Development of a green and low-cost method to determine mercury content in sediments affected by oil spill on the Brazilian coast.

Tons of crude oil were found on the Brazilian coast in 2019, and studies assessing its chemical composition are still scarce. This study aimed to develop a new and simple technique of cold vapor generation using infrared irradiation coupled with atomic absorption spectrometry to determine mercury content in sediments contaminated by crude oil. Experimental conditions were evaluated, including formic acid concentration, reactor temperature, and carrier gas flow rate. The accuracy of the method was validated by comparison with mercury contents in a certified reference material (PACS-2). The detection limit was found to be 0.44 µg kg-1. The developed method was applied to determine the total mercury content in marine sediment samples collected from beaches in Ceará State. Mercury concentrations ranged from 0.41 to 0.95 mg kg-1. The proposed method is efficient, simple, low-cost, and adequate for its purpose.

Metabolomic approaches to explore chemodiversity in seeds of guaraná (Paullinia cupana) using UPLC-QTOF-MSE and NMR analysis.

The growing interest in health and well-being has spurred the evolution of functional foods, which provide enhanced health benefits beyond basic nutrition. Guaraná seeds (Paullinia cupana) have been widely studied and used as a functional food due to their richness in caffeine, phenolic compounds, amino acids, and other nutrients. This has established guaraná as a significant food supplement, with Brazil being the largest producer of the world. This study aims to propose a set of analytical methods to chemically evaluate fifty-six different guaraná clones, from the Guaraná Germplasm Active Bank, to accommodate the diverse requirements of the food industry. Metabolomic approaches were employed, in which a non-target metabolomic analysis via UPLC-QTOF-MSE led to the annotation of nineteen specialized metabolites. Furthermore, targeted metabolomics was also used, leading to the identification and quantification of metabolites by NMR. The extensive data generated were subjected to multivariate analysis, elucidating the similarities and differences between the evaluated guaraná seeds, particularly concerning the varying concentration levels of the metabolites. The metabolomics approach based on the combination of UPLC-QTOF-MSE, NMR and chemometric tools provided sensitivity, precision and accuracy to establish the chemical profiles of guaraná seeds. In conclusion, evaluating and determining the metabolic specificities of different guarana clones allow for their application in the development of products with different levels of specific metabolites, such as caffeine. This caters to various purposes within the food industry. Moreover, the recognized pharmacological properties of the annotated specialized metabolites affirm the use of guarana clones as an excellent nutritional source.

Assessment of metabolic, mineral, and cytotoxic profile in pineapple leaves of different commercial varieties: A new eco-friendly and inexpensive source of bioactive compounds.

Pineapple is among the most produced and consumed fruits worldwide, and consequently, its agroindustrial production/processing generates high amounts of agricultural waste, which are routinely discarded. Thus, it is crucial to seek alternatives to reuse this agricultural waste that are in high availability. Therefore, this work aims to evaluate the chemical composition of a specific residue (leaves) of seven commercial varieties of pineapples, to attribute high added value uses, and to evaluate its potential as a source of secondary metabolites and minerals. Thereby, twenty-eight metabolites were annotated by UPLC-QTOF-MSE, including amino acids, organic acids, and phenolic compounds. The following minerals were quantitatively assessed by ICP-OES: Zn (5.30-19.77 mg kg-1), Cr, Cd, Mn (50.80-113.98 mg kg-1), Cu (1.05-4.01 mg kg-1), P (1030.77-6163.63 mg kg-1) and Fe (9.06-70.17 mg kg-1). In addition, Cr and Cd (toxic materials) present concentration levels below the limit of quantification of the analytical method (LOQCr and LOQCd = 0.02 mg kg-1) for all samples. The multivariate analysis was conceived from the chemical profile, through the tools of PCA (principal component analysis) and HCA (hierarchical cluster analysis). The results show that pineapple leaves have similarities and differences concerning their chemical composition. In addition, the cytotoxicity assays of the extracts against tumor and non-tumor strains shows that the extracts were non-toxic. This fact can corroborate and enhance the prospection of new uses and applications of agroindustrial co-products from pineapple, enabling the evaluation and use in different types of industries, such as pharmacological, cosmetic, and food, in addition to the possibility of being a potential source of bioactive compounds.

One-class classification of special agroforestry Brazilian coffee using NIR spectrometry and chemometric tools.

The near-infrared spectrometry combined with the one-class classification method was applied as quality control of the agroforestry-grown specialty coffee. A total of 34 samples were analyzed in this study. Spectral data were obtained using a NIR portable and different pre-treatment strategies for baseline correction were evaluated. Unsupervised pattern recognition (PCA and HCA) techniques were performed. The construction of the classification model was carried out using the dd-SIMCA algorithm with 19 samples acquired directly from producers that are recognized for the best quality control of the specialty type coffee. In order to test the model, 15 samples of non-specialty type, obtained in local markets, were evaluated. The classification model with the highest correct classification rate (CCR) scored 100% and 87% in the validation and test groups, respectively. The results demonstrated that the application of this strategy was successful in verifying the authenticity of specialty type agroforestry-grown coffee samples.