Chia (Salvia hispanica) seeds degradation studied by fuzzy-c mean (FCM) and hyperspectral imaging and chemometrics - fatty acids quantification

Chia seeds are nutritious food because they have a high content of protein, polyunsaturated fatty acids (omega-3 and omega-6) and phenolic compounds. During storage, fatty acids are degraded, by oxidative and hydrolytic reactions, forming free fatty acids (FFA). In this work, we used Near Infrared Hyperspectral Imaging (NIR- HSI) and chemometrics to predict FFA acid value and fatty acids concentrations in chia seeds during storage. First, we explore the hyperspectral images by Fuzzy c-means (FCM), where it is possible to observe as chemical compounds are formed or degraded during storage. Second, PLSR models were developed to predict FFA value and fatty acids concentration. RPD values reached values higher then 2.0, indicating a good ability to estimate these chemical compounds, especially polyunsaturated fatty acids omega-3 and omega-6. Finally, NIR-hyperspectral imaging coupled with chemometrics allowed us to show the chemical degradation process of chia seeds during storage, mainly associated with polyunsaturated fatty acids degradation. Besides NIR-HSI showed to be a powerful technique to quantify the main fatty acids with high accuracy

Chia (Salvia hispanica) seeds degradation studied by fuzzy-c mean (FCM) and hyperspectral imaging and chemometrics - fatty acids quantification

Chia seeds are nutritious food because they have a high content of protein, polyunsaturated fatty acids (omega-3 and omega-6) and phenolic compounds. During storage, fatty acids are degraded, by oxidative and hydrolytic reactions, forming free fatty acids (FFA). In this work, we used Near Infrared Hyperspectral Imaging (NIR- HSI) and chemometrics to predict FFA acid value and fatty acids concentrations in chia seeds during storage. First, we explore the hyperspectral images by Fuzzy c-means (FCM), where it is possible to observe as chemical compounds are formed or degraded during storage. Second, PLSR models were developed to predict FFA value and fatty acids concentration. RPD values reached values higher then 2.0, indicating a good ability to estimate these chemical compounds, especially polyunsaturated fatty acids omega-3 and omega-6. Finally, NIR-hyperspectral imaging coupled with chemometrics allowed us to show the chemical degradation process of chia seeds during storage, mainly associated with polyunsaturated fatty acids degradation. Besides NIR-HSI showed to be a powerful technique to quantify the main fatty acids with high accuracy

Novel brazilian hop (Humulus Lupulus L.) extracts through supercritical CO2 extraction: enhancing hop processing for greater sustainability

Hop cultivation has been increasing in the past decade in Brazil, demanding a better understanding of how the processing influences the national hop varieties. Despite the hop process being well-established in the producer countries, there is still room for optimization to reduce energy consumption for a more sustainable process. This studys main purpose was to understand the influence of drying and supercritical CO2 extraction on the quality of hop extracts. The hop quality during drying was evaluated regarding color, bitter acids, xanthohumol, total essential oil content, and volatile profile. Supercritical CO2 extraction yields, and bitter acid recovery were assessed by HPLC in a range of different temperatures (40 or 60°C) and pressure (15, 20, 25, or 30MPa) conditions. Hop processing was optimized to produce a greater extract quality from a Brazilian hop variety, saving energy and solvent consumption, and consequently, reducing the process footprint. Furthermore, this study established supercritical CO2 extraction conditions for Brazilian hop extract production, offering the national beer industry an alternative to overpriced products.Mariana Barreto Carvalhal Pinto and Flavio Luis Schmidt appreciate the support of the CNPq – Research Nacional Council - Brazil (Finance code 141485/2018-3). Grazielle Náthia Neves thanks CAPES - Coordination of Superior Level Staff Improvement - Brazil (Finance Code 001) for Ph.D. assistance. Renata Vardanega thanks European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement Nº 101062938 for a postdoctoral fellowship and Maria Angela Almeida Meireles thanks CNPq for a productivity grant (309825/2020-2). Pedro Renann Lopes de França acknowledges 2021/06606–4 scholarship funding from FAPESP.info:eu-repo/semantics/publishedVersio