Identification of coffee adulteration based on rapid evaporation ionization mass spectrometry technology

doi:10.14088/j.cnki.issn0439-8114.2024.12.031

Abstract

Abstract: Coffee and its adulterated black soybean, black corn, and coffee samples with different proportions of adulteration were evaluated, rapid evaporation ionization mass spectrometry （REIMS） to was used collect primary full scan mass spectrometry data of each sample, a sample principal component analysis linear discriminant analysis （PCA-LDA） model was constructed, and the leave-20%-out mode was validated. The results showed that the correct recognition rate of coffee powder, black soybean powder and black corn powder samples was 100.00%, the correct recognition rate of coffee powder, black soybean powder and different proportion of black soybean powder adulterated with coffee powder samples was 97.07%, and the correct recognition rate of coffee powder, black corn powder and different proportion of black corn powder adulterated with coffee powder samples was 96.60%. Coffee, black soybean, black corn and different proportion of adulterated coffee samples could be better distinguished. The model constructed could achieve instantaneous real-time recognition of samples. Real time identification of random raw material samples and coffee samples with different proportions （5%, 10%, 20%, 30%, 40%, and 50%） of adulteration was carried out using Live ID software. The results showed that all samples were correctly identified, and the detection limit of adulteration proportion could reach as low as 5%. This method could efficiently, quickly, and accurately monitor coffee adulteration, effectively meeting the identification needs of adulterated black soybean and black corn in coffee samples.

Key words: rapid evaporation ionization mass spectrometry, coffee, adulteration, PCA-LDA model

CLC Number:

TS255.1

WU Wan-qin, JIANG Feng, FAN Xiao-long, LI Xing, ZHU Song-song, WANG Wei, ZHANG Li, ZHANG Ya-zhen, ZHU Xiao-ling, FENG Meng. Identification of coffee adulteration based on rapid evaporation ionization mass spectrometry technology[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(12): 171-177.

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