Uptake and accumulation of Cr in edible parts of Eruca sativa from irrigation water. Effects on polyphenol profile and antioxidant capacity.

Metals in the environment have been an increasing research topic over the past decade, since they can be found in both natural and drinking water, including irrigation of crops and edible plants with contaminated water. The aim of this study was to investigate the uptake of Cr by arugula (Eruca sativa) in a greenhouse experiment, simulating the open field irrigation conditions. We also evaluate the toxic effects of Cr on oxidative stress by measuring the antioxidant capacity and polyphenol profile in the plant. The study examines the irrigation of arugula, during 15 and 21 days, with four Cr (VI) concentrations, ranging from 0 (control) to 250 µg. L-1. Arugula plants were able to accumulate Cr when irrigated during 15 and 21 days in all the Cr concentrations evaluated. The estimated daily intake (EDI) shows that the amount of Cr accumulated by arugula plants does not represent a threat to human health. Application of Cr levels induced some changes in content, profile and capacity of antioxidants depending on Cr concentration and time of exposure. Taking into account that E. sativa is consumed due to its polyphenol-related health benefits, the allowable Cr limits in irrigation water should be reviewed, in order to maximize health benefits associated with its consumption, and also to improve vegetable quality. Arugula is a valuable and nutritious food, that should not be excluded from a balanced diet. Chromium concentration in irrigation water as well as the speciation forms present in vegetables should be controlled.

Discovery of food identity markers by metabolomics and machine learning technology.

Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to screen food markers when coupled to efficient data analysis. This study explored feasibility of random forest (RF) machine learning, specifically its inherent feature extraction for non-targeted metabolic marker discovery. The distinction of chia, linseed, and sesame that have gained attention as "superfoods" served as test case. Chemical fractions of non-processed seeds and of wheat cookies with seed ingredients were profiled. RF technology classified original seeds unambiguously but appeared overdesigned for material with unique secondary metabolites, like sesamol or rosmarinic acid in the Lamiaceae, chia. Most unique metabolites were diluted or lost during cookie production but RF technology classified the presence of the seed ingredients in cookies with 6.7% overall error and revealed food processing markers, like 4-hydroxybenzaldehyde for chia and succinic acid monomethylester for linseed additions. RF based feature extraction was adequate for difficult classifications but marker selection should not be without human supervision. Combination with alternative data analysis technologies is advised and further testing of a wide range of seeds and food processing methods.

Data on polyphenols and biological activity analyses of an Andean tomato collection and their relationships with tomato traits and geographical origin.

Data provide information about a tomato collection composed of accessions from the Andean Valley, commercial accessions and wild species. Antioxidant metabolites were measured in mature fruits of this collection, and their biological activities were assessed by both in vitro and in vivo methods. In this work, the parameters used to identify and quantify polyphenols compounds in tomato fruit by liquid chromatography coupled to diode array detector and quadrupole time of flight mass spectrometer are described. Moreover, data supporting a procedure to characterize the properties of tomato fruits to revert death by thermal stress in Caenorhabditis elegans are explained in detail. Lastly, principal component analysis and hierarchical cluster analysis of metabolites composition, antioxidant activities (in vivo and in vitro), tomato traits and geographical origin of the tomatoes collection are shown. The data presented here are related to the research article entitled "Hydrophilic antioxidants from Andean Tomato Landraces assessed by their bioactivities in vitro and in vivo" [1].

Hydrophilic antioxidants from Andean tomato landraces assessed by their bioactivities in vitro and in vivo.

Potential nutraceutical properties of hydrophilic antioxidants in fruits of tomato landraces collected in Andean valleys were characterised. Antioxidant metabolites were measured by HPLC-DAD-MS/MS in mature fruits and their biological activities were assessed by in vitro and in vivo methods. In vitro antioxidant capacities were established by TEAC and FRAP methods. For in vivo biological activities we used a procedure based on Caenorhabditis elegans subjected to thermal stress. In addition, Saccharomyces cerevisiae was also used as a rapid screening system to evaluate tomato antioxidant capacity. All tomato accessions displayed significant differences regarding metabolic composition, biological activity and antioxidant capacity. Metabolite composition was associated with geographical origin and fruit size. Antioxidant activities showed significant association with phenolic compounds, such as caffeoylquinic acids, ferulic acid-O-hexosides and rutin. Combination of in vitro and in vivo methods applied here allowed evaluation of the variability in nutraceutical properties of tomato landraces, which could be applied to other fruits or food products.