己内酰胺（CPL）是食品包装材料中常见的添加剂，可以改善包装机械性能，在实际生产中比较常用。国内外对其添加量无限量标准，但规定了在食品中的迁移限量为15 mg/kg。过量的CPL会迁移至食品中，甚至超出迁移限量，从而危害人体健康。因此，对食品及包装材料中CPL的分析检测至关重要。近红外（NIR）和中红外（MIR）光谱技术是可用于食品及食品包装分析检测的无损检测方法，具有分析速度快、无需前处理、结果重现性好、对环境友好等优势。为探讨CPL对生物基食品包装膜性能的影响及其在食品模拟物中的迁移情况，并建立一种快速无损分析食品包装膜及酱类食品中CPL含量的新方法，在国家重点研发计划“食品新型包装材料及智能包装关键装备研发”（2018YFD0400703）项目的支持下，本文制备了一系列含不同浓度CPL的可得然薄膜，研究了CPL含量对膜机械性能、阻隔性能等性能的影响，建立了CPL在4种食品模拟物中的迁移模型，基于NIR和MIR光谱技术及三种数据融合策略分别构建了可得然薄膜和酱类食品（番茄酱、沙拉酱和蓝莓果酱）中CPL的定量分析模型。本文具体研究内容及结果如下：

锚点锚点锚点锚点锚点锚点1. 己内酰胺含量与可得然薄膜包装性能关系研究

锚点锚点锚点锚点锚点锚点制备了一系列含不同浓度CPL的可得然食品包装薄膜，测试了空白膜与含不同浓度CPL薄膜的包装性能参数，同时，表征并分析了薄膜表面和横截面的微观结构。结果发现，适量的CPL通过改善薄膜的微观结构和提高膜结构的致密程度来提高薄膜的抗拉强度和断裂延伸率，降低其透明度、吸水率和水蒸气透过率，但CPL的加入也会降低膜的玻璃化转变温度（Tg）、熔融温度（Tm）和熔融过程的吸热焓（ΔH），而对结晶温度（Tc）无明显影响。这意味着，适量CPL可以改善包装材料的机械性能，提高防光性能，增强阻隔性能，同时也会使薄膜的耐热性变差。因此，根据不同含量CPL的可得然薄膜的一系列性能参数以及微观结构的变化，结合实际生产成本、包装安全性等因素，提出了CPL在食品包装材料中的最佳添加量为5%。

锚点锚点锚点锚点锚点锚点2. 己内酰胺在食品模拟物中的的迁移规律及迁移模型研究

锚点锚点锚点锚点锚点锚点通过迁移试验，研究了在25 ℃、40 ℃和60 ℃条件下，初始浓度分别为1%、2%、3%和5%的CPL在4种食品模拟物中的迁移规律及影响因素，利用迁移数据建立了CPL在4种食品模拟物中关于C∞、τ和β三个参数的Weibull迁移模型并进行了模型外部验证。结果发现，温度越高，CPL初始迁移速率越快，同一时刻下的迁移量越高，达到迁移平衡状态所需时间越短；在迁移初期，迁移量随时间的延长而逐渐增加，到达迁移平衡时，迁移量不再随时间变化，保持在最大迁移量水平左右。初始浓度越高，最大迁移量也越高。CPL在4种食品模拟物中的迁移量由高到低依次为：4%乙酸、蒸馏水、50%乙醇、正己烷。Weibull迁移模型具有较好的预测准确性，可应用于生物基薄膜在酱类食品中的迁移预测。

3. 基于红外光谱对可得然薄膜中己内酰胺含量的检测研究

基于NIR、MIR和NIR-MIR融合光谱技术和化学计量学方法建立了9种光谱预处理方法下的可得然薄膜中CPL含量的PLS和SVM预测模型，通过比较模型评价参数，分别确定了基于NIR、MIR和NIR-MIR融合光谱对膜中CPL定量分析的最优模型。其中，NIR最优SNV-SVM模型Rp2为0.9552，RMSEP为1.251%，RPD值为4.50； MIR最优1st-SVM模型Rp2为0.9092，RMSEP为1.614%，RPD值为3.38。融合模型中低层次和高层次融合模型的预测效果要优于单一的NIR和MIR模型，而中层次融合模型的预测效果稍差，高层次融合模型的预测效果最好，Rp2为0.9606，RMSEP为1.211%，RPD值为4.52。据此，本章提供了一种基于NIR-MIR光谱高层次融合技术检测可得然薄膜中CPL含量的新方法，具有分析速度快、不破坏样品、绿色环保、低成本等优势。

4. 基于红外光谱对酱类食品中己内酰胺含量的检测研究

基于NIR、MIR和NIR-MIR融合光谱结合9种光谱预处理方法和化学计量学方法分别建立了番茄酱、沙拉酱和蓝莓果酱中CPL的定量分析模型，通过比较模型评价参数，确定了酱类食品中CPL定量分析的最优模型。结果发现，对番茄酱、沙拉酱和蓝莓果酱而言，高层次融合模型的预测效果均要优于低层次融合模型、中层次融合模型以及单一的NIR模型和MIR模型的预测效果。番茄酱、沙拉酱和蓝莓果酱的高层次融合模型Rp2分别为0.9990、0.9929和0.9989；RMSEP分别为1.079 mg/kg、2.930 mg/kg和1.151 mg/kg；RPD值分别为32.12、11.78和30.17，模型预测效果均很好。

为进一步验证NIR-MIR高层次融合模型检测多种酱类食品的适用性，将番茄酱、沙拉酱和蓝莓果酱的NIR和MIR光谱整合到一起，建立了基于3种酱基质中CPL含量的高层次融合预测模型，其Rp2为0.9961，RMSEP为2.151 mg/kg，RPD值可以达到15.91。结果表明，NIR和MIR光谱技术结合高层次数据融合方法可以提供一种酱类食品中有机危害物的无损快速定量分析新手段，具有结果准确、重现性好、对环境友好等优点。

Caprolactam (CPL) is a common additive in food packaging materials, which can improve the mechanical properties of packaging, and is commonly used in actual production. The standard of adding quantity of CPL is unlimited at home and abroad, but the migration limit in food is 15 mg/kg. Excessive CPL will migrate to food, even exceed the migration limit, thus endangering human health. Therefore, it is very important to analyze and detect CPL in food and packaging. Near infrared (NIR) and mid infrared (MIR) spectroscopy technology is a non-destructive detection method which can be used in the analysis and detection of food and food packaging. It has the advantages of fast analysis speed, no pretreatment, good reproducibility of results, and environmental friendliness. In order to investigate the effect of CPL on the performance of bio-based food packaging film and its migration in food simulants, a new method for rapid and non-destructive analysis of CPL content in food packaging film and sauces was established. Supported by the project of "research and development of new food packaging materials and key equipment for intelligent packaging" (2018YFd0400703) of the national key R&D plan, a series of curdlan-based films containing different concentrations of CPL were prepared, and the effects of CPL content on the mechanical properties and barrier properties of the films were studied. The migration models of CPL in food simulants were established. Quantitative analysis models of CPL in curdlan-based film and sauces (ketchup, salad dressing and blueberry jam) were established based on NIR and MIR spectroscopy technology and three data fusion strategies. The research contents and results were as follows:

1. The relationship between the CPL content and the packaging properties of curdlan-based film

A series of curdlan-based food packaging films with different CPL content were prepared. The packaging performances of the films were tested, and the micro-structure of the surface and cross-section of the film was analyzed. The results show that an appropriate amount of CPL improves the tensile strength and elongation at break of the film and reduces its transparency, water absorption and water vapor permeability by improving the micro-structure and the density of the film structure of the films. However, the addition of CPL will also reduce the glass transition temperature (Tg), melting temperature (Tm) and endothermic enthalpy (ΔH) of the melting process, but has no obvious effect on the crystallization temperature (Tc). This means that an appropriate amount of CPL can improve the mechanical properties of packaging materials, improve light-proof performance, enhance barrier properties, and at the same time make the heat resistance of the film worse. Therefore, according to a series of performance parameters and micro-structure changes of curdlan-based films with different CPL content, combined with the actual production cost, packaging safety and other factors, the optimal addition amount of CPL in food packaging materials was proposed as 5%.

2. Migration law and migration model of CPL in food simulants

The migration law and influencing factors of CPL with initial concentrations of 1%, 2%, 3% and 5% in food simulants at 25 ℃, 40 ℃ and 60 ℃ were studied by migration test. The Weibull migration model of CPL in food simulants with C∞, τ and β was established by using migration data, and the external validation of the model was carried out. The results show that the higher the temperature, the faster the initial migration rate, the higher the amount of migration at the same time, and the shorter the time to reach the equilibrium state of migration; in a certain range of time, the amount of migration gradually increases with the extension of time, and when it reaches the equilibrium state of migration, the amount of migration no longer changes with time, and basically remains at the level of the maximum amount of migration; The higher the initial concentration, the higher the maximum migration; the migration of CPL in the four food simulants from high to low is: 4% acetic acid, distilled water, 50% ethanol, n-hexane. Weibull migration model predicted accurately and can be applied to predict the migration of bio-based packaging film contacted with sauses.

3. Determination of CPL content in curdlan-based film based on infrared spectroscopy

The PLS and SVM prediction models of the CPL content in curdlan films under 9 spectral pretreatment methods were established based on NIR, MIR, and NIR-MIR fusion spectroscopy technology and chemometric methods. By comparing the evaluation parameters of the models, the optimal quantitative analysis model of CPL content in films was determined. The results show that the optimal model of NIR-SNV-SVM has Rp2 of 0.9552, RMSEP of 1.251% and RPD of 4.50; the optimal model of MIR-1st-SVM has Rp2 of 0.9092, RMSEP of 1.614% and RPD of 3.38. This shows that the prediction effect of low-level and high-level fusion model is better than that of single NIR and MIR model, while the prediction effect of mid-level fusion model is slightly worse. The high-level fusion model has the best prediction effect among them with Rp2 of 0.9606, RMSEP of 1.211% and RPD of 4.52. Therefore, this study provided a new method based on NIR-MIR spectral high-level fusion technology to detect the CPL content in curdlan films, which has the advantages of fast analysis speed, no damage to samples, green environmental protection and low cost.

4. Determination of CPL in sauces based on infrared spectroscopy

Based on NIR, MIR and NIR-MIR fusion spectroscopy, combined with nine spectral pretreatment methods and chemometric methods, the quantitative analysis models of CPL in ketchup, salad dressing and blueberry jam were established respectively. By comparing the evaluation parameters of the models, the optimal quantitative analysis model of CPL in sauces was determined. The results show that for ketchup, salad dressing and blueberry jam, the prediction effect of high-level fusion model is better than that of low-level fusion model, mid-level fusion model, single NIR model and MIR model. The Rp2 of high-level fusion model for ketchup, salad dressing and blueberry jam were 0.9990, 0.9929 and 0.9989, respectively; RMSEP were 1.079 mg/kg, 2.930 mg/kg and 1.151 mg/kg, respectively; RPD were 32.12, 11.78 and 30.17, respectively. The models all have good prediction ability for CPL content.

In order to further verify the applicability of NIR-MIR high-level fusion model in detecting a variety of sauces, NIR and Mir spectra of ketchup, salad dressing and blueberry jam were integrated to establish a high-level fusion prediction model based on CPL content in three sauce substrates, with Rp2 of 0.9961, RMSEP of 2.151 mg/kg and RPD of 15.91. The results show that NIR and MIR spectroscopy combined with high-level data fusion method can provide a new method for non-destructive and rapid quantitative analysis of organic hazards in sauces, which has the advantages of accurate results, good reproducibility and environmental friendliness.

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