Abstract

In this paper, the Trolox equivalent antioxidant capacity (TEAC) is estimated through a robust machine-learning algorithm known as the Particle Swarm Optimization-based Extreme Learning Machine (PSO-ELM) model. For this purpose, a large dataset from previously published reports was gathered. Various analyses were performed to evaluate the proposed model. The results of the statistical analysis showed that this model can predict the actual values with high accuracy, so that the calculated R2 and RMSE values were equal to 0.973 and 3.56, respectively. Sensitivity analysis was also performed on the effective input parameters. The leverage technique was also performed to check the accuracy of real data, and the results showed that the majority of data are reliable. This simple yet accurate model can be very powerful in predicting the Trolox equivalent antioxidant capacity values and can be a good alternative to laboratory data.

Highlights

  • Many antioxidant compounds may be found in vegetable materials [1, 2]

  • The Trolox equivalent antioxidant capacity (TEAC) is estimated through a robust machine-learning algorithm known as the Particle Swarm Optimization-based Extreme Learning Machine (PSO-ELM) model

  • We previously evaluated the substances of physiologically active chemicals and the cruciferous seeds’ Trolox equivalent antioxidant capacity during sprouting, and the findings on ascorbic acid levels were previously reported [24]

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Summary

Introduction

Many antioxidant compounds may be found in vegetable materials [1, 2]. To find possible sources of natural antioxidants for use in edible products, many plants have been researched and several substances have been identified [3, 4].Biologists and physicians are interested in antioxidants because of their use for guarding the human organs against the harm of reactive oxygen species (ROS) [5, 6]. Many antioxidant compounds may be found in vegetable materials [1, 2]. To find possible sources of natural antioxidants for use in edible products, many plants have been researched and several substances have been identified [3, 4]. Because of the alleged tight relationship between oxidative stress and illness, antioxidants are thought to be preventive agents against similar illnesses [7, 8]. There is a negative relationship between consuming fruits and vegetables, as the greatest sources of antioxidants, and the cancer risk, so that the risk is reduced by 30-50% [9, 10]. The antioxidant potential of a wide range of substances

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