This review summarizes the application of machine learning in research on the numbing substances of Zanthoxylum bungeanum. Different varieties of Z. bungeanum on the market vary in the composition and content of numbing substances. Traditional methods for the detection and analysis of the composition and content of numbing substances in Z. bungeanum have many limitations, so the introduction of machine learning algorithms has brought new possibilities to this field. Applying machine learning for predictive modeling of the quality of Z. bungeanum and modeling of its drying process, the sensory evaluation of Z. bungeanum, and establishing a germplasm bank for Z. bungeanum is of great significance for the genetic breeding of Z. bungeanum. This article systematically reviews the composition and content of numbing substances in different varieties of Z. bungeanum, and analyzes the application of machine learning algorithms in predictive quality modeling and drying modeling of Z. bungeanum and data analysis of its numbing substances. Integration with machine learning technology enables a deeper understanding of the currently established models, which will provide support for the optimization of the yield and quality of Z. bungeanum based on numbing substances.

Recently, food grade nanofiber-based materials have received growing attentions in food packaging. In this work, novel active and intelligent packaging nanofibers based on gelatin/ chitosan with curcumin (GA/CS/CUR) were developed via electrospinning technique. Effects of the incorporation of CUR content (0.1%－0.3%, m/m) on the microstructure and functional properties of the electrospun nanofibers were investigated. Morphological studies using scanning electron microscopy indicated that loading CUR can affect the average diameter of nanofiber mats, which remained around 160-180 nm. The addition of an appropriate level CUR (0.2%, m/m) led to a stronger intermolecular interaction, and thus enhanced the thermal stability and tensile strength of the obtained nanofibers. Meanwhile, the incorporation of CUR significantly improved antioxidant activity and the antimicrobial activity of GA/CS/CUR nanofibers. Moreover, the sensitivity of nanofibers to ammonia results indicated that GA/CS nanofibers containing 0.2% CUR (GA/CS/CUR Ⅱ) presented high sensitivity of colorimetric behavior to ammonia (within 3 min). These results suggest GA/CS/CUR Ⅱ nanofibers has great potential as a multifunctional packaging to protect and monitor the freshness of protein-rich animal foods, such as meat and seafood.

Development of functional bioinspired hydrogels that have good releases control character is necessary for the application of these materials in biomedical engineering. Herein, we report a composite hydrogel prepared from several biocompatible carboxymethyl konjac glucomannan (CKGM)/gelatin (G)/tannic acid (TA) functional nano-hydroxyapatite (TA@n-HA), which has good biodegradability and pH sensitivity. The mechanism of interaction between hydrogels was confirmed by Fourier transform infrared spectroscopy, X-ray diffraction, Scanning electron microscopy and Thermogravimetric analysis. The physico-chemical properties of CKGM/G hydrogels have been significantly improved through the incorporation of TA@n-HA within the matrix. Studies in the sustained release of epigallocatechin gallate (EGCG) demonstrated that the TA@n-HA/CKGM/G hydrogels exhibit not only better pH sensitive properties, but also enhanced biocompatibility and encapsulation in comparison to the matrix devoid of TA@n-HA. Consequently, TA@n-HA/CKGM/G hydrogels using EGCG as a drug release model show the potential for drug delivery.