Using novel ebb and flow hydroponic system lettuce (Lactuca sativa L.) samples were grown and then stored under different postharvest conditions (greenhouse with a cube, refrigerator with a cube, and refrigerator without a cube). The effect of the postharvest conditions on bioactive compounds profile and antioxidant activity was studied. All samples were subjected to the bioactive compounds composition analysis as well as to the antioxidant activity determination in order to reveal how the postharvest conditions affect them. The experimental data were used for the antioxidant activity modeling by artificial neural network (ANN) approach. The antioxidant activity was determined by DPPH assay and expressed as IC50. According to the standard statistical parameters, comparison of the experimentally observed and predicted data, and residuals analysis, generated ANNs could be used for the prediction of the antioxidant activity. Practical applications Lettuce (Lactuca sativa L.) samples were grown using novel Ebb and Flow hydroponic system. Different postharvest conditions were used for samples storage. Generated models for the prediction of antioxidant activity were obtained using artificial neural network (ANN) modeling.

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In this paper, 52 common bean (Phaseolus vulgaris L.) genotypes were analyzed regarding their phytochemical composition and antioxidant activity, as well as other characteristics (grain coat color, grain size, and growth size). The total phenols content (TPC), determined according to the Folin–Ciocalteu method, varied from 0.166 to 0.772 mg/100 g DM, while total flavonoids content (TFC), determined by aluminum chloride colorimetric assay, varied from 4.861 to 161.861 mg/100 g DM. Antioxidant activity was assessed by 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) scavenging capacity and ranged from 1.419 to 12.917 mg/ml. The antioxidant activity was predicted using multiple linear regression (MLR). The obtained results revealed certain influence of grain coat color on common bean phytochemical composition and antioxidant activity that was confirmed throughout classification method—principal component analysis (PCA). White grain coat color samples were distinguished from colored ones on the basis of their phytochemical composition and antioxidant activity. Practical applications The antioxidant activity of 52 common bean (Phaseolus vulgaris L.) genotypes was predicted using MLR. A certain influence of grain coat color on common bean phytochemical composition and antioxidant activity was detected applying classification chemometric techniques.

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