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水稻病害孢子多光譜衍射識(shí)別與病害源定位方法研究
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國(guó)家自然科學(xué)基金(面上)項(xiàng)目(32171895)、國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2019YFC1606600-03)、江蘇大學(xué)農(nóng)裝學(xué)部項(xiàng)目(NZXB20200205)、水稻生物學(xué)國(guó)家重點(diǎn)實(shí)驗(yàn)室開(kāi)放項(xiàng)目(20200302)和湛江市科技計(jì)劃項(xiàng)目(2021A05235)


Multispectral Diffraction Identification of Rice Disease Spores and Localization Method of Disease Source
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    摘要:

    水稻真菌病害主要依賴真菌孢子在空氣中進(jìn)行傳播。然而各種水稻病害孢子的形態(tài)相近,傳統(tǒng)孢子捕捉儀和顯微圖像法難以對(duì)其進(jìn)行區(qū)分。為了能夠準(zhǔn)確識(shí)別目標(biāo)病害孢子并進(jìn)行病害源定位,提出了一種水稻病害孢子多光譜衍射識(shí)別與病害源定位方法。為了解決傳統(tǒng)衍射方法無(wú)法識(shí)別形態(tài)相似的缺點(diǎn),設(shè)計(jì)了一種大視場(chǎng)、無(wú)透鏡的多光譜衍射成像傳感器。通過(guò)分析病害孢子衍射指紋圖譜,解析稻瘟病菌、稻曲病菌孢子多光譜衍射成像特征規(guī)律。融合孢子的形態(tài)特征和吸收特性,提出指紋分離強(qiáng)度和相對(duì)峰差兩個(gè)特征參數(shù),建立孢子的多光譜衍射識(shí)別模型。通過(guò)仿真計(jì)算實(shí)驗(yàn)分析孢子傳播規(guī)律,耦合環(huán)境信息建立孢子傳播過(guò)程中的擴(kuò)散模型。在無(wú)定向風(fēng)及有定向風(fēng)條件下分析孢子的空間分布情況,提出病害爆發(fā)源迭代質(zhì)心定位算法。實(shí)驗(yàn)結(jié)果表明,本文方法對(duì)水稻病害孢子的識(shí)別率達(dá)到98.5%,對(duì)無(wú)定向風(fēng)條件下的定位誤差最低為4.9%,對(duì)有定向風(fēng)條件下的定位誤差最低為7.1%。

    Abstract:

    Rice fungal diseases mainly rely on fungal spores for airborne transmission. However, the morphology of various rice disease spores is similar, and it is difficult to distinguish them by traditional spore trap and microscopic image methods. To be able to accurately identify target disease spores and locate the disease source, a multispectral diffraction identification and disease source localization method for rice disease spores was proposed. A large field-of-view, lens-free multispectral diffraction imaging sensor was designed to address the shortcomings of traditional diffraction methods that cannot identify morphological similarities. By analyzing the disease spore diffraction fingerprinting, the multi-spectral diffraction imaging characteristic pattern of rice blast and rice curd spores was analyzed. By integrating the morphological characteristics and absorption properties of spores, two characteristic parameters of fingerprint separation intensity and relative peak difference were proposed to establish the multispectral diffraction identification model of spores. The spore propagation law was analyzed by simulation and calculation experiments, and the diffusion model in the process of spore propagation was established by coupling environmental information. The spatial distribution of spores was analyzed under the conditions of non-directional wind and directional wind, and an iterative plasmodial localization algorithm of the disease outbreak source was proposed. The experimental results showed that the recognition rate of rice disease spores reached 98.5%, and the localization error was as low as 4.9% for undirected wind conditions and 7.1% for directed wind conditions. This method can provide a reference in locating the source of crop disease outbreaks.

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楊寧,張?zhí)炀?張釗源,張曉東,毛罕平,袁壽其.水稻病害孢子多光譜衍射識(shí)別與病害源定位方法研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2023,54(4):250-258. YANG Ning, ZHANG Tianwei, ZHANG Zhaoyuan, ZHANG Xiaodong, MAO Hanping, YUAN Shouqi. Multispectral Diffraction Identification of Rice Disease Spores and Localization Method of Disease Source[J]. Transactions of the Chinese Society for Agricultural Machinery,2023,54(4):250-258.

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  • 收稿日期:2022-06-26
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  • 在線發(fā)布日期: 2022-08-23
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