Influence of physical and biological variability and solution methods in fruit and vegetable quality nondestructive inspection by using imaging and near-infrared spectroscopy techniques: A review

Over the past decades, imaging and spectroscopy techniques have been rapidly developing and widely applied in nondestructive fruit and vegetable quality assessment. The physical properties (including size, shape, color, position, and temperature) and biological properties (including cultivar, season, maturity level and geographical origin) of fruits and vegetables vary from one to another. A great variety of physical and biological properties of agricultural products influence the optical propagation properties and interaction behaviors with incident light, thus decreasing the quality inspection accuracy. Many attempts have been made in image correction and spectral compensation methods to improve the inspection accuracy. This paper gives a detailed summary about influence of physical and biological variability, as well as the correction and compensation methods for eliminating or reducing the effects in fruit and vegetable quality nondestructive inspection by using imaging and spectroscopy techniques. The advantages and disadvantages of the solution methods are discussed and summarized. Additionally, the future challenges and potential trends are also reported.     

A Comprehensive Review on Food Applications of Terahertz Spectroscopy and Imaging

Food product safety is a public health concern. Most of the food safety analytical and detection methods are expensive, labor intensive, and time consuming. A safe, rapid, reliable, and nondestructive detection method is needed to assure consumers that food products are safe to consume. Terahertz (THz) radiation, which has properties of both microwave and infrared, can penetrate and interact with many commonly used materials. Owing to the technological developments in sources and detectors, THz spectroscopic imaging has transitioned from a laboratory‐scale technique into a versatile imaging tool with many practical applications. In recent years, THz imaging has been shown to have great potential as an emerging nondestructive tool for food inspection. THz spectroscopy provides qualitative and quantitative information about food samples. The main applications of THz in food industries include detection of moisture, foreign bodies, inspection, and quality control. Other applications of THz technology in the food industry include detection of harmful compounds, antibiotics, and microorganisms. THz spectroscopy is a great tool for characterization of carbohydrates, amino acids, fatty acids, and vitamins. Despite its potential applications, THz technology has some limitations, such as limited penetration, scattering effect, limited sensitivity, and low limit of detection. THz technology is still expensive, and there is no available THz database library for food compounds. The scanning speed needs to be improved in the future generations of THz systems. Although many technological aspects need to be improved, THz technology has already been established in the food industry as a powerful tool with great detection and quantification ability. This paper reviews various applications of THz spectroscopy and imaging in the food industry.     

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。     

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.     

深度学习在水果品质检测与分级分类中的应用

水果自动无损品质检测与分级分类是保障人们健康的重要措施,也间接影响着水果的经济价值。随着计算机技术的飞速发展,以深度学习为代表的人工智能方法在水果品质检测与分级分类领域的研究中取得了一系列重要成果。本文概述了深度学习的背景及常用的深度学习主流算法,然后从水果外部品质检测、内部品质检测、安全品质检测和分级分类等方面综述了近年来深度学习在水果品质检测与分级分类领域的最新研究成果。最后总结了未来深度学习和水果品质检测、分级分类交叉融合研究与应用中的优势,并展望了水果品质检测与分级分类研究融合深度学习的未来发展方向。     

Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables

Artificial vision systems are powerful tools for the automatic inspection of fruits and vegetables. Typical target applications of such systems include grading, quality estimation from external parameters or internal features, monitoring of fruit processes during storage or evaluation of experimental treatments. The capabilities of an artificial vision system go beyond the limited human capacity to evaluate long-term processes objectively or to appreciate events that take place outside the visible electromagnetic spectrum. Use of the ultraviolet or near-infrared spectra makes it possible to explore defects or features that the human eye is unable to see. Hyperspectral systems provide information about individual components or damage that can be perceived only at particular wavelengths and can be used as a tool to develop new computer vision systems adapted to particular objectives. In-line grading systems allow huge amounts of fruit or vegetables to be inspected individually and provide statistics about the batch. In general, artificial systems not only substitute human inspection but also improve on its capabilities. This work presents the latest developments in the application of this technology to the inspection of the internal and external quality of fruits and vegetables.     

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。     

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.     

Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review

With improvement in people's living standards, many people nowadays pay more attention to quality and safety of meat. However, traditional methods for meat quality and safety detection and evaluation, such as manual inspection, mechanical methods, and chemical methods, are tedious, time-consuming, and destructive, which cannot meet the requirements of modern meat industry. Therefore, seeking out rapid, non-destructive, and accurate inspection techniques is important for the meat industry. In recent years, a number of novel and noninvasive imaging techniques, such as optical imaging, ultrasound imaging, tomographic imaging, thermal imaging, and odor imaging, have emerged and shown great potential in quality and safety assessment. In this paper, a detailed overview of advanced applications of these emerging imaging techniques for quality and safety assessment of different types of meat (pork, beef, lamb, chicken, and fish) is presented. In addition, advantages and disadvantages of each imaging technique are also summarized. Finally, future trends for these emerging imaging techniques are discussed, including integration of multiple imaging techniques, cost reduction, and developing powerful image-processing algorithms.     

基于太赫兹反射成像技术的花生空果无损检测

目的 基于太赫兹反射成像技术(Terahertz Reflection Imaging Method, THz-RIM)实现花生空果无损检测,为太赫兹技术在农产品及食品快速无损检测中的应用奠定基础。方法 利用太赫兹脉冲光谱仪TeraPulse 4000及反射成像附件和采集软件,在0.2 mm采集步长下对去壳花生仁进行太赫兹反射成像预实验,确定出正式实验的图像颜色模式为hot模式。人为制备若干个花育36号满仁花生果样本和空果样本(仅有一粒花生仁),在与预试验相同的条件下采集样本光谱图像,以时域/频域2点外相加成像(Integrated Time Slice)重构方式进行图像重构, 突出花生空果样本图像的显著几何特征。结果 通过太赫兹反射图像可以实现满仁与花生空果样本的检测区分,但图像细节仍然比较模糊,需进一步提高图像清晰度。采用数字图像方法进行图像增强,利用OpenCV-Python提高图像的亮度、色度、对比度及锐度。提升对比度后的图像可观测度最高,且空果图像中黑色部分面积占比最大,与含仁部分对比最为明显,可以实现空果及满仁花生果的快速区分。结论 探索结果表明,THz波对花生外壳具有良好的穿透性,利用THz-RIM技术结合OpenCV-Python数字图像处理方法进行花生空果无损检测具有可行性,利用太赫兹光谱技术对油料作物内部品质进行无损检测研究具有极大潜力。     

果蔬品质安全近红外光谱无损检测研究进展

我国果蔬产量和销量均居世界首位, 生产和消费正由产量规模型向质量效益型转变, 对果蔬品质安全检测的要求与日俱增。当前, 果蔬采后品质分级、安全检测和货架期评价尚处于人工或简单机械的粗略检测阶段, 果蔬的内在组分和内部缺陷采用破坏性抽检, 货架期采用人工经验式, 效率低且成本高。近红外光谱检测技术具有无损伤、快速绿色、适于现场检测和在线分析等优势, 适于构建果蔬快速、高精度、智能化的检测系统。本文分析了果蔬产业的发展现状及关键技术需求, 阐述了近红外光谱技术的基本原理, 分别从果蔬内部光传输特性、内在组分检测、隐形缺陷判识、货架期评价4个方面论述了国内外近红外光谱技术在果蔬品质安全检测应用中的最新研究进展, 深入分析了近红外光谱技术在果蔬品质安全检测中的存在的问题, 并指出了解决思路和进一步研究的方向。     

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.     

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Cereal grains and nuts are represented as the economic backbone of many developed and developing countries. Kernels of cereal grains and nuts are prone to mold infection under high relative humidity and suitable temperature conditions in the field as well as storage conditions. Health risks caused by molds and their molecular metabolite mycotoxins are, therefore, important topics to investigate. Strict regulations have been developed by international trade regulatory bodies for the detection of mold growth and mycotoxin contamination across the food chain starting from the harvest to storage and consumption. Molds and aflatoxins are not evenly distributed over the bulk of grains, thus appropriate sampling for detection and quantification is crucial. Existing reference methods for mold and mycotoxin detection are destructive in nature as well as involve skilled labor and hazardous chemicals. Also, these methods cannot be used for inline sorting of the infected kernels. Thus, analytical methods have been extensively researched to develop the one that is more practical to be used in commercial detection and sorting processes. Among various analytical techniques, optical imaging and spectroscopic techniques are attracting growers’ attention for their potential of nondestructive and rapid inline identification and quantification of molds and mycotoxins in various food products. This review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging. Advance chemometric techniques to identify very low-level mold growth and mycotoxin contamination are also discussed. Benefits, limitations, and challenges of deploying these techniques in practice are also presented in this paper.     

Wavelet Analysis of Signals in Agriculture and Food Quality Inspection

Food quality and safety have become the top priorities for agriculture and food processing industry due to the increasing consumer demand for high-quality healthy food. The food processing industry is currently focusing on using fast, precise, and nondestructive automated quality inspection techniques. Near-infrared spectroscopy, image processing, hyperspectral imaging, X-rays, and ultrasonic techniques have been researched and shown to have high potential for automated inspection. The biggest challenge in the automated inspection systems deals with signal pre-processing, denoising, feature extraction, and its re-synthesis for classification purposes. Several research studies have established that the technique of wavelet analysis can very well resolve these issues of signal processing in many systems used for quality inspection of agricultural and food products. The objective of this paper is to discuss the theory of wavelet analysis and review its application in signal processing and feature extraction for quality monitoring of agricultural and food products.     

Measurements of lycopene contents in fruit: A review of recent developments in conventional and novel techniques

Lycopene is a biologically active phytochemical reported in fruit. Conventional techniques such as high performance liquid chromatography (HPLC) and thin layer chromatography (TLC) have been in existence for measuring lycopene in fruit, but these methods are destructive with relative accuracy and speed. Other novel spectroscopic and imaging approaches, which are more reliable and fast, have recently been developed to investigate complex components such as lycopene, total soluble solids, etc. in fruit. The current review attempts to highlight the potential of both conventional and novel techniques in evaluating lycopene contents of fruit. The novel techniques include both spectroscopic methods such as near infrared spectroscopy and Raman spectroscopy and spectral imaging approaches such as multispectral imaging, hyperspectral imaging and Raman imaging. The principles of these techniques are summarized, their detailed applications are discussed, and future trends are also presented. Both traditional and novel techniques highlighted in the current review can be used for assessing the distribution and concentration of lycopene in various fruit. Although novel spectroscopic and spectral imaging approaches may in the near future replace conventional methods, because conventional methods are typically often offline, destructive and time-consuming, which also require the use of chemicals.     

Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment

Hyperspectral imaging systems are starting to be used as a scientific tool for food quality assessment. A typical hyperspectral image is composed of a set of a relatively wide range of monochromatic images corresponding to continuous wavelengths that normally contain redundant information or may exhibit a high degree of correlation. In addition, computation of the classifiers used to deal with the data obtained from the images can become excessively complex and time-consuming for such high-dimensional datasets, and this makes it difficult to incorporate such systems into an industry that demands standard protocols or high-speed processes. Therefore, recent works have focused on the development of new systems based on this technology that are capable of analysing quality features that cannot be inspected using visible imaging. Many of those studies have also centred on finding new statistical techniques to reduce the hyperspectral images to multispectral ones, which are easier to implement in automatic, non-destructive systems. This article reviews recent works that use hyperspectral imaging for the inspection of fruit and vegetables. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products. Particular attention is paid to the works aimed at reducing the dimensionality of the images, with details of the statistical techniques most commonly used for this task.     

水果病虫害无损检测技术研究进展

水果的病害和虫害是影响水果品质等级鉴定的重要因素。水果在生长、加工、贮藏、运输过程中容易受到病菌侵染和害虫侵蚀,这将造成水果品质降低,同时对食品安全也会造成不良影响。本文综述了X射线成像技术、计算机视觉技术、核磁共振技术、光谱技术、新兴传感器技术等无损检测技术在水果病虫害识别与检测中的应用进展,并分析各技术的优势和劣势,重点介绍了高光谱成像技术在水果病虫害识别与检测方面的应用进展,分析存在的问题、展望发展趋势,为后续研究提供参考。     

Recent Advances in Nondestructive Analytical Techniques for Determining the Total Soluble Solids in Fruits: A Review

The total soluble solids play an important role in the fruit maturity process and determine the acceptance of rich nutrients as well as economic benefits in the fruit trade. Thus, development of rapid and nondestructive techniques for evaluating soluble solids content in fruits is important. This review focuses on recent advances in nondestructive techniques for soluble solids contents of fruits including hyperspectral imaging, laser light backscattering imaging, magnetic resonance imaging, X‐ray computed tomography, near‐infrared spectroscopy, and Raman spectroscopy. The advantages and disadvantages of these techniques are compared and discussed, and some viewpoints about future trends are also presented.     

柑橘近红外光谱无损检测技术研究进展

柑橘是世界第一大水果,中国是柑橘生产和销售大国.现阶段我国柑橘产业存在各环节分离、加工技术粗糙、采后品质分级落后等问题,导致我国柑橘在国际市场上缺乏竞争力.对柑橘产品进行检测与分级是提高竞争力的有效手段,然而传统的柑橘品质检测手段如肉眼识别法、图像识别法、化学滴定法等存在费时费力、精度不高等缺陷,且化学滴定法等对样品具...