Myoglobin-Based Classification of Minced Meat Using Hyperspectral Imaging

Minced meat substitution is one of the most common frauds which not only affects consumer health but impacts their lifestyles and religious customs as well. A number of methods have been proposed to overcome these frauds; however, these mostly rely on laboratory measures and are often subject to human error. Therefore, this study proposes novel hyperspectral imaging (400–1000 nm) based non-destructive isos-bestic myoglobin (Mb) spectral features for minced meat classification. A total of 60 minced meat spectral cubes were pre-processed using true-color image formulation to extract regions of interest, which were further normalized using the Savitzky–Golay filtering technique. The proposed pipeline outperformed several state-of-the-art methods by achieving an average accuracy of 88.88%

Trends in application of NIR and hyperspectral imaging for food authentication

Food fraud can cause damage to consumer health and affect their confidence, destroy brands and generate large economic losses in the industry. Food authenticity allows to identify if food composition, geographical origin, genetic variety and farming system corresponds to what has been declared on the label. Although there are currently standardized methods to identify certain adulterants, the complexity of the food, the complexity of the supply chain and the appearance of new adulterants require the continuous development of analytical techniques to detect food fraud. NIR and Hyperspectral imaging (HSI) in tandem with chemometrics are non-destructive, non-invasive and accurate techniques for food authentication. This review focuses on NIR and HIS approaches to food authentication, including adulteration by substitution, geographical origin and farming system. In this context, the advances in NIR and HSI approaches reported since 2014 are discussed regarding their potential use in food authentication. Both techniques have shown to have efficiency, precision and selectivity to detect adulterants and identify geographic origin, genetic variety and farming system. Portability and remote access are shown as the next step for the industrialization of NIR and HSI devices

Detection and quantification of paprika powder adulteration by near infrared (NIR) spectroscopy

Orientador: Douglas Fernandes BarbinDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: A páprica é uma das especiarias mais consumidas no mundo, e devido aos seus atributos sensoriais desejáveis, ela apresenta um alto valor de mercado. Embora especiarias como o pó de páprica sejam usadas e consumidas apenas em pequenas quantidades, elas estão presentes em muitos alimentos processados. Em razão disso, ela se torna susceptível a adulteração por motivação econômica. Por esse motivo, muitos esforços têm sido feitos no desenvolvimento de técnicas analíticas para detecção dessas práticas fraudulentas. No entanto, muitas dessas técnicas tradicionais são destrutivas, utilizam reagentes químicos e seu uso é dispendioso e demorado. Por outro lado, técnicas de espectroscopia vibracional, aliadas a quimiometria, surgem como uma alternativa promissora na detecção de adulteração na indústria de ervas e especiarias. O uso dessas técnicas traz como vantagens a rapidez e a natureza não-destrutiva das análises. Dessa forma, a espectroscopia de infravermelho próximo (NIR) tem sido utilizada com êxito, na verificação da autenticidade e no controle de qualidade desses produtos. Diante disso, o presente trabalho teve como objetivo investigar as potencialidades da espectroscopia NIR, em conjunto com a análise multivariada, na detecção e quantificação de substâncias estranhas (fécula de batata, goma arábica e urucum), em páprica em pó. Na determinação dos níveis de adulteração, foi utilizada a regressão por mínimos quadrados parciais (PLSR). Melhores resultados da calibração PLSR foram obtidos com um número reduzido de variáveis, aplicando o método de seleção de variáveis a partir do gráfico dos coeficientes de regressão. Como resultado, para os modelos PLSR reduzidos construídos a partir dos dados espectrais de NIR, os coeficientes de determinação de predição (R2p) foram 0,960, 0,968 e 0,874 para fécula de batata, goma arábica e urucum, respectivamente e os erros quadráticos médios de predição (RMSEP) foram 1,86, 1,68 e 1,74, respectivamente. Finalmente, a análise discriminante de mínimos quadrados parciais (PLS-DA) foi o método utilizado para estabelecer um modelo de classificação para discriminar amostras de páprica adulteradas e não adulteradas e também identificar o tipo de adulteração. Assim, este método de classificação mostrou-se bastante eficiente, com especificidade maior que 90% e taxa de erro menor que 2%, para todos os modelos construídos. Os resultados obtidos neste estudo mostraram que a espectroscopia NIR, combinada com a quimiometria podem ser uteis para a rápida detecção e/ou quantificação da adulteração em páprica em póAbstract: Paprika is one of the most consumed spices in the world, and because of its desirable sensory attributes, it has a high market value. Although spices such as paprika powder are used and consumed only in small amounts, they are present in many processed foods. Because of this, it becomes susceptible to adulteration by economic motivation. For this reason, much effort has been expended in developing analytical techniques to detect such fraudulent practices. However, many of these traditional techniques are destructive, use chemical reagents and their use is expensive and time consuming. On the other hand, techniques of vibrational spectroscopy, combined with chemometrics, appear as a promising alternative in the detection of adulteration in the herb and spice industry. The use of these techniques brings as advantages the speed and the non-destructive nature of the analyses. Thus, near infrared spectroscopy (NIR) has been successfully used to verify the authenticity and quality control of these products. The objective of this study was to investigate the potential of NIR spectroscopy, in conjunction with the multivariate analysis, in the detection and quantification of foreign substances (potato starch, acacia gum and annatto) in powdered paprika. In the determination of adulteration levels, partial least squares regression (PLSR) was used. The best results of the PLSR calibration were obtained with a reduced number of variables, applying the method of selection of variables from the graph of the regression coefficients. As a result, for the reduced PLSR models built with NIR spectral data, the prediction determination coefficients (R2p) were 0.960, 0.968 and 0.874 for potato starch, acacia gum and annatto, respectively, and the mean squared errors of prediction (RMSEP) were 1.86, 1.68 and 1.74, respectively. Finally, the discriminant analysis of partial least squares (PLS-DA) was the method used to establish a classification model to discriminate adulterated and unadulterated paprika samples and also to identify the type of adulteration. Hence, this method of classification proved to be efficient, with specificity greater than 90% and error rate lower than 2%, for all models constructed. The results obtained in this study showed that NIR spectroscopy, combined with chemometrics may be useful for the rapid detection and / or quantification of paprika powder adulterationMestradoEngenharia de AlimentosMestre em Engenharia de AlimentosCAPE

Non-destructive imaging and spectroscopic techniques for assessment of carcass and meat quality in sheep and goats: a review

In the last decade, there has been a significant development in rapid, non-destructive and non-invasive techniques to evaluate carcass composition and meat quality of meat species. This article aims to review the recent technological advances of non-destructive and non-invasive techniques to provide objective data to evaluate carcass composition and quality traits of sheep and goat meat. We highlight imaging and spectroscopy techniques and practical aspects, such as accuracy, reliability, cost, portability, speed and ease of use. For the imaging techniques, recent improvements in the use of dual-energy X-ray absorptiometry, computed tomography and magnetic resonance imaging to assess sheep and goat carcass and meat quality will be addressed. Optical technologies are gaining importance for monitoring and evaluating the quality and safety of carcasses and meat and, among them, those that deserve more attention are visible and infrared reflectance spectroscopy, hyperspectral imagery and Raman spectroscopy. In this work, advances in research involving these techniques in their application to sheep and goats are presented and discussed. In recent years, there has been substantial investment and research in fast, non-destructive and easy-to-use technology to raise the standards of quality and food safety in all stages of sheep and goat meat production. © 2020 by the authors.Authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020); Laboratory of Carcass and Meat Quality of Agriculture School of Polytechnic Institute of Bragança ‘Cantinho do Alfredo’. The authors A. Teixeira and S. Rodrigues are members of the Healthy Meat network, funded by CYTED (ref. 119RT0568). CECAV authors are thankful to the project UIDB/CVT/00772/2020 funded by the Foundation for Science and Technology (FCT, Portugal).info:eu-repo/semantics/publishedVersio

Non-destructive Detection of Food Adulteration to Guarantee Human Health and Safety

The primary objective of this review is to critique the basic concepts of non-destructive detection of food adulteration and fraud which collectively represent a tremendous annual financial loss worldwide and a major cause of human disease. The review covers the principles of the analytical instrumentation used for the non-destructive detection of food adulteration. Examples of practical applications of these methods for the control of food adulteration are provided and a comparative analysis of the advantages and disadvantages of instrumental methods in food technology are critiqued.Целью данного обзора является критическое рассмотрение основных понятий неразрушающего выявления фальсификации и подделки продуктов питания, которые в целом вызывают огромные ежегодные финансовые убытки во всем мире и являются одной из основных причин заболеваний человечества. Материалы и методы. Литература, указанная в данном обзоре, была получена в результате поиска библиографической информации в CAB abstracts, AGRICOLA, SciFinder Scholar, Modern Language Association (MLA), American Psychological Association (APA), OECD / EEA database по инструментам, которые используются для экологической политики и управления природными ресурсами, и Web of Science.Результаты и обсуждение. Фальсификация пищевых продуктов означает преднамеренное, обманное добавление посторонних, нестандартных или дешевых ингредиентов в продукты, или разбавление или удаление некоторых ценных ингредиентов с целью увеличения прибыли. В современных условиях производители стремятся увеличить выпуск своей продукции зачастую путем изготовления и продажи некачественных и фальсифицированных продуктов.“Неразрушающее выявление фальсификации пищевых продуктов” означает анализ образца и его существенных признаков без изменения физических и химических свойств образца. Повышение качества и безопасности пищевых продуктов путем разработки научных методов обнаружения фальсификации является главным условием для поддержания здоровья потребителей. Точная объективная оценка качества и выявление фальсификации пищевых продуктов представляется важнейшей целью пищевой промышленности. В связи с совершенствованием технологии фальсификации продуктов важно быть в курсе современных, самых точных методов контроля их фальсификации. С этой целью данный обзор рассматривает основные понятия выявления фальсификации продуктов питания, принципы устройств и возможные практические применения современных методов неразрушающего выявления фальсификации продуктов питания; сравнительный анализ преимуществ и недостатков инструментальных методов, используемых в пищевых технологиях. Каждый из рассмотренных методов обсуждается с точки зрения возможных различных консистенций продуктов – газов (свободного пространства вокруг продукта), свободно текущих жидкостей (соков), мутных и вязких жидкостей (меда как продукта растительного происхождения, растительных масел) и интактных продуктов (фруктов и овощей).Выводы. Результаты, освещенные в обзоре, рекомендуется использовать при контроле качества и безопасности пищевых продуктов.Метою даного огляду є критичний розгляд основних понять неруйнівного виявлення фальсифікації і підробки продуктів харчування, які в цілому викликають величезні щорічні фінансові збитки у всьому світі і є однією з основних причин захворювань людства. Матеріали і методи. Література, зазначена в даному огляді, була отримана в результаті пошуку бібліографічної інформації в in CAB abstracts, AGRICOLA, SciFinder Scholar, Modern Language Association (MLA), American Psychological Association (APA), OECD/EEA database щодо інструментів, які використовуються для екологічної політики та управління природними ресурсами, та Web of Science. Результати та обговорення. Фальсифікація харчових продуктів означає умисне, облудне додавання сторонніх, нестандартних або дешевих інгредієнтів в продукти, або розбавлення чи видалення деяких цінних інгредієнтів з метою збільшення прибутків. У сучасних умовах виробники прагнуть збільшити випуск своєї продукції найчастіше шляхом виготовлення та продажу неякісних та фальсифікованих продуктів. “Неруйнівне виявлення фальсифікації харчових продуктів” означає аналіз зразка і його істотних ознак без зміни фізичних і хімічних властивостей зразка. Підвищення якості та безпеки харчових продуктів шляхом розробки наукових методів виявлення фальсифікації є головною умовою для підтримки здоров’я споживачів. Точна об’єктивна оцінка якості і виявлення фальсифікації харчових продуктів представляється найважливішою метою харчової промисловості. У зв’язку з удосконаленням технології фальсифікації продуктів важливо бути в курсі сучасних, найбільш точних методів контролю їх фальсифікації. З цією метою даний огляд розглядає основні поняття виявлення фальсифікації продуктів харчування, принципи пристроїв і можливі практичні застосування сучасних методів неруйнівного виявлення фальсифікації продуктів харчування; порівняльний аналіз переваг і недоліків інструментальних методів, що застосовуються в харчових технологіях. Кожен з розглянутих методів обговорюється з точки зору можливих різних консистенцій продуктів - газів (вільного простору навколо продукту), вільно текучих рідин (соків), каламутних та в'язких рідин (меду як продукту рослинного походження, рослинних масел) і інтактних продуктів (фруктів і овочів). Висновки. Результати, висвітлені в огляді, рекомендується використовувати під час контролю якості та безпеки харчових продуктів

Novel Spectral and Spatial Process Analytical Tools for Meat Quality and Safety Assessment

Meat and meat products are highly nutritious, containing important levels of protein, vitamins, minerals and micronutrients, which are important for human growth and development. Beef has emerged as an important protein source in human diets. Minced beef is the primary ingredient for a variety of products such as burgers, meat balls, meat pastes, sausages and so on. Authenticity of the meat is a major requirement to meet the demands of consumers and assuring compliance with the government regulations and safety standards. Near-Infrared (NIR) spectroscopy and Hyperspectral Imaging (HSI) are sensing solutions which provide real time quality control and assurance. Laser Induced breakdown spectroscopy (LIBS) is an emerging technology in the area of mineral analysis in food. The unique spectral features obtained from NIR spectroscopy, HSI and LIBS make these techniques suitable for Process Analytical Technology (PAT) applications. The objective of this thesis was to evaluate the efficacy of novel spectroscopic techniques such as multi-point NIR spectroscopy, HSI and LIBS for performing quality monitoring of minced beef. A multi-point NIR system was successfully evaluated to identify and predict compositional attributes of minced beef such as moisture, fat, protein and ash; illustrating various features of the device. A HSI system was also successfully evaluated for identification and prediction of compositional attributes of minced beef along with chemical imaging. A LIBS system was successfully evaluated for: (a) quantification of minerals such as sodium (Na), potassium (K) and rubidium (Rb) in minced beef, (b) explore the potential of LIBS to detect offal adulteration and (c) demonstrate the ability of LIBS to provide spatial information of elements. Overall, the study illustrated the potential of these novel spectroscopic techniques for at/on/in-line quality monitoring of minced beef

Fraud Detection in Meat Using Hyperspectral Imaging

Fraud detection in meat is a challenging task for researchers, consumers, industries, and regulatory agencies. Traditional approaches for fraud detection are time-consuming, complicated, laborious, and expensive; they require technical skills. Therefore, much effort has been devoted in academia and industry to developing rapid and nondestructive optical techniques for fraud detection in meat. Among them, hyperspectral imaging has gained enormous attention and curiosity throughout the world. Hyperspectral imaging is an emerging analytical technique that combines spectroscopy and imaging in one system to acquire spectra and spatial information from an object simultaneously. Hyperspectral imaging is the only analytical technology that answers commonly asked analytical questions such as what chemical species are in the samples, how much, and most importantly, where they are located. Therefore, the technology will undoubtedly play indispensable roles in research and industry for fraud detection in the coming days

A review of optical nondestructive visual and near-infrared methods for food quality and safety

This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.©2013 the Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

HYPERSPECTRAL IMAGING TECHNIQUE AS A STATE OF ART TECHNOLOGY IN MEAT SCIENCE

Nowadays, the concern of meat consumption, safety and quality has been popular due to some health risks such coronary heart disease, stroke and diabetes caused by the content as saturated fat, cholesterol content and carcinogenic compounds, for consumers. The importance of the need of new non-destructive and fast meat analyze methods are increasing day by day.  For this, researchers have developed some methods to objectively measure the meat quality and meat safety as well as illness sources. Hyperspectral imaging technique is one of the most popular technology which combines imaging and spectroscopic technology. This technique is a non-destructive, real-time and easy-to-use detection tool for meat quality and safety assessment. It is possible to determine the chemical structure and related physical properties of meat. It is clear that hyperspectral imaging technology can be automated for manufacturing in meat industry and all of data’s obtained from the hyperspectral images which represent the chemical quality parameters of meats in the process can be saved to a database.&nbsp