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Full-Text Articles in Life Sciences
Application Of Dna Barcoding Technology In The Identification Of Adulterated Ingredients Of Edible Blood Products, Li Jiong, Wu Qiong, Jiang Hai, Hu Ming-Jie, Xu Xin-Yi
Application Of Dna Barcoding Technology In The Identification Of Adulterated Ingredients Of Edible Blood Products, Li Jiong, Wu Qiong, Jiang Hai, Hu Ming-Jie, Xu Xin-Yi
Food and Machinery
Objective: A COI sequence-based full-length DNA barcoding technology was established to identify adulteration of seven animal-derived components （including pigs, cows, sheep, chickens, ducks, geese and rabbits） in edible blood products. Methods: After the blood products were extracted and purified by DNA extraction and PCR amplification, the clone sequencing results were submitted to the DNA barcode local database of the 7 blood products for sequence comparison. The pretreatment method, DNA extraction method and PCR amplification conditions of the blood products were also selected and optimized, and various common blood product adulteration models were established to study the lowest adulteration detection rate …
Qualitative And Quantitative Detection Of Camellia Oil Adulteration Based On Electronic Nose, Jiang Han, Li Da-Peng, Wen Tao, Yang Gan, Gong Zhong-Liang
Qualitative And Quantitative Detection Of Camellia Oil Adulteration Based On Electronic Nose, Jiang Han, Li Da-Peng, Wen Tao, Yang Gan, Gong Zhong-Liang
Food and Machinery
Objective: This study aims to realize the adulteration detection of camellia oil mixed with rapeseed oil, soybean oil and corn oil. Methods: The electronic nose detection platform was used for the adulteration detection of camellia oil mixed with different proportion of rapeseed oil, soybean oil and corn oil. Firstly, the linear discriminant analysis （LDA） and support vector machine （SVM） were used for the qualitative identification of camellia oil adulteration. Then multilayer perceptron （MLP） and partial least squares regression （PLSR） were used to establish quantitative prediction models for camellia oil adulteration. Results: The accuracy of SVM for qualitative authentication was higher …
Detection Method Of Mutton Adulteration Based On Pso-Lssvm And Characteristic Wavelengths Extraction, Tian-Tian Cheng, Ke-Jian Wang, Xian-Zhong Han, Shi Li, Yuan Wang
Detection Method Of Mutton Adulteration Based On Pso-Lssvm And Characteristic Wavelengths Extraction, Tian-Tian Cheng, Ke-Jian Wang, Xian-Zhong Han, Shi Li, Yuan Wang
Food and Machinery
In order to solve the problem of fast detection of adulteration of mutton and pork, the spectral collection of adulterated mutton was carried out by using a multi-spectral instrument, and the reflectivity of samples at the band of 350~1 100 nm was obtained. For data preprocessing, Particle Swarm Optimization (PSO) was used to optimize the Least Squares Support Vector Machine (LSSVM), and a Least Squares Support Vector Machine (PSO-LSSVM) model based on Particle Swarm Optimization was established, compared with Partial Least Squares(PLS), Back Propagation Neural Network (BPNN) and LSSVM models. The result showed that PSO algorithm could effectively optimize LSSVM …