Food analysis is a challenging analytical problem, often addressed using sophisticated
laboratory methods that produce large data sets. Linear and non-linear multivariate methods …

New strategies to combat hunger are a current and urgent demand. The increase in
population has generated a high demand for products and services that affect food …

Multivariate approaches like machine learning are commonly used in estimation of
biochemical traits from spectral and color characteristics of foodstuffs and agricultural …

The Support vector regression (SVR) was used to investigate quantitative structure–activity
relationships (QSAR) of 75 phenolic compounds with Trolox-equivalent antioxidant capacity …

Quantitative structure–activity relationships (QSARs) built using machine learning methods,
such as artificial neural networks (ANNs) are powerful in prediction of (antioxidant) activity …

Rooibos is brewed from the medicinal plant Aspalathus linearis. It has a well-established
wide spectrum of bio-activity properties, which in part may be attributed to the phenolic …

The contribution of the individual polyphenols of Basque cider to the antioxidant activity and
browning has been determined. Nineteen monovarietal musts were obtained using different …

This work reports the evolution of polyphenolic compounds content during the cidermaking
process in the Basque Country (Northern Spain). Fourteen monovarietal musts were …

It is a well-established consensus among researchers that diets rich in fruits and vegetables
significantly reduce the risk of numerous forms of cancer and cardiovascular diseases …

Abstract Models of multiple linear regression and multilayer artificial neural network have
been developed for modeling and predicting the stability constants of sodium and potassium …