可见/近红外光谱图像在作物病害检测中的应用
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摘要
农作物病害严重影响了我国正常的农业生产,现代农业迫切需要快速、准确、高效的作物病害诊断方法。首先简单介绍了常用病害检测技术,如:聚合酶链式反应技术、人工感官判定技术、统计学方法等,这些方法或是比较费时、或是只能用于产生明显病斑后的病害诊断,而光谱技术在植物病害的快速检测方面有一定的潜力,目前已有大量的研究成果。主要围绕可见/近红外光谱图像在病害检测的应用展开分析和讨论,讨论了该技术所涉及的仪器,并从细胞、植物组织、冠层及更大尺度层面分析了该技术在病害检测中的现况。目前大部分与植物病害有关的可见/近红外光谱研究都以植物叶片为对象,而在更小尺度(细胞至显微尺度)和更大尺度(冠层至航空/航天遥感方面)上的研究较少,特别是单细胞级别的病害研究,只在动物细胞领域展开,而且以荧光、拉曼、红外光谱为主。可见/近红外在以植物叶片为主要研究对象的器官尺度上有大量的成功应用,目前的研究已涉及了大部分的常见作物及其主要病害,包括真菌性、细菌性等各种病原引起的病害的检测。植物叶片尺度的研究主要从以下三个方面展开:(1)基于计算机图像处理和模式识别的病害信息自动快速判断;(2)基于化学计量学方法的高光谱或高光谱图像病害程度模型;(3)建立与作物病害有关的叶片某些理化参数的光谱模型,从而量化病害的程度。在植物叶片这一尺度相关研究的主要问题是:研究过于碎片化,往往只研究了某一种或少数几种病害,所建的模型只能用于特定实验条件,无法直接自动判断任意田间样本的染病种类与程度。在近地冠层尺度,植株的三维形态对光谱模型有较大的干扰,有文献表明以植株近地冠层2D图像作为病害检测数据,偏差较大,所建模型不稳定,基于卫星影像的病害模型较少。还讨论了常用光谱及光谱图像建模与分类方法。目前可见/近红外光谱在农作物病害方面有一定的应用潜力,但存在研究内容的不平衡、研究系统性不够、各学科合作研究不够深入等几大问题。最后提出可见/近红外光谱在病害检测领域中应更注重多学科的深入合作,并急需相关的仪器设备、方法模型方面的突破。
Crop disease is a major biological hazard in agriculture of China and causes serious interference to farming process, so a fast, accurate and efficient diagnosis method for crop disease is in pressing need. Compared to some common crop disease detection technologies(such as polymerase chain reaction technique, artificial sensory evaluation technique, and statistical method), which are time-consuming or can only be used to detect obvious disease spots, spectral technology has potential in rapid detection of crop diseases and has been studied extensively. This passage mainly focuses on the application of visible/near infrared spectroscopy technology in disease detection, discusses instruments involved in this technology, and analyzes research status of visible/near infrared spectroscopy in disease detection from cell, plant tissue, canopy and larger scale aspects. At present, most of researches on visible/near infrared spectroscopy related to plant diseases are based on plant leaves. Few researches are on smaller scale(from cell to microscale) or larger scale(from canopy to aeronautical/spaceflight remote sensing scale), especially when it comes to disease researches on single cell scale, which are only done in the field of animal cells and have no successful application of visible/near infrared technology. However, visible/near infrared technology has many successful application in researches which are on organ scale of plant leaves. Most of common crops and major diseases of common crops, and diseases caused by fungal and bacterial pathogens are involved in current researches of disease detection. These researches are studied usually in three ways:(1) automatic and rapid diagnosis of disease information based on computer image processing and pattern recognition technology,(2) judgement model spectral analysis for Region of Interest(ROI) extracted from hyperspectral images was established based on stoichiometric method,(3) spectral model of some physical and chemical parameters of leaves related to crop diseases was established to quantify the extent of disease. The main problem related to this scale is that the research is so fragmented, which means only one or a few kinds of diseases are studied, that models can only be used in very specific conditions and can't be used directly to make a full automatic judgment on field samples. What's more, there are few studies on direct monitoring of crop diseases or multi-spectral imaging of near ground whole plants and the classification methods adopted are similar with those of leaf scale data processing. In near ground canopy scale, three dimensional forms of plants become a new source of interference in the spectral model, and some passage showed that 2 D image was used as disease detection data with a percentage deviation of 13%. Finally, according to the present situation of all aspects of researches, it is believed that visible/near infrared spectroscopy technology has a good application prospect in crop disease detection, but it is in the bottleneck period now. There exist some problems, including that unbalanced research content of plant disease detection, lack of systematisms caused by overabundance of disease species and insufficient cooperation of different subjects. According to those problems, this passage points out that visible/near infrared spectroscopy technology should pay more attention to the in-depth cooperation of multidisciplinary in the field of disease detection, and it is urgent to make breakthroughs in the related equipment and method model.
Crop disease is a major biological hazard in agriculture of China and causes serious interference to farming process, so a fast, accurate and efficient diagnosis method for crop disease is in pressing need. Compared to some common crop disease detection technologies(such as polymerase chain reaction technique, artificial sensory evaluation technique, and statistical method), which are time-consuming or can only be used to detect obvious disease spots, spectral technology has potential in rapid detection of crop diseases and has been studied extensively. This passage mainly focuses on the application of visible/near infrared spectroscopy technology in disease detection, discusses instruments involved in this technology, and analyzes research status of visible/near infrared spectroscopy in disease detection from cell, plant tissue, canopy and larger scale aspects. At present, most of researches on visible/near infrared spectroscopy related to plant diseases are based on plant leaves. Few researches are on smaller scale(from cell to microscale) or larger scale(from canopy to aeronautical/spaceflight remote sensing scale), especially when it comes to disease researches on single cell scale, which are only done in the field of animal cells and have no successful application of visible/near infrared technology. However, visible/near infrared technology has many successful application in researches which are on organ scale of plant leaves. Most of common crops and major diseases of common crops, and diseases caused by fungal and bacterial pathogens are involved in current researches of disease detection. These researches are studied usually in three ways:(1) automatic and rapid diagnosis of disease information based on computer image processing and pattern recognition technology,(2) judgement model spectral analysis for Region of Interest(ROI) extracted from hyperspectral images was established based on stoichiometric method,(3) spectral model of some physical and chemical parameters of leaves related to crop diseases was established to quantify the extent of disease. The main problem related to this scale is that the research is so fragmented, which means only one or a few kinds of diseases are studied, that models can only be used in very specific conditions and can't be used directly to make a full automatic judgment on field samples. What's more, there are few studies on direct monitoring of crop diseases or multi-spectral imaging of near ground whole plants and the classification methods adopted are similar with those of leaf scale data processing. In near ground canopy scale, three dimensional forms of plants become a new source of interference in the spectral model, and some passage showed that 2 D image was used as disease detection data with a percentage deviation of 13%. Finally, according to the present situation of all aspects of researches, it is believed that visible/near infrared spectroscopy technology has a good application prospect in crop disease detection, but it is in the bottleneck period now. There exist some problems, including that unbalanced research content of plant disease detection, lack of systematisms caused by overabundance of disease species and insufficient cooperation of different subjects. According to those problems, this passage points out that visible/near infrared spectroscopy technology should pay more attention to the in-depth cooperation of multidisciplinary in the field of disease detection, and it is urgent to make breakthroughs in the related equipment and method model.
引文
[1] XIE Chuan-qi,FENG Lei,FENG Bin,et al(谢传奇,冯雷,冯斌,等).Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2012,28(18):177.
[2] DAI Xiao-feng,YE Zhi-hua,CAO Ya-zhong,et al(戴小枫,叶志华,曹雅忠,等).Chinese Journal of Applied Ecology(应用生态学报),1999,10(1):119.
[3] HONG Ni,GAO Bi-da(洪霓,高必达).Plant Disease Quarantine(植物病害检疫学).Beijing:Science Press(北京:科学出版社),2018.300.
[4] KAN Chun-yue,WANG Shou-fa,YANG Cui-yun(阚春月,王守法,杨翠云).Journal of Anhui Agricultural Sciences(安徽农业科学),2010,38(15):7956.
[5] Putnam M L.Crop Protection,1995,14(6):517.
[6] FENG Lei,GAO Ji-xing,HE Yong,et al(冯雷,高吉兴,何勇,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2013,44(9):169.
[7] Bausch W C,Duke H R.Transactions of the ASAE,1996,39(5):1869.
[8] WANG Fu-min,WANG Yuan,HUANG Jing-feng(王福民,王渊,黄敬峰).Remote Sensing Technology and Application(遥感技术与应用),2004,19(2):80.
[9] HE Xiao-ling,WANG Song,Wang Pei,et al(何晓玲,王松,王沛,等).Journal of Shihezi University Natural Science Edition(石河子大学学报自然科学版),2015,33(3):281.
[10] LAN Shi-chao,JIANG Shan(兰世超,姜山).Guizhou Science(贵州科学),2013,31(3):17.
[11] LI Yun-mei,NI Shao-xiang,HUANG Jing-feng(李云梅,倪绍祥,黄敬峰).Remote Sensing Technology and Application(遥感技术与应用),2003,18(1):1.
[12] Kokaly R F,Clark R N.Remote Sensing of Environment,1999,67(3):267.
[13] Anne-Katrin M,Ulrike S,Christian H,et al.Plant Methods,2012,8(1):3.
[14] Wehbe K,Vezzalini M,Cinque G.Analytical and Bioanalytical Chemistry,2018,410(12):3003.
[15] ZHANG Jian,MENG Jing,ZHAO Bi-quan,et al(张建,孟晋,赵必权,等).Spectroscopy and Spectral Analysis(光谱学与光谱分析),2018,38(3):737.
[16] Mendoza F A,Cichy K A,Sprague C,et al.Journal of the Science of Food and Agriculture,2018,98(1):283.
[17] Lee H,Kim M S,Song Y,et al.Journal of the Science of Food and Agriculture,2017,97(4):1084.
[18] SUN Jun,JIN Xiao-ming,MAO Han-ping,et al(孙俊,金夏明,毛罕平,等).Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2014,30(10):167.
[19] Liu Y,Lyu Q,He S,et al.International Journal of Agricultural & Biological Engineering,2015,8(2):80.
[20] SUN Jun,WEI Ai-guo,MAO Han-ping,et al(孙俊,卫爱国,毛罕平,等).Transactions of the Chinese Society of Agricultural Machinery(农业机械学报),2014,45(7):272.
[21] Berdugo C A,Zito R,Paulus S,et al.Plant Pathology,2014,63(6):1344.
[22] WANG Jian,LI Zhen,HONG Tian-sheng,et al(王建,李震,洪添胜,等).Journal of Agricultural Mechanization Research(农机化研究),2015,40(7):18.
[23] Behmann J,Mahlein A,Paulus S,et al.Machine Vision and Applications,2016,27(5):611.
[24] Roth G A,Tahiliani S,Neu-Baker N M,et al.Wiley Interdiscip Rev Nanomed Nanobiotechnol,2015,7(4):565.
[25] LEI Yu,HAN De-jun,CENG Qing-dong,et al(雷雨,韩德俊,曾庆东,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2018,(5):1.
[26] WANG Li,MA Tian-lan,HE Xiao-guang,et al(王莉,马天兰,贺晓光,等).Science and Technology of Food Industry(食品工业科技),2017,22:242.
[27] XIAO Gong-hai,SHU Rong,XUE Yong-qi(肖功海,舒嵘,薛永祺).Optics and Precision Engineering(光学精密工程),2004,12(4):367.
[28] HE Xiao-kang,LIU Shu-nan,CHEN Xiao-jun,et al(何小亢,刘树楠,陈小军,等).Chinese Journal of Light Scattering(光散射学报),2012,24(3):294.
[29] WANG Xin,HU Yang-yang(王鑫,胡洋洋).Transducer and Microsystem Technologies(传感器与微系统),2016,35(12):146.
[30] Heraud P,Cowan M F,Marzec K M,et al.Scientific Reports,2018,8(1):2691.
[31] NAN Miao-qing,WANG Shuang,WANG Kai-ge,et al(南妙晴,王爽,王凯歌,等).Acta Photonica Sinica(光子学报),2013,42(9):1129.
[32] Heraud P,Wood B R,Tobin M J,et al.MEMS Microbiology Letters,2005,249(2):219.
[33] Murdock J N,Dodds W K,Wetzel D L.Vibrational Spectroscopy,2008,48(2SI):179.
[34] LIU Jing-hua,HUANG Qing(刘京华,黄青).The Journal of Light Scattering(光散射学报),2014,26(3):321.
[35] MA De-gui,SHAO Lu-shou,GE Jing,et al(马德贵,邵陆寿,葛婧,等).Chinese Agricultural Science Bulletin(中国农学通报),2008,24(9):485.
[36] GE Jing,SHAO Lu-shou,DING Ke-jian,et al(葛婧,邵陆寿,丁克坚,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2008,39(1):114.
[37] FENG Jie,LI Hong-ning,YANG Wei-ping,et al(冯洁,李宏宁,杨卫平,等).Spectroscopy and Spectral Analysis(光谱学与光谱分析),2010,30(2):426.
[38] TIAN You-wen,LI Tian-lai,ZHANG Lin,et al(田有文,李天来,张琳,等).Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2010,26(5):202.
[39] Lorente D,Blasco J,Serrano A J,et al.Food and Bioprocess Technology,2013,6(12):3613.
[40] Ashourloo D,Mobasheri M,Huete A.Remote Sensing,2014,6(6):4723.
[41] Baranowski P,Jedryczka M,Mazurek W,et al.PLOS ONE,2015,10(3):e122913.
[42] Iori A,Scala V,Cesare D,et al.European Journal of Plant Pathology,2015,141(4):689.
[43] Mo C,Kim G,Lim J,et al.Sensors,2015,15(11):29511.
[44] Abdulridha J,Ehsani R,de Castro A.Agriculture,2016,6(4):56.
[45] Zhu Hongyan,Chu Bingquan,Zhang Chu,et al.Scientific Reports,2017,7(1):4125.
[46] Zhao X,Wang W,Chu X,et al.Applied Sciences,2017,7(1):90.
[47] Lee H,Kim M S,Song Y,et al.Journal of the Science of Food and Agriculture,2017,97(4):1084.
[48] Rodgers J L,Nicewander A W.The American Statistician,1988,42(3):59.
[49] Blasco J,Aleixos N,Gómez J,et al.Journal of Food Engineering,1994,83(3):384.
[50] Ponsa D,López A.Pattern Recognition and Image Analysis,2007,4477:47.
[51] ZHANG Han,ZHAO Xiao-min,GUO Xi,et al(张晗,赵小敏,郭熙,等).Jiangsu Agricultural Sciences(江苏农业科学),2018,46(12):1.
[52] Dhau I,Adam E,Mutanga O,et al.Geocarto International,2017,doi:10.1080/10106049.2017.1343391.
[53] Das P K,Laxman B,Rao S V C K,et al.Internation Journal of Pest Management,2015,61(4):359.
[2] DAI Xiao-feng,YE Zhi-hua,CAO Ya-zhong,et al(戴小枫,叶志华,曹雅忠,等).Chinese Journal of Applied Ecology(应用生态学报),1999,10(1):119.
[3] HONG Ni,GAO Bi-da(洪霓,高必达).Plant Disease Quarantine(植物病害检疫学).Beijing:Science Press(北京:科学出版社),2018.300.
[4] KAN Chun-yue,WANG Shou-fa,YANG Cui-yun(阚春月,王守法,杨翠云).Journal of Anhui Agricultural Sciences(安徽农业科学),2010,38(15):7956.
[5] Putnam M L.Crop Protection,1995,14(6):517.
[6] FENG Lei,GAO Ji-xing,HE Yong,et al(冯雷,高吉兴,何勇,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2013,44(9):169.
[7] Bausch W C,Duke H R.Transactions of the ASAE,1996,39(5):1869.
[8] WANG Fu-min,WANG Yuan,HUANG Jing-feng(王福民,王渊,黄敬峰).Remote Sensing Technology and Application(遥感技术与应用),2004,19(2):80.
[9] HE Xiao-ling,WANG Song,Wang Pei,et al(何晓玲,王松,王沛,等).Journal of Shihezi University Natural Science Edition(石河子大学学报自然科学版),2015,33(3):281.
[10] LAN Shi-chao,JIANG Shan(兰世超,姜山).Guizhou Science(贵州科学),2013,31(3):17.
[11] LI Yun-mei,NI Shao-xiang,HUANG Jing-feng(李云梅,倪绍祥,黄敬峰).Remote Sensing Technology and Application(遥感技术与应用),2003,18(1):1.
[12] Kokaly R F,Clark R N.Remote Sensing of Environment,1999,67(3):267.
[13] Anne-Katrin M,Ulrike S,Christian H,et al.Plant Methods,2012,8(1):3.
[14] Wehbe K,Vezzalini M,Cinque G.Analytical and Bioanalytical Chemistry,2018,410(12):3003.
[15] ZHANG Jian,MENG Jing,ZHAO Bi-quan,et al(张建,孟晋,赵必权,等).Spectroscopy and Spectral Analysis(光谱学与光谱分析),2018,38(3):737.
[16] Mendoza F A,Cichy K A,Sprague C,et al.Journal of the Science of Food and Agriculture,2018,98(1):283.
[17] Lee H,Kim M S,Song Y,et al.Journal of the Science of Food and Agriculture,2017,97(4):1084.
[18] SUN Jun,JIN Xiao-ming,MAO Han-ping,et al(孙俊,金夏明,毛罕平,等).Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2014,30(10):167.
[19] Liu Y,Lyu Q,He S,et al.International Journal of Agricultural & Biological Engineering,2015,8(2):80.
[20] SUN Jun,WEI Ai-guo,MAO Han-ping,et al(孙俊,卫爱国,毛罕平,等).Transactions of the Chinese Society of Agricultural Machinery(农业机械学报),2014,45(7):272.
[21] Berdugo C A,Zito R,Paulus S,et al.Plant Pathology,2014,63(6):1344.
[22] WANG Jian,LI Zhen,HONG Tian-sheng,et al(王建,李震,洪添胜,等).Journal of Agricultural Mechanization Research(农机化研究),2015,40(7):18.
[23] Behmann J,Mahlein A,Paulus S,et al.Machine Vision and Applications,2016,27(5):611.
[24] Roth G A,Tahiliani S,Neu-Baker N M,et al.Wiley Interdiscip Rev Nanomed Nanobiotechnol,2015,7(4):565.
[25] LEI Yu,HAN De-jun,CENG Qing-dong,et al(雷雨,韩德俊,曾庆东,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2018,(5):1.
[26] WANG Li,MA Tian-lan,HE Xiao-guang,et al(王莉,马天兰,贺晓光,等).Science and Technology of Food Industry(食品工业科技),2017,22:242.
[27] XIAO Gong-hai,SHU Rong,XUE Yong-qi(肖功海,舒嵘,薛永祺).Optics and Precision Engineering(光学精密工程),2004,12(4):367.
[28] HE Xiao-kang,LIU Shu-nan,CHEN Xiao-jun,et al(何小亢,刘树楠,陈小军,等).Chinese Journal of Light Scattering(光散射学报),2012,24(3):294.
[29] WANG Xin,HU Yang-yang(王鑫,胡洋洋).Transducer and Microsystem Technologies(传感器与微系统),2016,35(12):146.
[30] Heraud P,Cowan M F,Marzec K M,et al.Scientific Reports,2018,8(1):2691.
[31] NAN Miao-qing,WANG Shuang,WANG Kai-ge,et al(南妙晴,王爽,王凯歌,等).Acta Photonica Sinica(光子学报),2013,42(9):1129.
[32] Heraud P,Wood B R,Tobin M J,et al.MEMS Microbiology Letters,2005,249(2):219.
[33] Murdock J N,Dodds W K,Wetzel D L.Vibrational Spectroscopy,2008,48(2SI):179.
[34] LIU Jing-hua,HUANG Qing(刘京华,黄青).The Journal of Light Scattering(光散射学报),2014,26(3):321.
[35] MA De-gui,SHAO Lu-shou,GE Jing,et al(马德贵,邵陆寿,葛婧,等).Chinese Agricultural Science Bulletin(中国农学通报),2008,24(9):485.
[36] GE Jing,SHAO Lu-shou,DING Ke-jian,et al(葛婧,邵陆寿,丁克坚,等).Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2008,39(1):114.
[37] FENG Jie,LI Hong-ning,YANG Wei-ping,et al(冯洁,李宏宁,杨卫平,等).Spectroscopy and Spectral Analysis(光谱学与光谱分析),2010,30(2):426.
[38] TIAN You-wen,LI Tian-lai,ZHANG Lin,et al(田有文,李天来,张琳,等).Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2010,26(5):202.
[39] Lorente D,Blasco J,Serrano A J,et al.Food and Bioprocess Technology,2013,6(12):3613.
[40] Ashourloo D,Mobasheri M,Huete A.Remote Sensing,2014,6(6):4723.
[41] Baranowski P,Jedryczka M,Mazurek W,et al.PLOS ONE,2015,10(3):e122913.
[42] Iori A,Scala V,Cesare D,et al.European Journal of Plant Pathology,2015,141(4):689.
[43] Mo C,Kim G,Lim J,et al.Sensors,2015,15(11):29511.
[44] Abdulridha J,Ehsani R,de Castro A.Agriculture,2016,6(4):56.
[45] Zhu Hongyan,Chu Bingquan,Zhang Chu,et al.Scientific Reports,2017,7(1):4125.
[46] Zhao X,Wang W,Chu X,et al.Applied Sciences,2017,7(1):90.
[47] Lee H,Kim M S,Song Y,et al.Journal of the Science of Food and Agriculture,2017,97(4):1084.
[48] Rodgers J L,Nicewander A W.The American Statistician,1988,42(3):59.
[49] Blasco J,Aleixos N,Gómez J,et al.Journal of Food Engineering,1994,83(3):384.
[50] Ponsa D,López A.Pattern Recognition and Image Analysis,2007,4477:47.
[51] ZHANG Han,ZHAO Xiao-min,GUO Xi,et al(张晗,赵小敏,郭熙,等).Jiangsu Agricultural Sciences(江苏农业科学),2018,46(12):1.
[52] Dhau I,Adam E,Mutanga O,et al.Geocarto International,2017,doi:10.1080/10106049.2017.1343391.
[53] Das P K,Laxman B,Rao S V C K,et al.Internation Journal of Pest Management,2015,61(4):359.