Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review

Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria.     

Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity

This paper reviews the current state of development of both near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for process monitoring, quality control, and authenticity determination in cheese processing. Infrared spectroscopy has been identified as an ideal process analytical technology tool, and recent publications have demonstrated the potential of both NIR and MIR spectroscopy, coupled with chemometric techniques, for monitoring coagulation, syneresis, and ripening as well as determination of authenticity, composition, sensory, and rheological parameters. Recent research is reviewed and compared on the basis of experimental design, spectroscopic and chemometric methods employed to assess the potential of infrared spectroscopy as a technology for improving process control and quality in cheese manufacture. Emerging research areas for these technologies, such as cheese authenticity and food chain traceability, are also discussed.     

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。     

Nontargeted,Rapid Screening of Extra Virgin Olive Oil Products for Authenticity Using Near‐Infrared Spectroscopy in Combination with Conformity Index and Multivariate Statistical Analyses

A rapid tool for evaluating authenticity was developed and applied to the screening of extra virgin olive oil (EVOO) retail products by using Fourier‐transform near infrared (FT‐NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products and other test samples were rapidly measured in the transmission mode without any sample preparation. The univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool were used to analyze the various olive oil products which were tested for authenticity against a library of reference EVOO. Better discrimination between the authentic EVOO and some commercial EVOO products was observed with SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants. Due to its simplicity and speed, FT‐NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO.     

Meat quality evaluation by hyperspectral imaging technique: an overview

During the last two decades, a number of methods have been developed to objectively measure meat quality attributes. Hyperspectral imaging technique as one of these methods has been regarded as a smart and promising analytical tool for analyses conducted in research and industries. Recently there has been a renewed interest in using hyperspectral imaging in quality evaluation of different food products. The main inducement for developing the hyperspectral imaging system is to integrate both spectroscopy and imaging techniques in one system to make direct identification of different components and their spatial distribution in the tested product. By combining spatial and spectral details together, hyperspectral imaging has proved to be a promising technology for objective meat quality evaluation. The literature presented in this paper clearly reveals that hyperspectral imaging approaches have a huge potential for gaining rapid information about the chemical structure and related physical properties of all types of meat. In addition to its ability for effectively quantifying and characterizing quality attributes of some important visual features of meat such as color, quality grade, marbling, maturity, and texture, it is able to measure multiple chemical constituents simultaneously without monotonous sample preparation. Although this technology has not yet been sufficiently exploited in meat process and quality assessment, its potential is promising. Developing a quality evaluation system based on hyperspectral imaging technology to assess the meat quality parameters and to ensure its authentication would bring economical benefits to the meat industry by increasing consumer confidence in the quality of the meat products. This paper provides a detailed overview of the recently developed approaches and latest research efforts exerted in hyperspectral imaging technology developed for evaluating the quality of different meat products and the possibility of its widespread deployment.     

Advanced applications of chemo-responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Public attention to foodquality and safety has been increased significantly. Therefore, appropriate analytical tools are needed to analyze and sense the food quality and safety. Volatile organic compounds (VOCs) are important indicators for the quality and safety of food products. Odor imaging technology based on chemo-responsive dyes is one of the most promising methods for analysis of food products. This article reviews the sensing and imaging fundamentals of odor imaging technology based on chemo-responsive dyes. The aim is to give detailed outlines about the theory and principles of using odor imaging technology for VOCs detection, and to focus primarily on its applications in the field of quality and safety evaluation of food products, as well as its future applicability in modern food industries and research. The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods , poultry meat, aquatic products, fruits and vegetables, and tea. It has the potential for the rapid, reliable, and inline assessment of food safety and quality by providing odor-image-basedmonitoring tool. Practical Application : The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods, poultry meat, aquatic products, fruits and vegetables, and tea.     

近红外光谱仪特性及在牛肉制品检测中的应用

近红外光谱技术作为一种新型的分析检测技术,具有快速准确、无损的特点,在食品品质检测和生产监控中有着良好的应用前景。本文着重介绍近红外分析技术的原理、仪器和在牛肉及其制品中的应用并将其与相关同类仪器的性能特点进行对比,最后对近红外光谱技术进行展望。     

Detection of adulteration in milk: A review

Milk is a wholesome nutritious dairy product and is consumed by a majority of the population worldwide for drinking as such, as well as via dairy products. However, the practice of adulteration of milk invariably reduces its quality and may introduce hazardous substances into the dairy supply chain jeopardising consumers’ health. Various instances of adulteration of milk have been reported globally, wherein substances such as extraneous water, foreign proteins, whey proteins, melamine and urea, vegetable or animal fats, plus many minor constituents of milk fat have been added as potential adulterants in milk and milk products. This review focusses on the different methods of detection of these adulterants in milk using techniques such as DSC, RP‐HPLC, LC‐GC, HPTLC, immunoassays: CE, ELISA, FAMPST, FTIR, NIR spectroscopy, PAGE, IEF, DNA‐based methods and MALDI‐MS that have been developed and employed for the last 25 years. The combination of advanced IR spectroscopy and chemometrics provides a powerful tool for quality and authenticity analysis of milk. An electronic tongue is an easy and economic tool for the detection of caprine milk adulterations with bovine milk. Biosensors having the ability to furnish real‐time signals have been developed for the detection of urea in milk. An attempt has been made to give a clear understanding of the most suitable methods for the determination of various sources of adulteration.     

Near‐infrared spectroscopy and data analysis for predicting milk powder quality attributes

Near‐infrared (NIR) spectroscopy is a rapid analytical method for food products. In this study, NIR spectroscopy, data pretreatment techniques and multivariate data analysis were used to predict fine particle size fraction, dispersibility and bulk density of various milk powder samples, which are believed to have a significant impact on milk powder quality. Predictive models using partial least‐squares (PLS) regression were developed using NIR spectra and milk powder physical and functional properties, and it was concluded that the PLS models predicted milk powder quality with an accuracy of 88‐90 per cent.     

Challenges in Model Development for Meat Composition Using Multipoint NIR Spectroscopy from At‐Line to In‐Line Monitoring

This study evaluates the efficiency of multipoint near‐infrared spectroscopy (NIRS) to predict the fat and moisture content of minced beef samples both in at‐line and on‐line modes. Additionally, it aims at identifying the obstacles that can be encountered in the path of performing in‐line monitoring. Near‐infrared (NIR) reflectance spectra of minced beef samples were collected using an NIR spectrophotometer, employing a Fabry‐Perot interferometer. Partial least squares regression (PLSR) models based on reference values from proximate analysis yielded calibration coefficients of determination of 0.96 for both fat and moisture. For an independent batch of samples, fat was estimated with a prediction coefficient of determination of 0.87 and 0.82 for the samples in at‐line and on‐line modes, respectively. All the models were found to have good prediction accuracy; however, a higher bias was observed for predictions under on‐line mode. Overall results from this study illustrate that multipoint NIR systems combined with multivariate analysis has potential as a process analytical technology (PAT) tool for monitoring process parameters such as fat and moisture in the meat industry, providing real‐time spectral and spatial information.     

红外光谱技术在鱼产品质量检测与安全评估中的应用

近年来消费者对鱼产品的掺假问题愈发关注,从而针对鱼产品的质量评估的相关研究也逐渐增加。传统的鱼类成分分析和质量检测技术方法烦琐、费力、昂贵、费时,而光谱技术因其具有速度快、使用方便、样品制备最少或不需要样品制备,及避免样品破坏等优点而受到越来越多的关注。本文综述了以红外光谱技术为主的光谱技术,包括近红外光谱技术、中红外光谱技术等在鱼类及鱼产品的成分和其他质量特性监测中的应用,并对光谱技术的应用前景和发展方向进行了展望,以期为红外光谱技术在鱼类及鱼产品质量监测体系中推广应用提供指导,为解决鱼产品及相关行业的质量问题提供了一种新的途径。     

近红外光谱技术结合化学计量学用于畜禽肉制品品质分析的研究进展

肉类作为人体摄入蛋白质的主要来源,随着人们生活水平的提高和对营养健康的追求,肉制品的需求量不断增大,与此同时,肉制品新鲜度、掺杂掺假等肉制品品质领域的质量问题较为多发。为改善传统肉类检测方法耗时费力的现状,肉品质量的检测方法也逐渐趋于多样化。近红外光谱技术目前已广泛应用于包括生物、医药、食品在内的诸多领域。近红外光谱技术与化学计量法结合可对样品进行定性和定量分析,具有快速、无损、高效的优势,适用于肉品及肉制品现场实时监测。在前期研究的基础上,本文综述了近年来近红外光谱技术在畜禽肉制品新鲜度、品种鉴别与掺假分析、产地溯源等方面的研究进展,以期为肉制品品质分析及质量控制提供理论指导。     

分子吸收光谱技术在肉类研究中的应用

本文介绍了分子吸收光谱中近红外光谱和紫外-可见光谱技术的特点以及在评定肉类品质上的应用发现状,并展望其研究发展前景。     

Potential use of near infrared reflectance spectroscopy (NIRS) for the estimation of chemical composition of oxen meat samples

Near infrared reflectance spectroscopy (NIRS) was evaluated as a tool to estimate several chemical parameters of oxen meat protected by a quality mark. Fifty-three samples of longissimus thoracis muscle corresponding to oxen reared in extensive conditions were homogenized and scanned over the NIR spectral range (1100-2500nm). Immediately after scanning, the samples were analyzed for crude protein (CP), myoglobin, collagen, ether extract (EE), gross energy (GE), dry matter (DM) and ash content, according to the official methods. Best NIR calibrations for chemical composition tested by cross-validation showed R(2) and SE(CV) of 0.874 and 20.33gkg(-1) DM (CP), 0.924 and 16.22gkg(-1) DM (EE), 0.941 and 0.293MJkg(-1) DM (GE) and 0.874 and 6.75gkg(-1) FM (DM). Calibrations for myoglobin, collagen and ash content showed a poor predictability, probably as a consequence of the lack of correlation between these parameters and EE content. However, NIRS technology could be an useful tool for estimating the main chemical parameters of oxen meat samples, thus guaranteeing the standards of quality marks.     

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。     

Quality analysis,classification, and authentication of liquid foods by near-infrared spectroscopy: A review of recent research developments

Nowadays, near-infrared spectroscopy (NIR) has become one of the most efficient and advanced techniques for analysis of food products. Many relevant researches have been conducted in this regard. However, no reviews about the applications of NIR for liquid food analysis are reported. Therefore, this review summarizes the recent research developments of NIR technology in the field of liquid foods, focusing on the detection of quality attributes of various liquid foods, including alcoholic beverages (red wines, rice wines, and beer), nonalcoholic beverages (juice, fruit vinegars, coffee beverages, and cola beverages), dairy products (milk and yogurt), and oils (vegetable, camellia, peanut, and virgin olive oils and frying oil). In addition, the classification and authentication detection of adulteration are also covered. It is hoped that the current paper can serve as a reference source for the future liquid food analysis by NIR techniques.     

近红外光谱技术在果蔬农药残留检测中的应用研究进展

近红外光谱技术是一种具有无损、快速、低成本等诸多特点的新型分析检测技术,可以方便地实现对农产品尤其是水果、蔬菜中农药残留的定性和定量监控。近红外光谱技术所具有的无损检测这一突出优势,使其在农产品安全领域有着广阔的应用前景。本文概述了近红外光谱技术的基本原理、应用特点、目前近红外光谱技术常用的样品前处理技术-预浓缩技术和定量校正模型,并对近红外光谱技术在果蔬农药残留检测领域的应用情况进行综述。随着近红外光谱技术的不断革新、相关前处理技术的不断发展和完善,未来近红外光谱技术在果蔬农药残留检测中会向着更加灵敏、更加准确、更加自动化、更加现场化等方向发展。     

光谱无损检测技术在农产品产地溯源中的研究进展

实现农产品产地溯源的无损检测,是建立农产品质量安全追溯体系的重要途径,也是保障食品安全质量、维护消费者合法权益的有效手段。相比于传统的检测方法,无损检测技术因其能实现不破坏被检样品的同时获取内外部有效信息的优点而被广泛应用于食品的产地溯源领域。本文主要概述了近红外光谱、高光谱成像、拉曼光谱三种光谱检测技术的原理及其在不同种类可食用农产品产地溯源中的最新应用现状,得出各光谱检测技术在农产品产地鉴别方面具有一定的可行性,同时对未来的研究方向作了展望,以期为农产品产地溯源的无损检测技术体系研究提供理论参考。     

近红外光谱检测技术在肉类工业中的应用

近年来,近红外光谱技术(near infrared reflectance spectroscopy,NIRS)已经成为肉和肉产品品质检测中最为有效、先进的方法之一。本文回顾了应用NIRS技术对食品化学成分、物理性质和感官指标的检测,说明了NIRS技术在肉品分级制度中的应用,并讨论了NIRS在肉品工业上的应用前景。     

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。