a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
b Food Refrigeration and Computerised Food Technology, Agriculture and Food Science Centre, University College Dublin, National University of Ireland , Belfield , Dublin 4 , Ireland.
Crit Rev Food Sci Nutr. 2016;56(1):113-27. doi: 10.1080/10408398.2013.873885.
With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.
随着消费者对食品质量和安全的关注度不断提高,近年来,食品行业开始更加注重快速、可靠的食品评估系统的发展。因此,制造商和零售商非常需要在食品生产和加工过程中对食品质量和安全进行有效的实时评估。计算机视觉作为一种无损评估方法,具有快速、易用和最小化样本准备等优点,能够评估食品产品的特性。具体来说,计算机视觉系统可用于将食品产品分类为特定等级、检测缺陷以及估计颜色、形状、大小、表面缺陷和污染等特性。因此,为了跟踪该技术在农业食品行业的最新研究进展,本综述旨在介绍计算机视觉系统的原理和仪器,并详细介绍 2007 年至 2013 年期间其在农业食品产品质量评估中的应用,同时结合光谱学讨论其未来趋势。