苹果品质高光谱成像检测技术研究进展

高光谱成像对水果的无损检测是近些年迅速发展的一项新技术,它能三维地获取被检测对象内部与外部多项特征。本文通过介绍高光谱成像系统结构、光源种类及扫描形式,归纳适用于检测苹果品质的系统类型,通过描述指标检测操作流程解析其中几个重要环节,并对国内外苹果指标检测的操作流程、建模方法、研究进展进行总结,最后提出苹果品质高光谱无损检测的研究方向和应用前景。      

高光谱成像技术在谷物品质检测中的应用进展

高光谱成像(Hyperspectral imaging,HSI)技术作为一种无损和快速的光学成像分析技术在谷物品质的无损检测应用广泛。本文简述了高光谱成像的基本原理、光谱信息数据处理方法,综述了HSI技术在小麦、玉米、稻谷3种大宗谷物中化学成分检测、品种鉴别、种子活力检测以及不完善籽粒检测等近五年的应用研究进展,提出HSI技术在谷物品质检测实际应用中需破解的难题。     

基于高光谱成像技术的红肉品质评定研究进展

红肉品质的传统检测方法会对样品造成污染,影响其理化指标的测定结果,在检测某些标量指标的同时还会具有一定的破坏性。因此,准确、无损、快速的检测评价对推动肉制品企业的发展具有十分重要的意义。近些年,高光谱成像技术在肉品品质检测和评价中的应用已成为研究热点,该技术已被广泛应用于食品安全与农产品质量检测中,并且取得了较好的研究成果。本文主要综述了近年来高光谱成像技术在红肉品质检测中的应用研究,分别从肉类品质评定的感官指标、内在指标2 个方面进行阐述。最后,对高光谱成像技术现存的一些不足和其在肉制品检测中的发展前景进行概述。     

高光谱成像在鱼肉品质无损检测中的研究进展

高光谱成像（hyperspectral imaging,HSI）技术作为一种无损、快速、准确的绿色分析技术在水产品品质检测方面得到了广泛应用。集图像与光谱技术优势于一体,HSI技术可同时检测实验样品的物理和几何特征（颜色、大小、形状和质地等）,还可以提供内部组成成分的化学和分子信息（水分、脂肪、蛋白及其他氢键物质）。本文主要综述了HSI技术在鱼肉品质快速检测方面的最新研究进展,主要涉及到鱼肉的化学组成、物理属性、微生物污染以及新鲜度等四大方面。同时对HSI技术在鱼肉检测中的应用研究进行了展望,以期开发适用于不同检测要求的在线HSI设备。     

高光谱成像技术在果蔬品质安全无损检测中的应用

近年来,人们对果蔬品质关注度提高。随着成像技术和光谱技术的快速发展,高光谱成像技术广泛应用于各种果蔬产品的快速和非破坏性检测中。高光谱成像技术具有"图谱合一"的优点,可同时检测果蔬的内部、外部品质信息。本文介绍了高光谱成像技术的基本原理,综述了高光谱成像技术在果蔬内外部品质检测方面的应用进展,并简要分析了高光谱成像技术在果蔬品质检测中的发展趋势和面临的挑战,以期对我国相关研究人员的研究工作提供参考。     

高光谱成像技术在食品品质无损检测中的应用探究

本文综述了高光谱成像技术和高光谱成像系统的原理,从食品新鲜度检测、生物污染检测、水分检测和固形物含量检测4个方面分析高光谱成像技术的应用,了解其检测要点与优势,以期提高高光谱成像技术的应用水平,更好地保证食品的品质和安全。     

高光谱成像技术在食品品质无损检测中的应用

高光谱成像技术结合光谱技术和图像技术的优势,能够很好的捕获光谱信息和图像信息。其丰富的光谱信息能够有效的提取样品内部特征。该分析技术已广泛应用于检测食品的水分含量、新鲜度、生物污染等。本文介绍并分析了高光谱成像技术在食品检测中的各种应用,指出了目前高光谱成像技术存在的不足之处,指明了该技术领域工作者今后的重点研究方向,并对高光谱成像技术发展前景进行了分析和展望。      

高光谱成像技术在农产品无损检测中的应用

高光谱成像技术具有“图谱合一”的特点,其汇集了传统成像和光谱技术的特点,能同时获得待测农产品样本的图像信息和光谱信息,因此该技术既可以通过成像技术检测物体的外部特征,又可以通过光谱技术得到农产品的内部品质和食用安全性信息,包括品种分类、理化指标测定、真菌感染检测和农药残留检测等。与传统检测方法相比,高光谱成像以其检测过程中前处理简单、无污染、无破坏性的特点,在农产品无损检测领域有所应用。从高光谱成像的理论基础出发,对其图像获取与分析方式进行概述,并阐述了高光谱成像技术在农产品无损检测领域中近五年的研究进展,以期为农产品的品种分类、营养品质和食用安全性评估方法提供参考。     

高光谱成像技术在肉品品质评价中的应用

高光谱成像技术具有图像技术和光谱学的优点,能同时获得食品物料的空间信息和光谱信息,进而达到快 速、无损、精准检测的效果。本文阐述了高光谱成像的基本原理,分析了高光谱图数据处理的方法;总结了高光谱 成像技术在肉品品质评价与检验方面的研究进展,并按肉品的检测指标进行了分类综述,以期为开展肉品品质评价 的研究提供借鉴。     

基于高光谱成像技术的水果品质无损检测

高光谱图像技术结合光谱技术与计算机图像技术两者的优点,可获得大量包含连续波长光谱信息的图像块,其图像信息可检测水果的外部品质,光谱信息则可用于水果内部品质的检测,达到根据水果内、外部综合品质进行分类的目的. 综述了国内外将该技术应用于水果品质检测方面的研究进展,提出了利用高光谱图像技术检测苹果轻微损伤的方法,利用500～900nm的高光谱图像数据,通过主成分分析提取547nm波长下的特征图像.     

A Review of Hyperspectral Imaging for Chicken Meat Safety and Quality Evaluation: Application,Hardware, and Software

Food quality and safety issues have received widespread attention around the world. Traditional analytical methods are cumbersome, time consuming, and disruptive. Consumers and businesses are in desperate need of a fast, nondestructive test to evaluate the safety and quality of food. Chicken is an important food source for the human diet and has a high consumption rate. Its quality and safety issues are especially important. The hyperspectral imaging (HSI) technique combines the main characteristics of the spectroscopy technique and the imaging technique to achieve fast, nondestructive testing and demonstrates great potential for evaluating the food safety and quality of chicken. For the past few years, there have been many studies on the HSI technique for the detection and evaluation of chicken meat safety and quality. Therefore, the purpose of this article is to provide a detailed overview of the HSI technique for microbiological safety detection and quality attribute assessments of chicken meat. In addition, the hardware and software used in the HSI systems are also summarized and compared. Finally, some opinions on the focus of future research and its applications in the modern poultry industry are presented.     

基于近红外高光谱成像快速无损检测注胶肉研究

采用近红外高光谱成像技术结合化学计量学方法建立注胶肉的快速无损检测模型。首先通过近红外高光谱成像系统获取含有不同浓度梯度卡拉胶的猪里脊肉高光谱图像,然后提取图像中的光谱数据,使用偏最小二乘法(Partial least square,PLS)探究光谱信息与不同掺假比例卡拉胶之间的定量关系。结果表明全波段光谱(900~1700 nm)所构建的PLS校正集模型均方根误差(Root mean square error,RMSE)为1.74%,预测模型RMSE为3.16%。表明基于全波段所建立的PLS模型具有较优的预测性能。利用连续投影算法(Successive projection algorithm,SPA)筛选获得11个特征波长,并优化全波长PLS模型,将预测集样品带入,以验证模型的预测效果,结果表明SPA算法结合PLS建模方法所建立的模型预测效果更优,预测集相关系数(R_P)为0.93,均方根误差(Root mean square error of prediction,RMSEP)为3.51%,预测偏差(Residual predictive deviation,RPD)为2.66。试验表明利用高光谱成像技术可实现对注胶猪肉的快速无损检测。     

Regression Algorithms in Hyperspectral Data Analysis for Meat Quality Detection and Evaluation

Hyperspectral imaging (HSI) system in tandem with chemometric methods is proposed as a rapid, efficient, cost‐saving, and nondestructive detection technique, and multivariate data analysis is an indispensable part of this novel detection technique. In recent years, the rapid progress that we have made in using all kinds of chemometric methods to deal with hyperspectral data of meat products, however, cannot meet the practical needs very well. Thus, in order to give some suggestions on how to select an appropriate algorithm for hyperspectral data analysis, this review, first, briefly introduces the principle of the most widely used regression algorithms, and, more importantly, then focuses on the application of different algorithms in modeling the correlation between the quality attributes of the tested sample and their hyperspectral data. The advantages and limitations of these algorithms are compared and discussed. This review article will provide valuable guidelines for data analysis in the future progress of HSI detection technique.     

高光谱成像技术在肉类安全无损检测的应用研究进展

高光谱成像技术在肉类安全品质预测及分选分级方面已取得了诸多成果。作者重点综述了其在肉类有毒有害物质检测、肉类掺假检测、肉类分选分级中的研究现状,讨论了其存在的不足及发展趋势,以期为肉类安全无损检测方法的研究提供参考。     

Applications of Hyperspectral Imaging in Chicken Meat Safety and Quality Detection and Evaluation: A Review

Currently, the issue of food safety and quality is a great public concern. In order to satisfy the demands of consumers and obtain superior food qualities, non-destructive and fast methods are required for quality evaluation. As one of these methods, hyperspectral imaging (HSI) technique has emerged as a smart and promising analytical tool for quality evaluation purposes and has attracted much interest in non-destructive analysis of different food products. With the main advantage of combining both spectroscopy technique and imaging technique, HSI technique shows a convinced attitude to detect and evaluate chicken meat quality objectively. Moreover, developing a quality evaluation system based on HSI technology would bring economic benefits to the chicken meat industry. Therefore, in recent years, many studies have been conducted on using HSI technology for the safety and quality detection and evaluation of chicken meat. The aim of this review is thus to give a detailed overview about HSI and focus on the recently developed methods exerted in HSI technology developed for microbiological spoilage detection and quality classification of chicken meat. Moreover, the usefulness of HSI technique for detecting fecal contamination and bone fragments of chicken carcasses are presented. Finally, some viewpoints on its future research and applicability in the modern poultry industry are proposed.     

高光谱成像技术检测肴肉新鲜度

建立阿胶中马和驴成分高特异、高灵敏的实时荧光聚合酶链式反应（polymerase chain reaction,PCR）检 测方法。选择马和驴线粒体基因tRNA-Thr及D-loop区为靶序列,设计合成特异引物,通过普通PCR和实时荧光PCR 检测,结果表明,这两对引物能够准确检测阿胶或动物胶中马和驴成分。