Olakanmi Sunday J, Jayas Digvir S, Paliwal Jitendra
Department of Biosystems Engineering, 75 Chancellors Circle, University of Manitoba, Winnipeg, Manitoba, R3T 5V6, Canada.
Compr Rev Food Sci Food Saf. 2023 May;22(3):1817-1838. doi: 10.1111/1541-4337.13131. Epub 2023 Mar 13.
One of the most widely researched topics in the food industry is bread quality analysis. Different techniques have been developed to assess the quality characteristics of bakery products. However, in the last few decades, the advancement in sensor and computational technologies has increased the use of computer vision to analyze food quality (e.g., bakery products). Despite a large number of publications on the application of imaging methods in the bakery industry, comprehensive reviews detailing the use of conventional analytical techniques and imaging methods for the quality analysis of baked goods are limited. Therefore, this review aims to critically analyze the conventional methods and explore the potential of imaging techniques for the quality assessment of baked products. This review provides an in-depth assessment of the different conventional techniques used for the quality analysis of baked goods which include methods to record the physical characteristics of bread and analyze its quality, sensory-based methods, nutritional-based methods, and the use of dough rheological data for end-product quality prediction. Furthermore, an overview of the image processing stages is presented herein. We also discuss, comprehensively, the applications of imaging techniques for assessing the quality of bread and other baked goods. These applications include studying and predicting baked goods' quality characteristics (color, texture, size, and shape) and classifying them based on these features. The limitations of both conventional techniques (e.g., destructive, laborious, error-prone, and expensive) and imaging methods (e.g., illumination, humidity, and noise) and the future direction of the use of imaging methods for quality analysis of bakery products are discussed.
面包品质分析是食品行业中研究最为广泛的课题之一。人们已经开发出不同的技术来评估烘焙食品的品质特性。然而，在过去几十年中，传感器和计算技术的进步增加了利用计算机视觉分析食品质量（如烘焙食品）的应用。尽管关于成像方法在烘焙行业应用的出版物众多，但详细介绍用于烘焙食品质量分析的传统分析技术和成像方法的综合综述却很有限。因此，本综述旨在批判性地分析传统方法，并探索成像技术在烘焙产品质量评估方面的潜力。本综述对用于烘焙食品质量分析的不同传统技术进行了深入评估，这些技术包括记录面包物理特性并分析其质量的方法、基于感官的方法、基于营养的方法以及利用面团流变学数据预测最终产品质量的方法。此外，本文还介绍了图像处理阶段的概述。我们还全面讨论了成像技术在评估面包和其他烘焙食品质量方面的应用。这些应用包括研究和预测烘焙食品的质量特性（颜色、质地、大小和形状），并基于这些特征对其进行分类。同时讨论了传统技术（如具有破坏性、费力、容易出错且成本高昂）和成像方法（如光照、湿度和噪声）的局限性，以及成像方法在烘焙食品质量分析方面的未来发展方向。
