During food quality control, NIR technology enables the rapid and non-destructive determination of the typical quality characteristics of food categories, their origin, and the detection of potential counterfeits. Over the past 20 years, the NIR results for a variety of food groups—including meat and meat products, milk and milk products, baked goods, pasta, honey, vegetables, fruits, and luxury items like coffee, tea, and chocolate—have been compiled. This review aims to give a broad overview of the NIRS processes that have been used thus far to assist researchers employing non-destructive techniques in comparing their findings with earlier data and determining new research directions.

The nutritional properties of Pleurotus mushrooms were studied to select the varieties with the most favourable properties. These mushrooms have high nutritional value; they are rich in carbohydrates, protein, minerals, vitamins, chitin and reducing compounds, such as phenols and polyphenols. In this study, the polyphenol profiles of thirteen Pleurotus ostreatus cultivars were established by the UHPLC-ESI-MS/MS technique. The results showed that 4-hydroxibenzoic acid, caffeic acid, p-coumaric acid and vanillic acid were the most abundant polyphenolic components in the samples. In addition, the Fourier-transformed near infrared (FT-NIR) spectra of the samples were recorded and evaluated. The correlation between the differences in NIR spectra and the differences in polyphenol patterns of the samples was investigated. The polyphenol results were subjected to several statistical evaluations (Kruskal–Wallis test, Principal Component Analysis (PCA), Spearman correlation analysis, cluster analysis) to detect possible differences between the samples. Relationships between the polyphenol profile and antioxidant capacity (FRAP), total polyphenol content (TPC), free amino acid content (fAA) and the values of each polyphenol component were examined. Based on the results, an effort was made to group the varieties according to the attributes tested.

The FT-NIR technique was used for rapid and non-destructive determination of plum ripeness. The dry matter (DM), titratable acidity (TA), total soluble solids (TSS) and calculated maturity index (MI: TSS/TA) were used as reference values. The PLS correlations were validated via five-fold cross-validation (RMSECV for different parameters: DM: 0.66%, w/w; TA = 0.07%, w/w; TSS = 0.72%, w/w; MI = 1.39) and test set validation (RMSEP for different parameters: DM: 0.65%, w/w TA = 0.07%, w/w; TSS = 0.61%, w/w; MI = 1.50). Different classification algorithms were performed for TA, TSS and MI. Linear, quadratic and Mahalanobis discriminant analysis (LDA, QDA, MDA) were found to be the best sample detection methods. The accuracy of the classification methods was 100% for all investigated parameters and cultivars.