Authentication of carioca common bean cultivars (Phaseolus vulgaris L.) using digital image processing and chemometric tools

SETApp: A machine learning and image analysis based application to automate the sea urchin embryo test

Since countless xenobiotic compounds are being found in the environment, ecotoxicology faces an astounding challenge in identifying toxicants. The combination of high-throughput in vivo/in vitro bioassays with high-resolution chemical analysis is an effective way to elucidate the cause-effect relationship. However, these combined strategies imply an enormous workload that can hinder their implementation in routine analysis. The purpose of this study was to develop a new high throughput screening method that could be used as a predictive expert system that automatically quantifies the size increase and malformation of the larvae and, thus, eases the application of the sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis. For this task, a training set of 242 images was used to calibrate the size-increase and malformation level of the larvae. Two classification models based on partial least squares discriminant analysis (PLS-DA) were built and compared. Moreover, Hierarchical PLS-DA shows a high proficiency in classifying the larvae, achieving a prediction accuracy of 84 % in validation. The scripts built along the work were compiled in a user-friendly standalone app (SETApp) freely accessible at https://github.com/UPV-EHU-IBeA/SETApp. The SETApp was tested in a real case scenario to fulfill the tedious requirements of a WWTP effect-directed analysis.

Monitoring Stimulated Darkening from UV-C Light on Different Bean Genotypes by NMR Spectroscopy

The use of UV-C cool white light on bean (Phaseolus vulgaris L.) seeds significantly increases the biochemical seed coat post-harvest darkening process, whilst preserving seed germination. The aim of this work consists in monitoring the effect caused by the incidence of UV-C light on different bean genotypes using NMR spectroscopy. The genotype samples named IAC Alvorada; TAA Dama; BRS Estilo and BRS Pérola from the Agronomic Institute (IAC; Campinas; SP; Brazil) were evaluated. The following two methodologies were used: a prolonged darkening, in which the grain is placed in a room at a controlled temperature (298 K) and humidity for 90 days, simulating the supermarket shelf; an accelerated darkening, where the grains are exposed to UV-C light (254 nm) for 96 h. The experiments were performed using the following innovative time-domain (TD) NMR approaches: the RK-ROSE pulse sequence; one- and two-dimensional high resolution (HR) NMR experiments (¹H; ¹H-¹H COSY and ¹H-¹³C HSQC); chemometrics tools, such as PLS-DA and heat plots. The results suggest that the observed darkening occurs on the tegument after prolonged (90 days) and accelerated (96 h) conditions. In addition, the results indicate that phenylalanine is the relevant metabolite within this context, being able to participate in the chemical reactions accounted for by the darkening processes. Additionally, it is possible to confirm that a UV-C lamp accelerates oxidative enzymatic reactions and that the NMR methods used were a trustworthy approach to monitor and understand the darkening in bean seeds at metabolite level.