Siamese network‐based computer vision approach to detect papaya seed adulteration in black peppercorns

Emergence of Internet of Things technology in food and agricultural sector: A review

Food processing is an indispensable sector crucial for controlling the food losses. Discrete measures were introduced and implemented to enhance the food shelf life and preservation techniques. However, poor handling and preservation methods usher to the food deprivation. In such milieu, amalgamation of futuristic technologies like sophisticated sensors tether with Internet of Things (IoT) could shoot up the food safety and minimize the deprivation. Research across the globe have proved that integration of IoT‐smart sensors in scrutinizing ecological factors such as temperature, radiation, gaseous composition, relative humidity, and moisture content that are critical for food processing and preservation. IoT has the prospects to ameliorate nationwide explicable execution, slash energy depletion, slash manufacturing expenses, inflate worker health and safety during food processing unit. Smart agricultural techniques also enable measurement of temperature, relative humidity, soil moisture, and nitrogen contents in smart farming and helps the user to determine the status of crops and commodity. This article aims to focus a few aspects and budding areas of IoT in the food and agricultural sectors. With this outlook, advancement and smartness in agriculture and food processing can be created by collaborating with IoT technology.

Applications of Electronic Nose, Electronic Eye and Electronic Tongue in Quality, Safety and Shelf Life of Meat and Meat Products: A Review

The quality and shelf life of meat and meat products are key factors that are usually evaluated by complex and laborious protocols and intricate sensory methods. Devices with attractive characteristics (fast reading, portability, and relatively low operational costs) that facilitate the measurement of meat and meat products characteristics are of great value. This review aims to provide an overview of the fundamentals of electronic nose (E-nose), eye (E-eye), and tongue (E-tongue), data preprocessing, chemometrics, the application in the evaluation of quality and shelf life of meat and meat products, and advantages and disadvantages related to these electronic systems. E-nose is the most versatile technology among all three electronic systems and comprises applications to distinguish the application of different preservation methods (chilling vs. frozen, for instance), processing conditions (especially temperature and time), detect adulteration (meat from different species), and the monitoring of shelf life. Emerging applications include the detection of pathogenic microorganisms using E-nose. E-tongue is another relevant technology to determine adulteration, processing conditions, and to monitor shelf life. Finally, E-eye has been providing accurate measuring of color evaluation and grade marbling levels in fresh meat. However, advances are necessary to obtain information that are more related to industrial conditions. Advances to include industrial scenarios (cut sorting in continuous processing, for instance) are of great value.

Application of Machine Vision System in Food Detection

Food processing technology is an important part of modern life globally and will undoubtedly play an increasingly significant role in future development of industry. Food quality and safety are societal concerns, and food health is one of the most important aspects of food processing. However, ensuring food quality and safety is a complex process that necessitates huge investments in labor. Currently, machine vision system based image analysis is widely used in the food industry to monitor food quality, greatly assisting researchers and industry in improving food inspection efficiency. Meanwhile, the use of deep learning in machine vision has significantly improved food identification intelligence. This paper reviews the application of machine vision in food detection from the hardware and software of machine vision systems, introduces the current state of research on various forms of machine vision, and provides an outlook on the challenges that machine vision system faces.