Application of a spore detection system based on diffraction imaging to tomato gray mold - Wang, Yafei; Shi, Qiang; Ren, Shanjian; Li, Tiezhu; Yang, Ning; Zhang, Xiaodong; Ma, Guoxin; Taha, Mohamed Farag; Mao, Hanping (International Journal of Agricultural and Biological Engineering, 2024)
This study addresses the challenge posed by the small spore size of tomato gray mold, which hinders its identification and enumeration by conventional techniques. This work presents a novel approach for quantifying spore counts of tomato gray mold using diffraction imaging technology and image processing techniques. To construct a device for acquiring diffraction images of tomato gray mold spores, initially, the hyperspectral data pertaining to the gray mold spores of tomatoes was obtained. The characteristic wavelength of the light source of the diffraction image acquisition device was obtained by smoothing, principal component analysis, and comprehensive coefficient weight calculation. Then, the key parameters of the system were simulated, and the diffraction image acquisition device was built. Finally, tomato gray mold spores were counted based on angular spectrum reconstruction and image processing. The findings indicated that the combined contribution rate of the initial and secondary principal components of the original spectral data obtained from tomato gray mold spore samples amounted to 92.271%. The visible range of 435 nm, 475 nm, and 720 nm can be selected as the light source for tomato gray mold’s spore diffraction imaging system. CMOS image sensor was installed 45 mm below the micropore with a diameter of 100 μm, and the diffraction image obtained by simulation has a clear diffraction fingerprint. The diffraction imaging system can collect diffraction images of disease spores, and the collected diffraction images have clear diffraction fingerprints. The experimental error range was 5.13%-8.57%, and the average error was 6.42%. The error was within a 95% consistency. Therefore, this study can provide a research basis for the classification and recognition of greenhouse disease spores. Keywords: greenhouse, tomato gray mold, spore detection, diffraction imaging, image processingDOI: 10.25165/j.ijabe.20241706.8537Citation: Wang Y F, Shi Q, Ren S J, Li T Z, Yang N, Zhang X D, et al. Application of a spore detection system based ondiffraction imaging to tomato gray mold. Int J Agric & Biol Eng, 2024; 17(6): 212–217.