New Spectral Classification Index for Rapid Identification of Fusarium Infection in Wheat Kernel
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New Spectral Classification Index for Rapid Identification of Fusarium Infection in Wheat Kernel Dongyan Zhang 1 & Qian Wang 1 & Fenfang Lin 2 & Shizhuang Weng 1 & Yu Lei 1 & Gao Chen 1 & Chunyan Gu 3 & Ling Zheng 1 Received: 16 January 2020 / Accepted: 29 July 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Fusarium-damaged kernels (FDK) contain a wide spectrum of mycotoxins, affecting the quality and safety of wheat used as food and feed. At present, traditional methods to detect FDK are time-consuming and laborious. Therefore, we propose herein a new spectral classification index (NSCI) method that can provide simple and low-cost FDK detection by analysing spectra in the wavelength range 350–2500 nm. The proposed index was based on the spectral reflectance and its first derivative. Frequency histograms were plotted for each class of index value, and Gaussian curve fitting was carried out for each histogram. Wheat kernels were then classified by using the intersection of the Gaussian curves as a threshold. The classification of NSCI for spectral data obtained the detection accuracy of 0.97, with a specificity of 0.99, a sensibility of 0.93 and a training time of 15.07 s. Compared with other spectral indexes and machine learning methods, the NSCI was more equilibrated in terms of efficiency and accuracy. Meanwhile, the threshold could be tuned to adjust accuracy, sensitivity or specificity to satisfy different practical needs. We also applied the NSCI for kernel hyperspectral data in another year, and the classification results is promising. The proposed method has the potential for the rapid and simple detection of FDK in wheat. Keywords Spectral reflectance . Machine learning . Fusarium damages kernel . Two-band index . Index distribution
Introduction Fusarium head blight (FHB) is the most important disease in wheat worldwide that can cause significant loss of yield and quality of wheat. FHB occurs at the flowering to early kernel-fill stages under conducive conditions such as warm temperature and high humidity. The disease is caused by various Fusarium species, producing a wide range of mycotoxins, including trichothecenes, zearalenone,
fumonisins, enniatins, beauvericin and moniliformin. These mycotoxins accumulate in wheat kernels and can seriously threaten human and animal health by interfering ribosomal peptidyl transferase activity, blocking ribosome circulation, and inhibiting protein synthesis (Gilbert et al. 2014; Pestka and Smolinski 2005). Therefore, detection procedures are needed to remove wheat kernels infected by the Fusarium fungus before processing to reduce the risks of poison caused by these mycotoxins.
* Ling Zheng [email protected]
Gao Chen [email protected]
Dongyan Zhang [email protected] Qian Wang [email protected]
Chunyan Gu [email protected] 1
National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei 230601, China
2
School of Geography and Remote Sensing, Nanjing University of
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