1. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
2. College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China
Abstract：The quality of peanut products were rapidly and non-destructively assessed for storage and edibility safety. Near infrared spectroscopy (NIRS) was applied to develop qualitative and quantitative methods to determine the toxigenic fungal contamination levels in peanuts. Firstly, clean and fresh peanuts were sterilized with Co-60 and inoculated individually with five common toxigenic fungal species in grains, namely A. flavus 3.17, A. flavus 3.3950, A. parastiticus 3.395 0, A. parastiticus 3.012 4, and A. ochraceus 3.648 6. The samples were then incubated for 9 days under suitable conditions (26 ℃, RH 80%). Secondly, diffuse reflectance spectra were collected from peanut samples in the wavenumber range 12 000 to 4 000 cm-1 at different time during the inoculation. Analysis models were developed with principal component analysis (PCA), discriminant analysis (DA) and partial least squares analysis (PLSR), respectively. The results showed that the inoculated different fungal species of peanuts can be effectively distinguished during different storage periods. After peanuts samples were incubated for 0, 3, 6 and 9 days, the overall classification accuracy would be 100% and 99.17% for the treatment of individual fungal and total fungal species by using DA analysis models. PLSR models were also developed to predict the number of colonies of peanut samples with the coefficient of determination of the validation set (R2P) of 0.874 1, root mean square error of cross-validation (RMSECV) of 0.276 Log CFU·g-1 and residual predictive deviation (RPD) of 1.92. The results indicated that the NIR technology could be used as a reliable and rapid analytical method for determination of fungal contamination in peanuts, which could realize quality and safety control in the process of storing of peanuts.
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