肉品品质检测技术综述

介绍了人工嗅觉与人工味觉检测技术、计算机视觉技术、近红外光谱技术、高光谱图像检测技术等无损检测技术的发展概况.应用高光谱图像技术对肉品品质进行无损检测是当前的研究热点之一.介绍了该技术的基本原理和国内外肉品品质高光谱图像检测技术的研究现状,并展望了高光谱图像检测技术在肉品品质检测中的研究前景,以期对我国相关研究人员的研...     

生鲜肉品质安全无损伤检测技术研究进展

生鲜肉品质安全无损检测技术是肉品品质检测的关键技术,日益受到肉制品生产加工企业的重视。本文介绍了国内外肉品无损检测技术的研究情况,包括用于肉品外部品质检测的机器视觉和图像处理技术、用于肉品内外部多品质同时检测的光谱技术、用于胴体检测分级的超声波技术和X射线技术等。研究表明,以上技术可以对胴体和肉品的品质参数进行快速无损检测,但这些研究大部分停留在实验系统的开发阶段,没有大规模用于工业生产。文中指出,为满足工业生产无损检测的要求,需要将多种检测技术、检测手段进行融合和集成,利用多种信息对肉品品质安全进行无损检测,开发出用于工业生产的在线无损检测系统。     

肉类品质无损检测技术研究现状与发展趋势

介绍了近年来国内外肉类品质无损检测技术,主要包括近红外光谱技术、计算机视觉技术和电子鼻技术,可实现对肉品水分、蛋白质、脂肪、pH、新鲜度、剪切力等多个指标的检测。但单一技术无法实现肉品品质的综合评价,多源感知信息融合技术和高光谱图像技术将多种信息融合,可以更好地反映肉品的综合性状,在肉品内外部品质检测方面具有独特的优势,是肉品品质检测的发展趋势。     

光谱技术在生鲜肉品质安全快速检测的研究进展

光谱技术作为无损快速检测技术在肉品行业中得到广泛应用.该技术能实现生鲜肉快速、在线、准确、无损检测,是各类生鲜肉品质安全分析的重要技术之一.文章综述了近红外光谱、拉曼光谱、高光谱成像技术、荧光光谱等光谱技术在生鲜肉品质检测和安全评定上的重要应用和研究进展.主要包括水分、蛋白质及脂肪等影响肉类营养品质的组成成分分析,肉品食用品质如嫩度、大理石花纹、肉色及新鲜度等指标的评价,肉品加工品质如保水性并由此实行肉类分级的检测以及生鲜肉在微生物污染等安全品质的评定.同时分析各种光谱技术的现状提出存在的问题,并针对目前发展趋势展望了该技术的前景:光谱技术通过与机器视觉技术等新型无损检测技术的有机融合,将实现在线检测评价生鲜肉品质安全的目标.     

农畜产品品质安全光学无损检测技术的进展和趋势

本文综述了国内外农畜产品品质安全无损检测技术的研究状况和发展趋势。在农畜产品检测领域, 发现近红外光谱技术、高光谱成像技术、激光拉曼光谱法和X射线荧光光谱法等主要的光学无损检测技术和方法有广泛的研究和应用状况, 它们在果蔬的品质成分分析、农药残留检测与在线分级分拣; 生鲜肉肉品品质检测、品种鉴别与安全评定; 乳品、茶叶等特种农产品的成分分析、品种分类等方面具有重要作用。农畜产品无损检测技术具有广阔的发展前景和应用潜力。     

肉品质量无损检测技术研究进展

肉类和肉类食品品质与安全检测一直是肉类行业中关注的热点。本文综述了超声波、电磁特性、电子鼻与电子舌、计算机视觉、光谱分析等几种当前主要无损检测技术在肉品质量评价中的研究进展。其中,重点介绍了光谱分析中具有图谱合一、可同时获取样品内外部品质信息特性的高光谱成像技术及其在国内外肉品品质检测中的应用现状,提出了该技术在肉类品质检测研究方向的几点思考,并展望了无损检测技术在肉品品质检测中的研究前景,以期为后续研究提供参考。     

近红外光谱技术在肉类品质评价中的应用

我国作为肉品消耗大国, 肉类品质一直是政府和百姓关注的热点问题。传统肉品检测方法不仅所用试剂会对环境造成污染, 而且检测周期也很难满足当今快速增长的肉品消耗需求。近红外光谱作为一个快速、无损、无污染、效率高、低成本、响应速度快、选择性强、抗干扰能力强和多组分同时分析(即一个近红外光谱数据可获得样品多种物质信息)的检测技术已逐渐被广泛用于肉品检测领域。本文综述了近红外光谱技术在肉品种类判别、产地溯源和品质分类定性鉴别中的研究, 以及在肉品颜色、pH值、持水力和常规化学组成定量分析中的研究, 并对近红外光谱在肉品检测领域的发展前景进行展望, 以期为更好评价肉类品质提供参考。     

高光谱成像技术在红肉食用品质检测中的应用研究进展

高光谱成像技术是一种集光谱技术与计算机视觉技术为一体的无损检测技术,该项技术能快速、全面、无损地获取肉品的内外部信息,在红肉食用品质的检测中具有广泛应用。本文在简述高光谱成像原理的基础上,详述近年来高光谱成像技术在红肉制品食用品质方面的应用,并对该项技术存在的问题及应用前景进行概述,以期为红肉无损检测的研究提供参考。     

拉曼光谱技术在肉品加工与品质控制中的研究进展

拉曼光谱技术作为新型的光谱检测技术,在分析肉及肉制品结构和理化性质方面具有方便简单、快速无损、高效等优点,已迅速成为肉品研究领域中重要的检测技术之一。本文简述了拉曼光谱技术的原理,综述了拉曼光谱技术在肉品加工中的应用,其中包括肉品加工品质、食用品质以及安全品质等分析方面;进而阐述拉曼光谱技术与化学计量学相结合方式在肉品科学研究和工业生产中的优势,并对拉曼光谱技术在今后肉品领域中的发展进行总结和展望。     

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。     

肉品品质的无损检测方法(英文)

At present, some foreign researchers of meat industry developed countries are studying and applying nondestructive testing techniques to detect meat quality.In our country, these techniques are seldom used besides some techniques using electromagnetic properties.This paper introduces some modern nondestructive testing techniques for quality detection of meat, such as Supersonic wave, electronic Nose, electromagnetic method, near infrared, Raman Spectroscopy and computer vision technology.These techniques can meet the requirements of high speed and high accuracy on line detection of meat.Besides, further research and possible applications are also discussed.     

Advances in Nondestructive Methods for Meat Quality and Safety Monitoring

ABSTRACT

Meat is highly perishable and poses health threats when its quality and safety is unmonitored. Chemical methods of quality and safety determination are expensive, time-consuming and lack real-time monitoring applicability. Nondestructive techniques have been reported as antidotes to these constraints. This paper assessed the potential of nondestructive techniques such as near-infrared spectroscopy, hyperspectral imaging, multispectral imaging, e-nose, and their data fusion, all combined with algorithms for quality monitoring of pork, beef, and chicken, the most consumed meat sources in the world. These techniques combined with data processing applications may offer a panacea for real-time industrial meat quality and safety monitoring.     

Emerging nondestructive approaches for meat quality and safety evaluation—A review

Meat is one of the most consumed agro-products because it contains proteins, minerals, and essential vitamins, all of which play critical roles in the human diet and health. Meat is a perishable food product because of its high moisture content, and as such there are concerns about its quality, stability, and safety. There are two widely used methods for monitoring meat quality attributes: subjective sensory evaluation and chemical/instrumentation tests. However, these methods are labor-intensive, time-consuming, and destructive. To overcome the shortfalls of these conventional approaches, several researchers have developed fast and nondestructive techniques. Recently, electronic nose (e-nose), computer vision (CV), spectroscopy, hyperspectral imaging (HSI), and multispectral imaging (MSI) technologies have been explored as nondestructive methods in meat quality and safety evaluation. However, most of the studies on the application of these novel technologies are still in the preliminary stages and are carried out in isolation, often without comprehensive information on the most suitable approach. This lack of cohesive information on the strength and shortcomings of each technique could impact their application and commercialization for the detection of important meat attributes such as pH, marbling, or microbial spoilage. Here, we provide a comprehensive review of recent nondestructive technologies (e-nose, CV, spectroscopy, HSI, and MSI), as well as their applications and limitations in the detection and evaluation of meat quality and safety issues, such as contamination, adulteration, and quality classification. A discussion is also included on the challenges and future outlooks of the respective technologies and their various applications.     

P(y)-a parameter for meat quality

The P_y is a parameter which assesses the integrity of the cell membranes. It is a direct indicator for the volume fraction of cells surrounded by insulating cell membranes. The P_y has been shown to correlate well with meat quality parameters like the drip loss or pH. It is a useful parameter for the discrimination between normal suited meat and PSE meat. The measurement is instantaneous and nondestructive. Due to aging of meat, P_y depends on the time post mortem. It shows the highest significance between 4 and 24 h p.m.     

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。     

A Photon Migration Method for Characterizing Fiber Formation in Meat Analogs

ABSTRACT:  Meat analogs produced by high-moisture extrusion of soy proteins are good alternatives to animal meat and have many health benefits. In addition to textural properties, an abundant fibrous structure in such extrudates is a key factor for consumer acceptance. Although several techniques have been developed for quantifying fiber formation in extrudates, their applications for real-time quality control in manufacturing process have been challenging. In this study, we developed a nondestructive imaging technique to quantify fibrous structures in soy protein extrudates. The spatial distribution of light reflectance on sample surface was imaged and a fiber formation index was derived based on the random-walk theory of light transport in anisotropic media. This method has a potential to be used as a nondestructive, real-time quality control tool for products with fibrous structures.     

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.     

Recent Applications of Spectroscopic and Hyperspectral Imaging Techniques with Chemometric Analysis for Rapid Inspection of Microbial Spoilage in Muscle Foods

Muscle food is one of the most perishable food products because of its vulnerability to microbial spoilage, which can result in critical food safety problems. Traditional techniques for detection and evaluation of microbial spoilage in muscle foods are tedious, laborious, destructive, and time‐consuming. In recent years, spectroscopic and imaging technologies have shown great potentials for the assessment of food quality and safety due to their nondestructive, noninvasive, cost‐effective, and rapid responsive nature. This review focuses on the applications of several valuable spectroscopic techniques including visible and near‐infrared spectroscopy, Fourier transform infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy, and hyperspectral imaging for the rapid and nondestructive detection of microbial spoilage in common muscle foods such as meat, poultry, fish, and related products. Combined with chemometric analysis, such as spectral preprocessing and modeling methods, these potential technologies have been successfully developed for the determination of total viable count, aerobic plate count, Enterobacteriaceae, Pseudomonas, Escherichia coli, and lactic acid bacteria loads in muscle foods. Moreover, the advantages and disadvantages of these techniques are discussed and some perspectives about future trends are also presented.     

肉品品质变化的蒙特卡罗方法仿真

目的采用蒙特卡罗方法仿真研究检测间距对检测深度的影响以及光子在不同肉品组织中的迁移规律。方法使用Windows界面的蒙特卡罗仿真软件对肉品的不同品质、不同检测间距的光子迁移分布进行仿真。结果随着检测器与光源之间间距的增加,检测深度逐渐增加;对于不同新鲜度的样品,散射系数在0.4~1.5 mm~(-1)范围内,随着散射系数的增大,光子在组织中的迁移路径长度逐渐减小,检测器可以捕获更多的光子包。结论对不同检测间距下检测深度的蒙特卡罗仿真实验结果与实际测定结果基本相同,因此蒙特卡罗仿真可以为光学在肉品无损检测方案的研究提供有效理论支撑。