Enhancing phytochemical parameters in broccoli through vacuum impregnation and their prediction with comparative ANN and RSM models

被引:2
|
作者
Wahid, Aseeya [1 ]
Giri, Saroj Kumar [1 ]
Kate, Adinath [1 ]
Tripathi, Manoj Kumar [1 ]
Kumar, Manoj [1 ]
机构
[1] ICAR Cent Inst Agr Engn, Bhopal 462038, India
来源
SCIENTIFIC REPORTS | 2023年 / 13卷 / 01期
关键词
RESPONSE-SURFACE METHODOLOGY; ANTIOXIDANT CAPACITY; OSMOTIC DEHYDRATION; ASCORBIC-ACID; QUALITY; EXTRACTION; OPTIMIZATION; FRUIT; ENHANCEMENT; KINETICS;
D O I
10.1038/s41598-023-41930-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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-2 value as compared to RSM models. Instrumental characterization (FTIR, XRD and SEM analysis) of untreated and treated samples were done to see the effect of impregnation on microstructural and morphological changes in broccoli. The results showed enhancement in the TPC, TFC, AAC, TCC, FRSA, and CC values of broccoli florets with impregnation. The FTIR and XRD analysis also supported the results.
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页数:14
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