The role of ascorbate peroxidase, guaiacol peroxidase, and polysaccharides in cassava (Manihot esculenta Crantz) roots under postharvest physiological deterioration

Abstract This study aimed to investigate the role of ascorbate peroxidase (APX), guaiacol peroxidase (GPX), polysaccharides, and protein contents associated with the early events of postharvest physiological deterioration (PPD) in cassava roots. Increases in APX and GPX activity, as well as total protein contents occurred from 3 to 5 days of storage and were correlated with the delay of PPD. Cassava samples stained with periodic acid-Schiff (PAS) highlighted the presence of starch and cellulose. Degradation of starch granules during PPD was also detected. Slight metachromatic reaction with toluidine blue is indicative of increasing of acidic polysaccharides and may play an important role in PPD delay. Principal component analysis (PCA) classified samples according to their levels of enzymatic activity based on the decision tree model which showed GPX and total protein amounts to be correlated with PPD. The Oriental (ORI) cultivar was more susceptible to PPD.

Characterization of phenolic compounds and antioxidant properties of Glycyrrhiza glabra L. rhizomes and roots

The present work aims to characterize and quantify the phenolic composition and to evaluate the antioxidant activity of Glycyrrhiza glabra L. (commonly known as licorice) rhizomes and roots. The antioxidant potential of its methanol/water extract could be related with flavones (mainly apigenin derivatives), flavanones (mainly liquirintin derivatives), a methylated isoflavone and a chalcone, identified in the extract. Lipid peroxidation inhibition was the most pronounced antioxidant effect (EC50=0.24±0.01 µg/mL and 22.74±2.42 µg/mL in TBARS and -carotene/linoleate assays, respectively), followed by free radicals scavenging activity (EC50=111.54±6.04 µg/mL) and, finally, reducing power (EC50=128.63±0.21 µg/mL). In this sense, licorice extract could be used as a source of antioxidants for pharmaceutical, cosmetic and/or food industries.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.