A supervised machine learning approach for the prediction of antioxidant activities of Amaranthus viridis seed.

This research aimed at modelling and predicting the antioxidant activities of Amaranthus viridis seed extract using four (4) data-driven models. Artificial Neural Network (ANN), Support Vector Machine (SVM), k-nearest Neighbour (k-NN), and Decision Tree (DT) were used as modelling algorithms for the construction of a non-linear empirical model to predict the antioxidant properties of Amaranthus viridis seed extract. Datasets for the modelling operation were obtained from a Box Behnken design while the hyperparameters of the ANN, SVM, k-NN and DT were determined using a 10-fold cross-validation technique. Among the Machine Learning algorithms, DT was observed to exhibit excellent performance and outperformed other Machine Learning algorithms in predicting the antioxidant activities of the seed extract, with a sensitivity of 0.867, precision of 0.928, area under the curve of 0.979, root mean square error of 0.184 and correlation coefficient of 0.9878. It was closely followed by ANN which was used to analyze and explain in detail the effect of the independent variables on the antioxidant activities of the seed extracts. This result affirmed the suitability of DT in predicting the antioxidant activities of Amaranthus viridis.

Lignocellulose, dietary fibre, inulin and their potential application in food.

In recent years, due to food insecurity, lignocellulose, dietary fibre as well as inulin have received wider attention owing to their abundance and being relatively low-cost indigestible polysaccharides. Since the recognition, acceptance of the consumption and utilization of these polysaccharides, as well as their attraction in science and industry has grown tremendously. There have been further researches carried out to ascertain the fact that people who consume or utilize these polysaccharides have low exposure to some fatal life-threatening illnesses. Rich sources of indigestible polysaccharides such as vegetables, cereals, fruits and nuts are beneficial to good health as consuming them reduce the occurrence of degenerating diseases such as colon cancer, heart disease, diabetes, etc. Despite these increasing facts depicting their advantages in the state of human health, their intake and utilization still fall below the acceptable limit and the knowledge of how they work in the human body are minimal with their explicit actions not easily shown. Hence, this review gives a better understanding of the significance of lignocellulose, dietary fibre and inulin, their functions, classifications, types and applications in the food industry, thereby exposing their various uses as these polycarbohydrates were considered a waste before now.