This review systematically examines the transformative potential of machine learning across the entire food packaging industry chain, including material design and selection, structural optimization, sensory-preference analysis, smart packaging, automated packaging machinery, microplastic detection, and waste recycling.
Tiantong Lan, Xiyuan Ma, Hao Zhang et al.· Food Research International· 0 citations
The reconstituted soybean protein isolate (SPI) was constructed by adjusting the ratios of its main components, namely lipophilic protein (LP), glycinin (11S), and β-conglycinin (7S). The effects of different LP/11S/7S ratios on stability and delivery function of transglutaminase-induced emulsion gel were investigated. The reconstituted SPI with a high proportion of LP had lower particle size, higher surface charge and excellent interface affinity, which helped to strengthen microstructure of emulsion gel. The reconstituted SPI emulsion gels exhibited higher viscoelasticity and water holding capacity, and the freeze-thaw, thermal and pH stability were enhanced. Furthermore, reconstituted SPI emulsion gels increased encapsulation efficiency of quercetin to 92.2%, which facilitated its chemical stability and promoted bioaccessibility to 61.78%. Therefore, reconstituted SPI emulsion gel can be improved by regulating ratios of LP, 7S and 11S, thus promoting quercetin delivery, which provides a theoretical basis for construction and application of stable SPI-based emulsion gel carriers.
Jiannan Yan, Fangxiao Xing, Pan Liu et al.· Food Chemistry· 0 citations
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