ArticleScientific reports2023
Enhancing phytochemical parameters in broccoli through vacuum impregnation and their prediction with comparative ANN and RSM models.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 8 citations in OpenAlex.
- Anti-Helicobacter pylori activity of nanocomposites from chitosan/broccoli mucilage/selenium nanoparticles.Scientific reports · 2024Article
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5 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Amidst increasing demand for nutritious foods, the quest for effective methods to enhance health-promoting attributes has intensified. Vacuum impregnation (VI) is a promising technique to augment produce properties while minimizing impacts on biochemical attributes. In light of broccoli's growing popularity driven by its nutritional benefits, this study explores the impact of VI using ascorbic acid and calcium chloride as impregnation agents on enhancing its phytochemical properties. Response surface methodology (RSM) was used for optimization of the vacuum impregnation process with Vacuum pressure (0.6, 0.4, 0.2 bar), vacuum time (3, 7, 11 min), restoration time (5, 10, 15 min), and concentrations (0.5, 1.0, 1.5%) as independent parameters. The influence of these process parameters on six targeted responses viz. total phenolic content (TPC), total flavonoid content (TFC), ascorbic acid content (AAC), total chlorophyll content (TCC), free radical scavenging activity (FRSA), and carotenoid content (CC) were analysed. Levenberg-Marquardt back propagated neural network (LMB-ANN) was used to model the impregnation process. Multiple response optimization of the vacuum impregnation process indicated an optimum condition of 0.2 bar vacuum pressure, 11 min of vacuum time, 12 min of restoration time, and 1.5% concentration of solution for vacuum impregnation of broccoli. The values of TPC, TFC, AAC, TCC, FRSA, and CC obtained at optimized conditions were 291.20 mg GAE/100 g, 11.29 mg QE/100 g, 350.81 mg/100 g, 1.21 mg/100 g, 79.77 mg, and 8.51 mg, respectively. The prediction models obtained through ANN was found suitable for predicting the responses with less standard errors and higher R
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