Qingqing Li,Zhiyi Wu,Longdong Qin,Liang Zhang,Linpin Luo,Guangjun Huang,Jianlong Wang
Food spoilage caused by microbial proliferation and moisture loss remains a critical challenge in postharvest management. This study proposes a smart hydrogel system integrating photothermal-responsive Pickering emulsions and thermo-sensitive biopolymers to achieve on-demand antimicrobial release and water retention. The Pickering emulsion, stabilized by indocyanine green (ICG)-loaded halloysite nanotubes (HNTs), serves as an antimicrobial depot of cinnamaldehyde (Cin). Under near-infrared (NIR) irradiation, ICG converts light energy into heat, triggering both thermal-enhanced Cin volatilization and sol-gel transition of the κ-carrageenan/gelatin (CG) hydrogel matrix. This dual-action mechanism enables: (i) Spatiotemporal control: NIR exposure achieves precise Cin release, with cumulative release increasing to 21.5 %; (ii) Dual-mode antibacterial efficacy: The system exhibits a 3.12 cm inhibition zone against S. aureus and complete suppression of Penicillium expansum growth through combined contact and vapor-phase antimicrobial activity. (iii) Superior preservation performance: Grapes packaged with the hydrogel maintain 98.92 % initial weight after 14 days, with retained firmness, stable pH, and minimal soluble solids loss. By synergizing photothermal conversion, thermal-responsive hydrogel dynamics, and natural antimicrobials, this work establishes a non-contact preservation platform that extends grape shelf life by 250 %, demonstrating significant potential for intelligent food packaging applications.
This study focused on analyzing the aroma formation mechanism of retronasal muscat flavor in table grapes. The sensory characteristics and fragrance components of table grape juice with different intensities of Muscat were investigated using GC-Quadrupole-MS, quantitative descriptive analysis and three-alternate forced choice. Free monoterpenoids were the main contributors to the retronasal Muscat flavor. The contribution of Muscat compounds to this flavor was quantified by Stevens coefficient, the most and the least sensitive compounds to concentration changes were citronellol and linalool, respectively. To predict the Muscat flavor intensity by mathematical modeling, established a model between Muscat flavor intensity and monoterpenoids concentration, and an optimal partial least squares regression model with a linear relationship between natural logarithms was obtained. These findings provide reference for understanding the formation mechanism of specific aromas in fruits and provide a basis for the development and quality control of processed products such as Muscat flavor grape juice.
危险品化学品经营许可证（带存储）