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

A consumer perspective of the South African red meat classification system

The South African consumer market is characterised by socio-economic and cultural diversity. Food expenditure patterns, behaviour and preferences differ significantly between the various socio-economic sub-groups. Packaging information, including red meat classification information, could be an important tangible resource used by consumers to gauge product quality. The first objective of the research reported in this paper is to investigate the red meat knowledge, usage and perceptions regarding beef and sheep meat classification and related quality parameters among South African consumers. Consumer perceptions of red meat classification were extracted from a comprehensive consumer survey among stratified representative samples of South African low-, middle- and high-income consumers (n = 165, n = 171 and n = 249). The paper also briefly reports on an in-store ‘observational’ research project that was conducted to develop an understanding of the communication of carcass classification to consumers through fresh red meat product labels at independent butchers and large retailers across South Africa (n = 60). Low-income consumers had very limited understanding and gave little attention to red meat classification. Even though middle-class and wealthy consumers also have a limited understanding of red meat classification, about half of these consumers check for a classification mark. Red meat classification was not mentioned by consumers as a major concern regarding red meat, but related aspects were important such as quality, fattiness, tenderness, juiciness, taste, freshness, smell and appearance. Purchase considerations for beef and mutton/lamb focussed largely on safety, appearance, price and eating quality. Labelling information observed at retail outlets gave very little attention to classification. There is a definite need for consumer education relating to the red meat classification system and for the development of an appropriate front-of-pack labelling system to communicate red meat classification.The authors The Red Meat Research and Development South Africa (RMRDSA), and the Institute of Food, Nutrition and Well-being, University of Pretoria.http://www.sasas.co.za/am201

Consumers’ perceptions and experiences of food quality in purchasing fresh food from retail outlets in Malaysia

Malaysia, like many other developing countries, is experiencing major change within its retail food industry. A number of pull factors including an increase in personal disposable income, greater urbanisation, changes in lifestyle and an increasing interest in food safety have contributed to the emergence of modern supermarkets and hypermarkets in Malaysia. Previous studies into the impact of modern food retailing suggest that many consumers will shift their food purchasing behaviour from the traditional retail outlets to modern retail formats which offer better quality products, lower prices, a more comfortable environment and the convenience of one-stop shopping.A shopping-mall intercept survey of more than 500 food shoppers in the Klang Valley revealed that despite the expansion of modern retail formats in Kuala Lumpur, most consumers still purchase the majority of their fresh/chilled meat and fresh fruit and vegetables from traditional retail outlets. Although modern retail outlets and traditional markets share many of the same variables which influence respondents’ choices of retail stores, the traditional markets for fresh/chilled meat are anticipated to remain strong as many consumers perceive that the food available from these markets is guaranteed Halal and safe to eat. Furthermore, consumers still appreciate the personalised service offered by trusted and knowledgeable vendors, which is seldom offered when purchasing fresh food from a modern retail outlet. Among the main drivers for consumers to purchase their fresh fruit and vegetables from a traditional market were the ability to bargain on price, the lower price offered and the wider range of fresh produce available.In the attempt to identify the relationship between the perceived quality cues and quality attributes in respondents’ decisions to purchase fresh food, the findings from this study reveal that a number of variables were utilised by respondents to evaluate a multiple number of desired values. The freshness of both fresh/chilled meat and fresh fruit and vegetables signifies that the food will have a good taste, a good texture/mouth feel, be healthy and nutritious and represent good value for money. Fresh/chilled meat that is free from growth promotants and fresh produce that is free from chemical residues indicates that the food is safe to eat, healthy and nutritious and has been produced in a manner that was not harmful for the environment or worker welfare. The findings of the study have practical implications for producers, food marketers and the government

Perceptions of rural consumers and the quality of mutton at purchase points in the Eastern Cape Province, South Africa

The objective of the study was to determine perceptions of rural consumers on mutton quality, and the quality of mutton at purchase points in the Eastern Cape Province, South Africa. The study was conducted in five different municipalities (Buffalo City, Nkonkobe, Ngqushwa, Lukhanje and Amahlathi). A survey was conducted where a sample of 215 consumers were randomly selected and interviewed, either at point of purchase or as they left the shops. The survey was not limited to the shoppers only but also extended to households from the villages. Questions on some of the most important meat quality cues were compiled. The physico-chemical quality of mutton purchased from different shops was also determined. Forty different shops and butcheries selling mutton from all the selected municipalities were visited. Different parts of mutton samples were bought. Physico-chemical qualities of mutton such as colour (L* - lightness, b* - redness and a* - yellowness) and meat pH measurements were taken at points of purchase. Cooking loss and tenderness evaluations were later done at the Meat Science laboratory at the University of Fort Hare. The results indicated that price was one of the major factors affecting the purchasing decisions of consumers. Thirty four percent of the consumers preferred mutton as compared to other protein sources, even though they were not buying this type of meat because it was not affordable to them. Both male and female consumers suggested that more sheep farmers need to be established in order to reduce the levels of imported mutton into South Africa. They also highlighted that selection programmes that will result in efficient sheep production and reduced mutton prices need to be implemented. Meat at points of purchase was affected by season resulting in lower lightness (L*24.7±0.49) values in winter and higher (L* 32.2±0.49) in Spring. The class of shop did not have an effect on meat quality attributes. Trotter had high values of lightness (L*30.4±2.78a), redness (a*30.4±2.78a), yellowness (13.1±1.08a), pH (6.3±0.12a), tenderness (24.9±3.69b) and cooking loss (39.5±4.38ab). The number of days from when the meat was put on the shelves to the time when it was purchased for consumption (days to purchase) had a significant (P<0.05) negative correlation with the Warner Braztler Shear Force (WBSF)values and lightness of the meat. Significant negative (P < 0.05) correlations between pH and colour of the meat (L*, a* and b*) were also observed. It was concluded that rural consumers perceive the quality of mutton as the best and that the physico-chemical quality of meat purchased from different shops was different, largely based on the part of meat, meat storage conditions and not necessarily on the class of the shop

Food Recognition and Ingredient Detection Using Electrical Impedance Spectroscopy With Deep Learning Techniques to Facilitate Human-food Interactions

Food is a vital component of our everyday lives closely related to our health, well-being, and human behavior. The recent advancements of Spatial Computing technologies, particularly in Human-Food interactive (HFI) technologies have enabled novel eating and drinking experiences, including digital dietary assessments, augmented flavors, and virtual and augmented dining experiences. When designing novel HFI technologies, it is essential to recognize different food and beverages and their internal attributes (i.e., food sensing), such as volume and ingredients. As a result, contemporary research employs image analysis techniques to identify food items, notably in digital dietary assessments. These techniques, often combined with AI algorithms, analyze digital food images to extract various information about food items and quantities. However, these visual food analyzing methods are ineffective when: 1) identifying food’s internal attributes, 2) discriminating visually similar food and beverages, and 3) seamlessly integrating with people’s natural interactions while consuming food (e.g., automatically detecting the food when using a spoon to eat). This thesis presents a novel approach to digitally recognize beverages and their attributes, an essential step towards facilitating novel human-food interactions. The proposed technology has an electrical impedance measurement unit and a recognition method based on deep learning techniques. The electrical impedance measurement unit consists of the following components: 1) a 3D printed module with electrodes that can be attached to a paper cup, 2) an impedance analyzer to perform Electrical Impedance Spectroscopy (EIS) across two electrodes to acquire measurements such as a beverage’s real part of impedances, imaginary part of impedances, phase angles, and 3) a control module to configure the impedance analyzer and send measurements to a computer that has the deep learning framework to conduct the analysis. Two types of multi-task learning models (hard parameter sharing multi-task network and multi-task network cascade) and their variations (with principal component analysis and different combinations of features) were employed to develop a proof-of-concept prototype to recognize eight different beverage types with various volume levels and sugar concentrations: two types of black tea (LiptonTM and TwiningsTM English-Breakfast), two types of coffee (StarbucksTM dark roasted and medium roasted), and four types of soda (regular and diet coca-cola, and regular and diet Pepsi). Measurements were acquired from these beverages while changing volume levels and sugar concentrations to construct training and test datasets. Both types of networks were trained using the training dataset while validated with the test dataset. Results show that the multi-task network cascades outperformed the hard parameter sharing multi-task networks in discriminating against a limited number of drinks (accuracy = 96.32%), volumes (root mean square error = 13.74ml), and sugar content (root mean square error = 7.99gdm3). Future work will extend this approach to include additional beverage types and their attributes to improve the robustness and performance of the system and develop a methodology to recognize solid foods with their attributes. The findings of this thesis will contribute to enable a new avenue for human-food interactive technology developments, such as automatic food journaling, virtual flavors, and wearable devices for non-invasive quality assessment

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