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Single-stranded DNA (ssDNA) aptamers against four organophosphorus pesticides (phorate, profenofos, isocarbophos and omethoate) were simultaneously isolated from an immobilized random ssDNA library by systematic evolution of ligands by exponential enrichment (SELEX) technique. After 12 rounds of in vitro selection, five ssDNA aptamer candidates were(More)
Broccoli grading was studied based on computer vision and neural networks. Broccoli images were captured and the five parameters of color and shape (b*, TCD, Hdeg, proportion of yellowness area, roundness) were extracted and calculated from those images by images analysis method such as background purification, color segmentation, gray transform etc. A new(More)
The use of non-destructive methods to detect egg hatching properties could increase efficiency in commercial hatcheries by saving space, reducing costs, and ensuring hatching quality. For this purpose, a hyperspectral imaging system was built to detect embryo development and vitality using spectral and morphological information of hatching eggs. A total of(More)
This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS). A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar(More)
To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network(More)
A rapid method of predicting the growing situation of Pseudomonas aeruginosa is presented. Gas sensors were used to acquire volatile compounds generated by P. aeruginosa on agar plates and meat stuffs. Then, optimal sensors were selected to simulate P. aeruginosa growth using modified Logistic and Gompertz equations by odor changes. The results showed that(More)
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