高光谱成像技术在动物源性食品微生物污染快速检测中的应用进展

高光谱成像(hyperspectral imaging,HSI)技术作为一种无损、快速、准确的检测技术在动物源性食品微生物污染检测方面得到了广泛应用.该技术集图像与光谱技术的优势于一体,可同时检测实验样品的物理特征与化学特征.本文系统地综述HSI原理,及其在动物源性食品微生物(菌落总数、腐败菌、致病菌)污染无损检测方面...     

近红外光谱技术在生鲜禽肉质量检测中应用的研究进展

近红外光谱（near-infrared spectroscopy,NIRS）技术作为一种快速、无损、绿色的检测技术正在被广泛用于禽肉品质研究,通过将肉样光谱信息和品质指标参考值相关联,构建高精度、高稳定性的数学模型预测未知肉品品质。相比传统检测方式,NIRS技术具有无需预处理、更加丰富的信息量、数据计算更快等优势,在肉制品检测应用方面潜力巨大。本文主要综述了NIRS技术在生鲜禽肉（鸡肉、鸭肉、鹅肉）物理属性、化学指标以及微生物腐败等方面检测的研究进展,归纳总结了NIRS技术结合不同化学计量学算法构建模型检测禽肉各品质指标的效果,同时提出了NIRS技术在检测禽肉方面存在的缺点及未来发展趋势,可为改善NIRS技术检测应用、研发便携式NIRS检测设备提供数据支撑和理论参考。     

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。     

高光谱成像技术应用于畜禽肉品品质研究进展

食品安全不光关乎我们身体健康而且影响着社会稳定,做好食品安全检测是防止有毒食品进入人体的关键步骤也是维护社会稳定的重要举措。为改善传统畜禽肉质检测方法费时费力的现状,食品安全检测方法正趋于多样化,引入了许多高新技术,高光谱成像技术（hyperspectral imaging,HSI）便是其中之一。它是将成像技术和光谱技术相结合,在不损伤产品外形的情况下得到产品外部图像特征和产品内部品质信息光谱图,本文从畜禽肉品品质安全角度出发,围绕畜禽肉品化学指标、物理属性和食用安全指标三个方面,综述了高光谱成像技术在畜禽肉品安全检测中的应用,归纳总结了预处理,变量筛选和建模方法。对目前高光谱成像技术应用于畜禽肉品检测中所暴露的缺点进行总结, 并就未来发展方向进行展望,为食品安全检测提供了新的参考。     

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.     

近红外光谱技术在乳制品快速检测中的应用研究进展

近红外光谱（NIR）技术作为一种高效、快速、便捷、低成本、无污染的检测方法,在乳制品快速检测中具有广泛的应用。该文首先阐述了近红外光谱技术的原理,并探讨了其优缺点,列举了常用的化学计量学方法,综述了近红外光谱技术应用于乳制品中掺假识别、微生物快速检测、化学成分快速检测、快速鉴定牛奶品牌等方面的最新研究进展和成果,为近红外光谱技术在乳制品快速检测中的应用推广提供参考。     

鱼油品质光谱检测技术的研究进展

鱼油制品具有丰富的营养功能,深受消费者喜欢。常规检测鱼油品质方法,由于操作困难、破坏性强、试剂污染等缺点,不能满足快速无损、高效无污染的检测要求。光谱检测技术(如近红外光谱技术和核磁共振技术),伴随着化学计量学的发展,突破了常规检测方法局限性,是鱼油品质检测技术的发展趋势。在大量文献的基础上,综述目前光谱检测技术在鱼油品质的应用情况,特别分析光谱方法、化学计量学和仪器设备,指出现阶段利用光谱技术检测鱼油品质存在的主要问题,并对今后的研究方向进行展望。     

近红外光谱分析在食品检测中的最新进展

近红外光谱分析技术是一种需较少预处理的快速无损伤技术，这项技术已广泛应用于食品化学组成和物化性质分析中。简述了近红外光谱技术在食品组成成分、食品品质、食品生产和食品安全等四个方面应用的最新进展。     

多光谱成像技术在食品营养品质检测方面的应用进展

食品营养品质是食品的重要属性之一。开展储藏加工过程营养品质的快速无损监测与评价具有重要意义。多光谱成像(Multispectral imaging,MSI)技术是一种近几年发展起来的食品快速无损检测新技术,它将光谱信息和成像数据结合起来,利用化学计量学技术对数据进行筛选建模,进而构建食品品质快速无损高效准确评价方法。本文对近五年国内外多光谱成像技术在肉类、果蔬和粮油作物营养品质检测方面的研究进展进行了总结和讨论,主要涉及到食品中水分、蛋白质、脂肪、可溶性固形物、生物活性物质等多种含量及变化。同时对多光谱成像技术目前的局限性进行了讨论,并对该技术未来的发展方向进行了展望,以期研发出可以应对复杂工业生产环境的在线多光谱成像检测设备。     

坚果品质检测方法研究进展

坚果含有优质蛋白质、脂肪等丰富的营养物质,深受消费者喜爱。由于富含不饱和脂肪酸及油脂,坚果的品质易受贮藏条件、加工方式及包装方式等外部因素的影响而发生变化,不当的处理会加速其氧化哈败,甚至产生对人体有害的毒素。另一方面,坚果品质受产地、品种、土壤环境及遗传因素等方面的影响表现出不同的外观性状及理化特征。随着科学技术的发展,坚果品质的检测趋向于无损、快速,电子鼻在这方面有着突出的优势,因此电子鼻对坚果品质的无损检测成为研究的新热点。本文从口感、色泽、风味、外观性状等感官检测,营养品质（蛋白质、脂肪等）、油脂品质（酸价、过氧化值等）等理化检测,光谱分析技术（近红外光谱、高光谱等）、电子鼻技术等快速检测方法综述了坚果品质检测方法的研究现状,为坚果品质的监控和检测提供技术参考。     

Recent Developments and Applications of Hyperspectral Imaging for Quality Evaluation of Agricultural Products: A Review

Food quality and safety is the foremost issue for consumers, retailers as well as regulatory authorities. Most quality parameters are assessed by traditional methods, which are time consuming, laborious, and associated with inconsistency and variability. Non-destructive methods have been developed to objectively measure quality attributes for various kinds of food. In recent years, hyperspectral imaging (HSI) has matured into one of the most powerful tools for quality evaluation of agricultural and food products. HSI allows characterization of a sample's chemical composition (spectroscopic component) and external features (imaging component) in each point of the image with full spectral information. In order to track the latest research developments of this technology, this paper gives a detailed overview of the theory and fundamentals behind this technology and discusses its applications in the field of quality evaluation of agricultural products. Additionally, future potentials of HSI are also reported.     

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.     

Principles of Hyperspectral Microscope Imaging Techniques and Their Applications in Food Quality and Safety Detection: A Review

Hyperspectral imaging (HSI) techniques play an important role in the food industry for providing rapid, nondestructive, and chemical‐free detection method, whereas a microscope can provide detailed information about the microstructure of a food item. As an emerging imaging spectroscopy technique, hyperspectral microscope imaging (HMI) technique combines the advantages of HSI with microscopic imaging and has been gradually applied in the food industry. This review introduces the principles of different kinds of HMI techniques, such as fluorescence HMI, visible/near‐infrared HMI, Raman HMI, and infrared HMI. Moreover, detailed applications of HMI techniques are summarized, including evaluation of structures of nutrients, and detection of microorganisms and residues. On the other hand, some challenges and future trends in the applications of these techniques are also discussed. It is concluded that by integrating HSI with microscopy, HMI can not only provide both spectral and spatial information about food substances but also provide their chemical information at the molecular or cellular level. Therefore, HMI techniques have great potentials in nondestructive evaluation of structures of nutrients, and detection of microorganisms and residues for the food industry.     

Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review

Fourier transform infrared (FT‐IR) and Raman and hyperspectral imaging (HSI) techniques have emerged as reliable analytical methods for effectively characterizing and quantifying quality attributes of different categories of powdery food products (such as milk powder, tea powder, cocoa powder, coffee powder, soybean flour, wheat flour, and chili powder). In addition to the ability for gaining rapid information about food chemical components (such as moisture, protein, and starch), and classifying food quality into different grades, such techniques have also been implemented to determine trace impurities in pure foods and other properties of particulate foods and ingredients with avoidance of extensive sample preparation. Developments of corresponding quality evaluation systems based on FT‐IR, Raman, and HSI data that measure food quality parameters and ensure product authentication, would bring about technical and economic benefits to the food industry by enhancing consumer confidence in the quality of its products. Accordingly, a comprehensive review of the mushrooming spectroscopy‐based FT‐IR, Raman, and HSI literature is carried out in this article. The spectral data collected, the chemometric methods used, and the main findings of recent research studies on quality assessments of powdered materials are discussed and summarized. Providing a review in such a flourishing research field is relevant as a signpost for future study. The conclusion details the promise of how such noninvasive and powerful analytical techniques can be used for rapid and accurate determinations of powder quality attributes in both academical and industrial settings.     

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.     

Recent Progress of Hyperspectral Imaging on Quality and Safety Inspection of Fruits and Vegetables: A Review

Objective quality assessment and efficacious safety surveillance for agricultural and food products are inseparable from innovative techniques. Hyperspectral imaging (HSI), a rapid, nondestructive, and chemical‐free method, is now emerging as a powerful analytical tool for product inspection by simultaneously offering spatial information and spectral signals from one object. This paper focuses on recent advances and applications of HSI in detecting, classifying, and visualizing quality and safety attributes of fruits and vegetables. First, the basic principles and major instrumental components of HSI are presented. Commonly used methods for image processing, spectral pretreatment, and modeling are summarized. More importantly, morphological calibrations that are essential for nonflat objects as well as feature wavebands extraction for model simplification are provided. Second, in spite of the physical and visual attributes (size, shape, weight, color, and surface defects), applications from the last decade are reviewed specifically categorized into textural characteristics inspection, biochemical components detection, and safety features assessment. Finally, technical challenges and future trends of HSI are discussed.     

Applications of hyperspectral imaging in grains and nuts quality and safety assessment: a review

Quality of foods is generally controlled with traditional methods such as microbiological and chemical tests. However, the necessity of a non-destructive, rapid and accurate on-line method to monitor the product quality and safety is the key topic of many research studies. Hyperspectral imaging (HSI) has emerged as a powerful tool to handle the afore-mentioned goals. It is a novel technique that combines simultaneous advantages of imaging and spectroscopy. HSI is an analytical method that simultaneously delivers chemical, structural and functional information from the sample. This technique can be used to analyze both individual kernels and bulk samples and simultaneously determine quality parameters of grains and nuts. Nuts and grains are nutrient dense foods with complex matrices rich in mono- and poly-unsaturated fatty acids, vegetable proteins, fiber, vitamins, minerals etc. Therefore, nuts and grains are useful dietary sources to decrease the risk of diabetes, cancer and cardiovascular disease. In this paper, recent applications of hyperspectral imaging in quality and safety inspection of nuts and grains such as classification, compositions prediction, texture analysis, and detection of varietal impurities, damages, and infections are reviewed.