The Experts below are selected from a list of 30348 Experts worldwide ranked by ideXlab platform
Jose Blasco - One of the best experts on this subject based on the ideXlab platform.
-
automated systems based on machine vision for inspecting citrus fruits from the field to postharvest a review
Food and Bioprocess Technology, 2016Co-Authors: Sergio Cubero, Won Suk Lee, Nuria Aleixos, Francisco Albert, Jose BlascoAbstract:Computer vision systems are becoming a scientific but also a commercial tool for Food Quality Assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external Quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing.
Dawen Sun - One of the best experts on this subject based on the ideXlab platform.
-
recent advances in image processing using image texture features for Food Quality Assessment
Trends in Food Science and Technology, 2013Co-Authors: Patrick Jackman, Dawen SunAbstract:The use of computer vision technology has been highly successful in Food classification problems in the past and it has continued this success in recent times. There does however exist a number of opportunities to progress computer vision technology further, these opportunities are critically examined based on cost and feasibility. A range of hardware options are considered along with a range of software options. The economic cost of implementing new hardware continues to prove a major impediment. Thus future efforts need to be focused on maximising the potential benefits of the existing hardware framework and instead concentrate on developing improved software. Of the improved software available the aspect that offers the greatest promise is more efficient analysis of Food surface texture attributes which will lead to more powerful understanding of the relationships between Quality factors and experimentally measured Food Quality.
-
hyperspectral imaging for Food Quality analysis and control
2010Co-Authors: Dawen SunAbstract:Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive Food Quality analysis and control. "Hyperspectral Imaging for Food Quality Analysis and Control" provides the core information about how this proven science can be practically applied for Food Quality Assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world Food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating Food products. Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation. This title includes real-world, practical application to demonstrate the viability and challenges of working with this technology. It provides necessary information for making correct determination on use of hyperspectral imaging.
Alex Martynenko - One of the best experts on this subject based on the ideXlab platform.
-
IoT, big data and artificial intelligence in agriculture and Food industry
IEEE Internet of Things Journal, 2026Co-Authors: N N Misra, Ahmad Al-mallahi, Rohit Upadhyay, Manreet Singh Bhullar, Yash Dixit, Alex MartynenkoAbstract:Internet of things (IoT) results in massive amount of streaming data, often referred to as “big data”, which brings new opportunities to monitor agricultural and Food processes. Besides sensors, big data from social media is also becoming important for the Food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-Food systems. Following an introduction to the fields of IoT, big data, and AI, we discuss the role of IoT and big data analysis in agriculture (including greenhouse monitoring, intelligent farm machines, and drone-based crop imaging), supplychain modernization, social media (for open innovation and sentiment analysis) in Food industry, Food Quality Assessment (using spectral methods and sensor fusion), and finally, Food safety (using gene sequencing and blockchain based digital traceability). A special emphasis is laid on the commercial status of applications and translational research outcomes.
Tiziano Gomiero - One of the best experts on this subject based on the ideXlab platform.
-
Food Quality Assessment in organic vs conventional agricultural produce findings and issues
Applied Soil Ecology, 2017Co-Authors: Tiziano GomieroAbstract:Organic Food is increasingly attracting the interest of consumers, as it is perceived to be healthier than Food produced by conventional agriculture, and to be more sustainable for the environment. This paper provides a review on the Quality of organic produce in terms of its nutritional value, the presence of pesticide residues, heavy metals, mycotoxins and bacterial contamination, and the issue of antibiotics. The use of Recombinant Bovine Growth Hormone is addressed. Hydroponic techniques are also discussed. Compared to conventional produce, organic produce is richer in some useful compounds. Nevertheless, heterogeneous findings have been reported. Studies concord in finding organic Food much less contaminated by pesticides, and with residues of much lower toxicity compared to those found in conventional Foods. As for heavy metals, mycotoxins and bacterial contamination, there are no significant differences in organic produce compared to conventional produce (with the exception of Cd, found to be lower in organic produce, which is a positive finding). More effective and detailed guidelines should be devised for the design and reporting of both primary studies and meta-analyses. Pesticide residues should be assessed both quantitatively and qualitatively. The issue of multiple residues should also be addressed. Of course, organic produce cannot be assumed, a priori, to be safe. Sound monitoring needs to be constantly performed. It is concluded that organic agriculture can provide important benefits to human health and to the environment, and promote a more compassionate treatment of animals. It is hoped that agricultural policies will pay more attention to organic, agroecological and low-input agricultural practices, and invest in research and innovation.
Sergio Cubero - One of the best experts on this subject based on the ideXlab platform.
-
automated systems based on machine vision for inspecting citrus fruits from the field to postharvest a review
Food and Bioprocess Technology, 2016Co-Authors: Sergio Cubero, Won Suk Lee, Nuria Aleixos, Francisco Albert, Jose BlascoAbstract:Computer vision systems are becoming a scientific but also a commercial tool for Food Quality Assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external Quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing.