectral profiles. In this case it was observed that sound and decayed spectra were separable along the resultant first principal component (PC1) axis, then, four wavelength images centered at 575, 698, 810 and 969 nm were selected as the characteristic wavelength images by analyzing the weight coefficients of PC1 in order to develop a fast classification method for establishing an on-line multispectral imaging system. Subsequently, a combination image, which obtained by multiplying the characteristic weight coefficients by corresponding to mean-normalized characteristic wavelength images of each orange sample, was calculated for determination of decayed fruits. Based on the obtained multispectral combination image, the technique of intensity slicing as one of the pseudo-color image processing methods is used to transform the combination image into a 2-D visual classification image that would enhance the contrast between sound and decayed classes. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudo-color image coupled with a simple thresholding method. For the investigated 210 naval orange samples including 80 sound fruits and 130 infected fruits, the total success rate is 100% for training set and 98.6% for test set with no false negatives, respectively, indicating that the proposed multispectral algorithm here is capable of detecting decay caused by penicillium digitatum in naval orange fruit using only four key wavelength images. The results from this study could be used for development of a non-destructive monitoring system for rapid detection of decayed citrus on the processing line. The idea behind the proposed algorithm can be extended to detect the non-visible damages of other fruit, such as slight bruise and chilling injury in apples. (C) 2016 Published by Elsevier B.V.

分类号： S`TP3

  • 相关文献

[1]THE INFRARED THERMAL IMAGE-BASED MONITORING PROCESS OF PEACH DECAY UNDER UNCONTROLLED TEMPERATURE CONDITIONS. Jiao, L. Z.,Wu, W. B.,Zheng, W. G.,Dong, D. M.. 2015

[2]Hyperspectral classification for identifying decayed oranges infected by fungi. Yin, Shiyang,Gu, Xiaomin,Xiao, Yong,Bi, Xiaoqing,Niu, Yong. 2017

[3]Detection of early bruises on peaches (Amygdalus persica L.) using hyperspectral imaging coupled with improved watershed segmentation algorithm. Li, Jiangbo,Chen, Liping,Huang, Wenqian,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Li, Jiangbo,Chen, Liping,Huang, Wenqian. 2018

[4]Detection of Early Rottenness on Apples by Using Hyperspectral Imaging Combined with Spectral Analysis and Image Processing. Zhang, Baohua,Fan, Shuxiang,Li, Jiangbo,Huang, Wenqian,Zhao, Chunjiang,Qian, Man,Zheng, Ling,Zhang, Baohua,Zhao, Chunjiang.

[5]Effects of Foliar Application of Various Zinc Fertilizers with Organosilicone on Correcting Citrus Zinc Deficiency. Peng, Liang-Zhi.

[6]Effects of exogenous 24-epibrassinolide treatment on postharvest quality and resistance of Satsuma mandarin (Citrus unshiu). Zhu, Feng,Yun, Ze,Ma, Qiaoli,Gong, Qi,Zeng, Yunliu,Xu, Juan,Cheng, Yunjiang,Deng, Xiuxin,Yun, Ze,Gong, Qi.

[7]Antifungal activity of thyme oil against Geotrichum citri-aurantii in vitro and in vivo. Liu, X.,Li, Y. C.,Yu, T.,Zheng, X. D.,Wang, L. P.,Li, H. Y.. 2009

[8]Enantioselective determination of acaricide etoxazole in orange pulp, peel, and whole orange by chiral liquid chromatography with tandem mass spectrometry. Yao, Zhoulin,Lin, Mei,Yao, Zhoulin,Xu, Mingfei,Wang, Qiang,Zhang, Hu,Yao, Zhoulin,Li, Zuguang,Zhuang, Shulin,Li, Xiaoge.

[9]Application of Fourier Transform Infrared Spectroscopy in Identification of Wine Spoilage. Zhao Xian-de,Dong Da-ming,Zheng Wen-gang,Jiao Lei-zi,Lang Yun. 2014

[10]Purification and characterization of polygalacturonase-inhibiting protein from Asian pear varieties. Tian, J. B.,Pastore, M.,Greve, L. C.,Vicente, A.,Labavitch, J. M.,Gregori, R.. 2008

[11]EARLY DETECTION OF GREY MOULD DEVELOPMENT IN 'RED GLOBE' GRAPES DURING STORAGE. Guan, Wenqiang,Wu, Xinling,Guan, Wenqiang,Wang, Zhidong,Wang, Xiaotuo,Yan, Ruixiang. 2015

[12]Effect of BTH on antioxidant enzymes, radical-scavenging activity and decay in strawberry fruit. Cao, Shifeng,Hu, Zhichao,Lu, Binhong,Zheng, Yonghua,Yang, Zhenfeng.

[13]Survey of Support Vector Machine in the Processing of Remote Sensing Image. Li, Su,Wang, Wenchao. 2013

[14]Quick image processing method of HJ satellites applied in agriculture monitoring. Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong,Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong. 2016

[15]Detection of defects on apple using B-spline lighting correction method. Li, Jiangbo,Huang, Wenqian,Guo, Zhiming. 2013

[16]Image processing methods to evaluate tomato and zucchini damage in post-harvest stages. Antonio Alvarez-Bermejo, Jose,Giagnocavo, Cynthia,Ming, Li,Yang Xinting,Castillo Morales, Encarnacion,Morales Santos, Diego P.. 2017

[17]Motion Blurring Direction Identification Based on Second-Order Difference Spectrum. Zhang, Junxiong,Li, Wei,He, Fen. 2011

[18]Design and Experiment of an Automatic Detection System for Cotton Field Pest and Seedling Information. Hua, Wu Hai,Bo, Zhao,Jun, Li Shu,Hua, Mao Wen,Chao, Zhang Xiao. 2014

[19]Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images. Li Shao-kun,Wang Ke-ru,Wang Chong-tao,Suo Xing-mei,Jiang Ying-tao,Yang Mei. 2010

[20]MOBILE SMART DEVICE-BASED VEGETABLE DISEASE AND INSECT PEST RECOGNITION METHOD. Wang, Kaiyi,Zhang, Shuifa,Wang, Zhibin,Liu, Zhongqiang,Yang, Feng,Wang, Kaiyi,Zhang, Shuifa,Wang, Zhibin,Liu, Zhongqiang,Yang, Feng. 2013

作者其他论文 更多>>

微信小程序