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Application of a spore detection system based on diffraction imaging to tomato gray mold
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作者 Yafei Wang Qiang Shi +6 位作者 Shanjian Ren Tiezhu Li Ning Yang Xiaodong Zhang Guoxin Ma Mohamed Farag Taha Hanping Mao 《International Journal of Agricultural and Biological Engineering》 2024年第6期212-217,共6页
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 spor... 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 100μm,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. 展开更多
关键词 GREENHOUSE tomato gray mold spore detection diffraction imaging image processing
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Detection and quantification of Bacillus cereus and its spores in raw milk by qPCR,and distinguish Bacillus cereus from other bacteria of the genussBacillus 被引量:4
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作者 Lijiao Liang Ping Wang +3 位作者 Tianming Qu Xiaomei Zhao Yiqiang Ge Ying Chen 《Food Quality and Safety》 SCIE CSCD 2022年第3期386-395,共10页
Introduction:Raw milk is the basic raw material of dairy products.Bacillus cereus(B.cereus)is a typical conditional pathogenic bacteria and cold-phagocytic spoilage bacteria in raw milk.Materials and Methods:In this s... Introduction:Raw milk is the basic raw material of dairy products.Bacillus cereus(B.cereus)is a typical conditional pathogenic bacteria and cold-phagocytic spoilage bacteria in raw milk.Materials and Methods:In this study,a quantitative polymerase chain reaction(qPCR)method for detecting B.cereus in raw milk was established.The specificity of the method was verified by using other Bacillus bacteria and pathogenic bacteria;the sensitivity of the method was evaluated by preparing recombinant plasmids and simulated contaminated samples;and the applicability of the method was verified using pure spore DNA.The actual sample detection was completed by using the established qPCR method.Results:The qPCR established in this study can specifically detect B.cereus in raw milk.The limit of detection of the method was as low as 200 CFU/mL,the limit of quantification ranged from 2×10^(2)to 2×10^(8)CFU/mL,and the amplification efficiency of qPCR was 96.6%.Conclusions:The method established in this study can distinguish B.cereus from other Bacillus bacteria,and spore DNA can be used as the detection object.This method has the advantages of strong specificity,high sensitivity,wide application range,and short detection time,which isexpectedtobeapplied in thedairy industry. 展开更多
关键词 Raw milk quality control Bacillus cereus detection SYBR Green real-time qPCR spore DNA detection
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