The total phenolic content, anthocyanins, phenolic acids, antioxidant capacity and α-amylase inhibitory activity of black (Aydin Siyahi), purple (Kadife Kemer) and white (Trabzon Kadife) eggplants grown in Turkey were subjected to a comparative investigation. The black cultivar exhibited the highest total phenolic (17,193 and 6552 mg gallic acid equivalent/kg fw), flavonoid (3019 and 1160 quercetin equivalent/kg fw) and anthocyanin (1686 and 6167 g delphinidin-3-O-glucoside equivalent/kg fw) contents in crude extracts of the peel and pulp. The majority of the caffeic acid was identified in the ester (2830 mg/kg fw) and ester-bound (2594 mg/kg fw) forms in the peel of ‘Kadife Kemer’ and in the glycoside form (611.9 mg/kg fw) in ‘Aydin Siyahi’, as well as in the pulp of these two eggplants. ‘Kadife Kemer’ (purple eggplant) contained the majority of the chlorogenic acid in free form (27.55 mg/kg fw), compared to ‘Aydin Siyahi’ in the ester (7.82 mg/kg fw), glycoside (294.1 mg/kg dw) and ester-bound (2.41 mg/kg fw) forms. The eggplant cultivars (peel and pulp, mg/kg fw) exhibited a relatively high delphinidin-3-O-rutinoside concentration in the peel of ‘Aydin Siyahi’ (avg. 1162), followed by ‘Kadife Kemer’ (avg. 336.6), and ‘Trabzon Kadife’ (avg. 215.1). The crude phenolic extracts of the eggplants exhibited the highest antioxidant capacity values (peel and pulp, µmoL Trolox equivalent/kg fw) of 2,2-diphenyl-1-picrylhydrazyl (DPPH, 8156 and 2335) and oxygen radical absorbance capacity (ORAC, 37,887 and 17,648). The overall results indicate that black and purple eggplants are the cultivars with greater potential benefits in terms of their phenolics and antioxidant values than the white eggplant.

The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (R²_p: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (R²_p: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (R²_p) of over 0.70. In addition, the result of the testing model proved the model’s performance by obtaining a similar R² and error to the calibration model.