A rapid rice blast detection and identification method based on crop disease spores' diffraction fingerprint texture

文献类型： 外文期刊

第一作者： Yang Ning

作者： Yang Ning;Yu Junjie;Zhang Rongbiao;Xie Liangliang;Kwabena, Oppong Paul;Wang Aiying;Tang Jian;Shu Fangyu

作者机构：

关键词： lensless diffraction fingerprint recognition system; fringe intensity contrast (FIC); fringe dispersion (FD); convolutional neural network; rice blast early warning

期刊名称：JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE （ 影响因子：3.638； 五年影响因子：3.802 ）

ISSN： 0022-5142

年卷期： 2020 年 100 卷 9 期

页码：

收录情况： SCI

摘要： BACKGROUND Rice blast fungus is a worldwide disease, and it is one of the most serious rice diseases in the north and south rice fields in China. The initial symptoms of rice blast are not obvious, and the speed of transmission is fast. Manual identification is time-consuming and laborious. At present, it is a great challenge to realize rapid and accurate early identification of rice blast. RESULTS In this paper, an identification method based on crop disease spores' diffraction fingerprint texture for rice blast was studied; this method utilizes the light field and texture features of diffraction images. To verify the reliability of the model that we proposed, we selected two methods of manual identification and machine recognition to compare and detect rice blast spores. The experimental results show that the identification of light diffraction characteristics is not only higher than the traditional manual recognition by microscope (increased by more than 0.3%), but also faster after neural network training (increased by more than 90%). The diffraction recognition method used in this study, based on crop disease spores' diffraction fingerprint texture, can be completed in a few seconds, and its test accuracy is 97.18%. CONCLUSION The proposed method, a rapid rice blast detection and identification method based on crop disease spores' diffraction fingerprint texture, has certain advantages compared with the existing manual identification by microscope. This method can be applied to the recognition of rice blast in agricultural research. (c) 2020 Society of Chemical Industry

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