Evaluation of phenolic and antioxidant properties of strawberry as a function of extraction conditions

Comparison of high pressure and thermal pasteurization on the quality parameters of strawberry products: a review

Strawberry (Fragaria ananassa) is rich in bioactive compounds with high antioxidant activity. High pressure processing (HPP) is an efficient alternative to preserve these bioactive compounds in terms of microbial inactivation and shelf-life stability. This review compares the effects of pasteurization methods using high pressure or thermal pasteurization (TP) on the quality parameters of various strawberry-based products. To summarize, most of the high pressure-treated products are microbiologically stable and showed minimum degradation of thermolabile compounds than TP-treated ones. However, some studies reported that high pressure did not have an advantage over TP especially in the preservation of phenolic phytochemicals during storage. The insufficient enzyme inactivation and high residual activity of enzymes after high pressure treatment could cause anthocyanins degradation thus affecting the product quality. Overall, this review could be valuable to potential processors in evaluating the effective commercialization of high pressure-treated strawberry products.

Optimization of the Extraction Conditions of Antioxidant Phenolic Compounds from Strawberry Fruits (Fragaria x ananassa Duch.) Using Response Surface Methodology

The subject of this study is to determine the best solvent and optimum extraction conditions for the extraction of maximum antioxidant phenolic compounds and antioxidant activity from strawberry fruits (Fragaria x ananassa Duch.). Extractions were carried out using solvents with different polarities (water, methanol, ethanol, acetonitrile, and acetone). Box-Behnken Design was used to optimize extraction conditions, including extraction time (t), temperature (°C), and liquid/solid (L/S) ratio. In the study, extracts obtained with acetone indicated the highest total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity. The optimal extraction conditions for both responses were determined to be time of 17.5 min, temperature 52.5 °C, and liquid/solid ratio of 30:1. The maximum TPC and TFC values were found as 18.78 ± 0.22 mg of gallic acid equivalent (GAE/g) and 10.52 ± 0.35 mg of catechin equivalents (CE/g) under optimum extraction conditions. The results indicated that optimizing extraction conditions is critical for quantifying antioxidant phenolic compounds. The present model can contribute to finding a cheap way of delivering natural antioxidants in the food, cosmeceutical, and pharmaceutical industries. Furthermore, these results indicate that strawberry fruits (Fragaria x ananassa Duch.) can be a natural food colorant in dietary applications with potential health benefits.

Extraction of Phenolic Compounds with Antioxidant Activity from Strawberries: Modelling with Artificial Neural Networks (ANNs)

This research study focuses on the evaluation of the total phenolic compounds (TPC) and antioxidant activity (AOA) of strawberries according to different experimental extraction conditions by applying the Artificial Neural Networks (ANNs) technique. The experimental data were applied to train ANNs using feed- and cascade-forward backpropagation models with Levenberg-Marquardt (LM) and Bayesian Regulation (BR) algorithms. Three independent variables (solvent concentration, volume/mass ratio and extraction time) were used as ANN inputs, whereas the three variables of total phenolic compounds, DPPH and ABTS antioxidant activities were considered as ANN outputs. The results demonstrate that the best cascade- and feed-forward backpropagation topologies of ANNs for the prediction of total phenolic compounds and DPPH and ABTS antioxidant activity factors were the 3-9-1, 3-4-4-1 and 3-13-10-1 structures, with the training algorithms of trainlm, trainbr, trainlm and threshold functions of tansig-purelin, tansig-tansig-tansig and purelin-tansig-tansig, respectively. The best R² values for the predication of total phenolic compounds and DPPH and ABTS antioxidant activity factors were 0.9806 (MSE = 0.0047), 0.9651 (MSE = 0.0035) and 0.9756 (MSE = 0.00286), respectively. According to the comparison of ANNs, the results showed that the cascade-forward backpropagation network showed better performance than the feed-forward backpropagation network for predicting the TPC, and the FFBP network, in predicting the DPPH and ABTS antioxidant activity factors, had more precision than the cascade-forward backpropagation network. The ANN technique is a potential method for estimating targeted total phenolic compounds and the antioxidant activity of strawberries.

Plant Polyphenols-Biofortified Foods as a Novel Tool for the Prevention of Human Gut Diseases

Plant food biofortification is recently receiving remarkable attention, as it aims to increase the intake of minerals, vitamins, or antioxidants, crucial for their contribution to the general human health status and disease prevention. In this context, the study of the plant’s secondary metabolites, such as polyphenols, plays a pivotal role for the development of a new generation of plant crops, compensating, at least in part, the low nutritional quality of Western diets with a higher quality of dietary sources. Due to the prevalent immunomodulatory activity at the intestinal level, polyphenols represent a nutritionally relevant class of plant secondary metabolites. In this review, we focus on the antioxidant and anti-inflammatory properties of different classes of polyphenols with a specific attention to their potential in the prevention of intestinal pathological processes. We also discuss the latest biotechnology strategies and new advances of genomic techniques as a helpful tool for polyphenols biofortification and the development of novel, healthy dietary alternatives that can contribute to the prevention of inflammatory bowel diseases.