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基于光譜分形維數(shù)的水稻白葉枯病害監(jiān)測(cè)指數(shù)研究
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國(guó)家自然科學(xué)基金項(xiàng)目(31601545)和中央高?;究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(KJQN201732)


Monitoring Index of Rice Bacterial Blight Based on Hyperspectral Fractal Dimension
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    摘要:

    針對(duì)缺乏有效監(jiān)測(cè)水稻葉片感染白葉枯病害光譜指數(shù)的問(wèn)題,以分蘗期的水稻葉片為研究對(duì)象,,采集了接種白葉枯病菌的水稻葉片和對(duì)照處理的水稻葉片各200片,,利用高光譜成像裝置獲取373~1033nm波段的水稻葉片光譜數(shù)據(jù),選取450~900nm波段的水稻葉片高光譜數(shù)據(jù)作為樣本,。從每個(gè)樣本中選取一個(gè)感興趣區(qū)域(Region of interest, ROI)并計(jì)算平均光譜,,經(jīng)過(guò)Savtzky-Golay平滑處理得到平均光譜曲線;為了定量描述水稻葉片是否感染病害,,提出將光譜分形維數(shù)(Fractal dimension, FD)作為定量描述水稻白葉枯病害的監(jiān)測(cè)光譜指數(shù),,實(shí)現(xiàn)對(duì)白葉枯病害的監(jiān)測(cè),。通過(guò)分析光譜指數(shù)(Spectral index, SI)和FD,建立SI和FD之間的多元線性關(guān)系,,同時(shí)比較了FD與其他常用監(jiān)測(cè)指數(shù)對(duì)白葉枯病害監(jiān)測(cè)的有效性,。結(jié)果表明:水稻白葉枯病害在綠峰(510~560nm)和紅谷(650~690nm)波譜內(nèi)的響應(yīng)較為敏感;針對(duì)健康和感病葉片,,F(xiàn)D與SI之間存在較好的多元線性關(guān)系,,說(shuō)明FD與光譜曲線有較好的對(duì)應(yīng)關(guān)系,可以作為定量描述葉片健康狀況的光譜指數(shù),;與常用監(jiān)測(cè)指數(shù)相比,,本文病害監(jiān)測(cè)指數(shù)與水稻染病具有更高的相關(guān)性,其相關(guān)系數(shù)達(dá)到了0.9840,,指數(shù)分布穩(wěn)定性更高,。本研究結(jié)果說(shuō)明基于光譜反射曲線的圓規(guī)分形維數(shù)對(duì)判斷水稻葉片是否感染白葉枯病害是可行的,為水稻白葉枯病害的監(jiān)測(cè)提供了一種新方法,。

    Abstract:

    With the rapid development of rice phenotype research, rice disease research has also made significant progress as an essential part of rice phenotype research. Bacterial blight disease is one of the three major diseases of rice. Still, there is a lack of an effective spectral index for monitoring whether rice leaves are infected with bacterial blight. Taking rice leaves at the tillering stage as the research object, totally 200 pieces of rice leaves inoculated with Xanthomonas oryzae, and control group were collected respectively. A hyperspectral imaging device was used to obtain the spectral data of rice leaves in the band of 373~1033nm, and eventually, the band of 450~900nm was selected. The hyperspectral data of rice leaves in the wave band was used as a sample. The region of interest (ROI) was selected from each sample and the average spectrum was calculated. After applying Savtzky-Golay smoothing, the average spectrum curve was obtained. In order to quantitatively describe whether the rice leaves were infected or not, the spectral fractal dimension (FD) as a monitoring spectral index for quantitatively describing rice bacterial leaf blight disease was used. By analyzing the spectral index (SI) and FD, the multivariate linear relationship between SI and FD was established, and the effectiveness of FD and other commonly used monitoring indexes for bacterial blight monitoring were compared. The results showed that the response of rice bacterial leaf blight in the green peak (510~560nm) and red valley (650~690nm) spectrum was more sensitive;for healthy and susceptible leaves, there was a good relationship between FD and SI. The multivariate linear relationship of FD indicated that FD had a good corresponding relationship with the spectral curve, which can be used as a spectral index to quantitatively describe the health of leaves;compared with the commonly used monitoring index, the proposed disease monitoring index had a high correlation with whether rice was infected or not. The correlation coefficient reached 0.9840, and the distribution was more stable. The results indicated that the fractal dimension based on the spectral reflectance curve was feasible for judging whether rice leaves were infected with bacterial blight and provided a method for early monitoring of rice bacterial blight.

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曹益飛,袁培森,王浩云,KOROHOU Tchalla Wiyao,范加勤,徐煥良.基于光譜分形維數(shù)的水稻白葉枯病害監(jiān)測(cè)指數(shù)研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2021,52(9):134-140. CAO Yifei, YUAN Peisen, WANG Haoyun, KOROHOU Tchalla Wiyao, FAN Jiaqin, XU Huanliang. Monitoring Index of Rice Bacterial Blight Based on Hyperspectral Fractal Dimension[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(9):134-140.

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  • 收稿日期:2020-10-09
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  • 在線發(fā)布日期: 2021-09-10
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