基于轻量级卷积神经网络的荧光指示标签用于冷鲜猪肉新鲜度判别

Freshness Discrimination of Chilled Pork with Fluorescent Indicator Labels Based on Lightweight Convolutional Neural Network

荧光新鲜度标签的颜色指示是实时监测肉制品品质的重要手段。以冷鲜猪肉为研究对象,提出一种由异硫氰酸荧光素(fluorescein isothiocyanate,FITC)、罗丹明B(rhodamine B,RhB)2种荧光素组成的比率型荧光新鲜度指示标签,其中发绿色荧光的FITC为反应信号,发红色荧光的RhB为参考信号。结果表明:当标签与腐败胺反应时,表现出双发射特性,FITC荧光增强,RhB荧光不受干扰,标签呈现红粉色到黄绿色的明显过渡,显著提高了标签的灵敏性和精确性;其次,利用卷积神经网络对荧光新鲜度标签的色泽变化进行智能化判别,以减少人为视觉误差,对比3种轻量级(MobileNetv2、EfficientNetb0、ShuffleNetv2)和2种非轻量级卷积神经网络(ResNet50、VGG16)的判别效果,其中轻量级神经网络EfficientNetb0的效果优于其他4种模型,识别准确率高达95.6%,且参数量和运算量仅为4.01 MB和0.398 GMACs,实现了最佳运算速度和精度的平衡。因此,利用该模型可满足快速、准确、无损判别冷鲜猪肉新鲜度的需求。研究结果可为荧光指示标签应用于冷链物流贮运过程中智能化判别冷鲜猪肉新鲜度提供理论参考。

Color indications of fluorescent labels for freshness provide an important tool for monitoring meat quality in real time.This study developed a fluorescent label based on a zein film modified with rhodamine B(RhB) and fluorescein isothiocyanate(FITC).In the label,green fluorescence from FITC acted as a response signal,and red fluorescence from RhB as a reference signal.This fluorescent label exhibited dual emission responses when exposed to amines,FITC fluorescence increased whilst the fluorescence of RhB was undisturbed.The fluorescent label presented a clearly distinguishable color transition from pink to yellow-green,indicating significantly enhanced sensitivity and accuracy.Furthermore,convolutional neural network(CNN) was used to intelligently distinguish the color changes of the fluorescent label to reduce human visual errors.Lightweight CNN EfficientNetb0 was found to be superior to two other lightweight CNN(MobileNetv2and ShuffleNetv2) and two non-lightweight CNN(ResNet50 and VGG16) in terms of discriminant effectiveness,with a recognition accuracy of 95.6%.The parameters and floating-point operations per second(FLOPs) of the EfficientNetb0model were 4.01 MB and 0.398 GMACs,respectively,which achieved the best balance between FLOPs and accuracy.Therefore,this model can meet the need for the fast,accurate and nondestructive identification of chilled pork freshness.The research results provide a theoretical reference for the intelligent grading of the freshness of chilled pork using fluorescent indicator labels during cold storage and cold-chain transportation.