A review on colorimetric indicators for monitoring product freshness in intelligent food packaging: Indicator dyes,preparation methods,and applications

Intelligent food packaging system exhibits enhanced communication function by providing dynamic product information to various stakeholders (e.g., consumers, retailers, distributors) in the supply chain. One example of intelligent packaging involves the use of colorimetric indicators, which when subjected to external stimuli (e.g., moisture, gas/vapor, electromagnetic radiation, temperature), display discernable color changes that can be correlated with real-time changes in product quality. This type of interactive packaging system allows continuous monitoring of product freshness during transportation, distribution, storage, and marketing phases. This review summarizes the colorimetric indicator technologies for intelligent packaging systems, emphasizing on the types of indicator dyes, preparation methods, applications in different food products, and future considerations. Both food and nonfood indicator materials integrated into various carriers (e.g., paper-based substrates, polymer films, electrospun fibers, and nanoparticles) with material properties optimized for specific applications are discussed, targeting perishable products, such as fresh meat and fishery products. Colorimetric indicators can supplement the traditional “Best Before” date label by providing real-time product quality information to the consumers and retailers, thereby not only ensuring product safety, but also promising in reducing food waste. Successful scale-up of these intelligent packaging technologies to the industrial level must consider issues related to regulatory approval, consumer acceptance, cost-effectiveness, and product compatibility.     

Fruits and Vegetables Freshness Categorization Using Deep Learning

The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using hand-held cameras. The recognition and categorization of fruits and vegetables are performed through two deep learning models: Visual Geometry Group (VGG-16) and You Only Look Once (YOLO), and their results are compared. VGG-16 classifies fruits and vegetables and categorizes their freshness, while YOLO also localizes them within the image. Furthermore, we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree. A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness dataset. The dataset is publicly available for further evaluation by the research community.     

冷链物流中远程食品新鲜度检测的电子鼻系统设计

为了有效监测冷链物流各环节中食品新鲜度,设计了远程电子鼻系统。以与猪肉新鲜度关联的特定气体为检测目标,使用单片机技术针对性地设计了检测气室和气体传感阵列,实现了冷库内的猪肉信息的采集、处理,使用主成分分析方法进行猪肉新鲜度检测,并通过GPRS将检测结果传输到远程控制中心。测试结果表明,该系统检测准确度高、丢包率小,满足应用需求。     

考虑数据新鲜度和交叉熵的电动汽车短期充电负荷预测模型

研究了公交车充电站短期负荷预测方法,提出了一种基于数据新鲜度和交叉熵的组合预测模型。首先,对公交车充电站的负荷特性进行分析,发现日充电负荷具有波动大、周期性、与气象条件(温度、降雨等)密切相关的特点。其次,对组合预测模型在累积历史预测误差的过程中作了如下改进:1考虑充电负荷样本数据的时间特征和波动性特征,给出了基于灰色关联度的相似日选取方法;2考虑单一模型在预测过程中的精度和稳定度,基于交叉熵和正态分布概率密度函数建立组合预测模型,动态地调整权重系数;3充分考虑数据源的时间有效性,提出新鲜度函数的概念,改善了单一预测方法的概率密度分布函数,进而优化组合预测的权重系数,进一步提高组合模型预测精度。基于北京市某公交车充电站的历史充电数据构建训练样本和测试样本,通过与单一预测模型和其他组合模型的预测结果进行比较,证明了所提组合预测模型的有效性。     

食品安全与鲜度的检测与监控（下）

简述影响食品安全与鲜度的主要因素及其检测技术。诸如农药残留;抗生素、生长激素、抗寄生虫药物;有害元素（Hg、Pb、Cd、As、Sn、Cu、Cr、Al、Ni、F）以及制假掺假与有毒食品加工等。另一部分为水产品、果蔬食品的鲜度检测方法。     

Effect of lightly salt and sucrose on rigor mortis changes in silver carp (Hypophthalmichthys molitrix) stored at 4°C

To evaluate the effect of salt and sucrose on rigor mortis changes in silver carp during 72 h at 4 °C, physical (texture parameters, water holding capacity (WHC), cooking loss, L* value) and chemical adenosine triphosphate (ATP‐related compounds, K value, pH value) characteristics were studied. Silver carp were subjected to following treatments: left untreated (CK), treated with 1.8% salt (S) and 1.8% salt incorporating 1.8% sucrose (S+S). Curing treatments predominantly increased IMP content, WHC and texture parameters, retarded cooking loss and discoloration compared with untreated samples. The highest IMP concentration measured in S and S+S all occurred at 4 h, which was prior to that of CK (48 h). K value of S+S did not follow a linear relationship with time. The results indicated that the best eating times of CK, S and S+S were 2, 4 and 4 h at 4 °C, respectively, and curing treatments improved the quality of silver carp during postmortem process.     

Rapid and non‐invasive evaluation of pork meat quality during storage via impedance measurement

In this study, the evolutions of impedance and bio‐indicators (total aerobic count (TAC), total volatile base nitrogen (TVB‐N) and pH) of meat freshness during storage at 4 °C were investigated and compared. The influence of electrode configurations, frequencies and directions of applied electric fields on impedance measurement was considered. Good relationships between measured impedance and bio‐indicators were obtained, with R² ranging from 0.758 to 0.992, RMSE from 0.11 to 0.57 for TAC and R² ranging from 0.636 to 0.989, RMSE from 0.29 to 1.68 for TVB‐N. Bar and ring electrodes had better performance as compared to needle electrodes. Effects of frequency on impedance were important from 20 Hz to 200 kHz and diminished in the higher ranges. Impedance generally exhibited better correlations with TAC, TVB‐N at high frequency than at low frequency. The findings demonstrated that impedance measurement could be a viable, rapid method to assess the quality of stored pork meat.     

茶多酚对冷却猪肉保鲜效果的应用研究

研究了质量分数分别为0%、0.25%、0.75%、1.25%、1.75%和2.25%的茶多酚对贮藏在4℃下冷却猪肉的保鲜效果。在贮藏的过程中,分别定期对冷却猪肉的菌落总数、色泽及持水力、pH、TBA、TVB-N等理化指标进行检测。结果表明,茶多酚处理能抑制冷却肉中微生物的增长速度,明显抑制冷却肉中脂质的氧化,延缓TVB-N的增加,使冷却肉在较长时期内保持良好的食用品质,延长其货架期。     

鱼类贮藏期间鲜度指标K值变化及鲜度评价

目的 研究鱼类肌肉在不同贮藏条件下的鲜度指标K值及鲜度变化情况。方法 鱼类肌肉在不同条件下贮藏, 肌肉中的ATP关联物用高氯酸溶液提取后用高效液相色谱进行检测, 通过公式计算出K值。结果 K值与鱼类的新鲜度变化趋势有较好的规律性, 随着贮藏时间延长K值增大, 温度越低变化越缓慢。在28~30 ℃条件下只能贮藏数小时, 4~5 ℃条件下可延长至5 d, ?2~0 ℃条件下贮藏大于15 d。结论 K值客观地反映了鱼类贮藏过程中的鲜度变化情况, 适合于作为鲜度的判定指标。     

基于阳极氧化铝比色阵列传感器对鱼肉新鲜度的测定

为了快速、准确地对鱼肉新鲜度进行无损实时监测,本研究以阳极氧化铝片为基材,选取13种指示剂作为气敏材料,构建了一种可视化比色阵列传感器。利用所构建的比色阵列传感器对贮藏过程中大菱鲆鱼肉新鲜度进行测定。结果表明,在25 ℃条件下,当贮藏时间超过22 h时,鱼肉的总挥发性盐基氮（TVB-N）含量达到32.85 mg/100 g,鱼肉发生腐败变质,此时的比色阵列传感器中的阵列点发生颜色变化。提取阵列点在响应前后的红、绿、蓝（Red、Green、Blue,RGB）值并进行差减,对其进行聚类分析和主成分分析。结果表明,该传感阵列能够准确区分不同贮藏时间段的鱼肉新鲜度。此外,将该阵列传感器应用于不同贮藏时间下鲤鱼和美国红鱼新鲜度的检测,结果表明通过传感阵列预测的TVB-N值与实际测量值之间没有显著性差异。因此,将该传感器应用于鱼肉新鲜度监测具有可行性。