Double-layer indicator films aided by BP-ANN-enabled freshness detection on packaged meat products
Introduction
Along with an increasing demand for safety, consumers are also placing more emphasis on various quality aspects of packaged foods. Food packaging are therefore nowadays, in addition to providing protection and facilitating transportation, expected to be capable of providing information on quality changes of packaged foods (Yang et al., 2021a, Guo et al., 2020a, Wang et al., 2012). Much research has indeed been conducted on the development and applications of intelligent packaging that can provide information on food freshness (Wang et al., 2021, Fan et al., 2019, Farhan and Hani, 2017, Choi et al., 2017). In the case of meat products, spoilage is accompanied by decomposition of proteins, which results in turn in the production of volatile organic amines, including trimethylamine, as well as an increase in the pH of the products (Chen et al., 2020, Meng et al., 2012, Zhang et al., 2008). pH-sensitive materials have therefore been applied as intelligent packaging to indicate freshness of packaged meat products; freshness can be monitored via such colorimetric indicators as bromocresol blue, methyl red and polyaniline (Zhang et al., 2021b, Chen et al., 2019, Yang et al., 2021b). However, these chemicals are expensive and possess potential health hazard when being used in food packaging.
Among many pH-sensitive materials, anthocyanins are one of the most commonly used. Since anthocyanins can be easily extracted from an array of plant materials, the pigments are available at a relatively low cost (Zhang et al., 2021b, Mohammadalinejhad et al., 2020, Cortez et al., 2017, Ezati and Rhim, 2020, Chen et al., 2020, Wang et al., 2019, Roy and Rhim, 2020). Anthocyanins are nevertheless unstable and can be easily degraded by heat, light, oxygen and the presence of metal ions. To protect anthocyanins from these deteriorating factors, the pigments should be encapsulated in an appropriate matrix. Such matrix should also possess appropriate mechanical and barrier properties as it must also play the role of being food packaging as well.
Among the factors affecting mechanical properties of food packaging films, type of material and its film forming capability are of importance. Compared with single film-forming materials, composite materials are well recognized to be capable of improving mechanical properties of the resulting films. An array of biopolymers, which exhibit such advantages as biodegradability, non-toxicity and biocompatibility, can be used in combination to form films. Layer-by-Layer is a method that can be actively controlled to prepare composite coatings, which can give full play to the advantages of each combination of materials to adjust the performance of the coating, with complementary materials, structure and performance controllable. Low-acyl gellan gum is, for example, an anionic polysaccharide, which is formed by repeated polymerization of basic units composing of three monosaccharides (glucuronic acid, rhamnose and glucose). The gum is widely used as an emulsifier in beverages and as a wall material for encapsulation purposes (Xie et al., 2021, Guo et al., 2020b, Xu et al., 2019, Zhang et al., 2019a, An et al., 2006). Chitosan is, on the other hand, a cationic polysaccharide with good film-forming capability as well as oxygen barrier property (Bof et al., 2015, Talón et al., 2017). Studies have then shown that the interactions between chitosan and gellan gum could help improve mechanical and oxygen barrier properties of the resulting films (Amin, Panhuis 2011; Zhang et al., 2021a). With these superior properties, the film system is expected be capable of protecting anthocyanins that would be incorporated into its matrix as well.
Several studies have reported the development of anthocyanins/gellan based films for food freshness detection (Wu et al., 2021, Yang et al., 2021b; Xu et al., 2021; Zhai et al. 2018; Wei, Cheng, Ho, Tsai, & Mi, 2017), once a pH-sensitive smart packaging system has been developed, a means to correlate color changes to freshness of packaged foods must be established. Back propagation artificial neural network (BP-ANN), which is commonly used to establish an artificial intelligence-based prediction model, can be used for such a purpose. BP-ANN can recognize pattern and build predictive model from experimental data only after a limited number of iterations (Sun, Chi, Xu, & Wang, 2020). The algorithm also exhibits a strong capability of non-linear processing, self-learning, self-adaptation, structure adjustment, fault-tolerance and noise avoidance; it is therefore suitable for a complex non-linear problem of the present study.
In the present study, raspberry anthocyanins were used as a pH-sensitive color indicator. The indicator was first incorporated into low-acyl gellan to improve the stability of the former. Indicator-incorporated gellan was used to form an inner layer, while chitosan was used to form an outer layer of a double-layer indicator film; the final film system was prepared via layer-by-layer assembly. pH-dependent color change of anthocyanins was first investigated. Mechanical properties, moisture content and water vapor permeability as well as color stability of the film system were then determined. FTIR spectroscopy was conducted to identify if chemical interactions occurred within the composite film structure. In order to explore the applicability of the developed double-layer indicator film, pork patties and fish balls were selected as test meat products; the film system was used to pack and monitor spoilage of pork patties and fish balls during refrigerated storage. BP-ANN model was established using color parameters of the double-layer indicator films (which reflected change in the quality of the meat products) as the input and total volatile nitrogen (TVB-N) content as the output.
Section snippets
Raw materials
Raspberries were obtained from Qingdao Shanghao Food Co., Ltd. (Qingdao, China) and used to extract anthocyanins. Pork patties (protein content of 14-18 g/100 g, fat content of 10-15 g/100 g, moisture content of 20-30 g/100 g) were obtained from Yangzhou Yechun Food Co., Ltd. (Yangzhou, China). Chitosan (degree of deacetylation of 80%) and low-acyl gellan were purchased from Sinopac Group Co., Ltd. (Shanghai, China).
Extraction and characterization of anthocyanins
Raspberries were freeze dried at a pressure of 80±5 Pa, cold trap temperature
Color change of indicator
Color of raspberry anthocyanins changed from red to blue-violet and then yellow when the pH increased from 6 to 11 (Fig. 1). When the pH was lower than 7, the color was pink and the maximum absorption peak was observed at around 520 nm. At pH 7, the maximum absorption peak shifted from 520 nm to 580 nm; the absorbance at the maximum absorption wavelength (580 nm) decreased. As pH increased from 8 to 11, the color changed from blue-purple to yellow; the maximum absorption peak also shifted from
Conclusion
Color of raspberry anthocyanins changed from red to blue-violet and then yellow when the pH increased from 6 to 11. Compared with the single-layer film, thickness, tensile strength, elongation and residual moisture content of the double-layer film were significantly higher. Due to its lower hydrophilicity, the outer chitosan layer helped alleviate poor water barrier property of the inner film. Double-layer film also exhibited higher opacity. The presence of the outer chitosan layer was
CRediT authorship contribution statement
The experiment was performed by Yanan Sun. Oversight of the project and field experience were provided by Min Zhang, Benu Adhikari, Haixiang Wang and Sakamon Devahastin. Critical review of the manuscript was performed by Min Zhang, Benu Adhikari and Sakamon Devahastin.
Acknowledgments
This work was financially supported by National Key R&D Program of China (Contract No. 2017YFD0400501), National First-class Discipline Program of Food Science and Technology (No. JUFSTR20180205), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX20_1835) and Jiangsu Province Key Laboratory Project of Advanced Food Manufacturing Equipment and Technology (No. FMZ202003).
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