Modelling and optimization of high-pressure homogenization of not-from-concentrate juice: Achieving better juice quality using sustainable production

被引:18
作者
Liu, Jianing [1 ,2 ]
Bi, Jinfeng [1 ]
Liu, Xuan [1 ]
Liu, Dazhi [1 ]
Verkerk, Ruud [2 ]
Dekker, Matthijs [2 ]
Lyu, Jian [1 ]
Wu, Xinye [1 ]
机构
[1] Chinese Acad Agr Sci CAAS, Inst Food Sci & Technol, Key Lab Agroprod Proc, Minist Agr & Rural Affairs, Beijing 100193, Peoples R China
[2] Wageningen Univ & Res, Food Qual & Design Grp, POB 17, NL-6700 AA Wageningen, Netherlands
关键词
High-pressure homogenization; Sustainable production; Not-from-concentrate (NFC) combined peach  and carrot juice; Comprehensive quality; Back propagation neural network; HIGH-HYDROSTATIC-PRESSURE; FREE AMINO-ACIDS; PECTIN METHYLESTERASE; ORANGE JUICE; FRUIT; STABILITY; BIOACCESSIBILITY; DEGRADATION; KINETICS;
D O I
10.1016/j.foodchem.2021.131058
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
The present work optimized high-pressure homogenization (HPH) parameters for not-from-concentrate combined peach and carrot juices, based on a two-step comprehensive model using factor analysis and analytic hierarchy process methods. Treating combined juice with pressures over 200 MPa retained more amounts of the bioactive compounds (carotenoids and polyphenols) than non-homogenization. Nutrition-oriented optimization, with higher judgement weight on nutritional properties, and sense-oriented optimization, with higher weight on sensory properties, were set up. Combined juice (250 MPa, 1 pass and 25 degrees C) had the best quality, based on the nutrition- and sense-oriented models. Back propagation neural network (BPNN) models could predict antioxidant capacities of the combined juice with greater accuracy compared with stepwise linear regression. The relative errors of BPNN prediction model were <= 5%.
引用
收藏
页数:11
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