Development of multivariate regression models for real-time monitoring of physicochemical changes of foodstuffs during drying process using Vis-NIR optical imaging

开发多元回归模型，利用 Vis-NIR 光学成像实时监测食品在干燥过程中的理化变化

• 批准号: 420778578
• 负责人: Professor Dr. Oliver Hensel
• 金额: --
• 依托单位: Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/420778578?language=en
• 关键词: Development; multivariate; regression; models; real

Drying is the most widely used method of long-term foodstuffs preservation. Currently employed drying methods result predominantly in a low retention of product quality. Polyphenols, carotenoids, and vitamins are some of the most important nutritious substances which are very sensitive to heat. Furthermore, physical attributes undergo severe changes during the thermal processing. For the optimization of the process, it is intrinsic to fully understand the dynamic changes of a product (and its components) undergoing throughout the process, which is only possible if reliable non-invasive quality inspection systems are available. To this end, optical techniques as non-destructive, non-contact, and rapid tools for monitoring of foodstuffs exposed to the drying process have gained a significant interest over the last decades. The current study intends to develop, evaluate, and compare multivariate regression models based on the data acquired using a hyperspectral and four multispectral imaging techniques (i.e. laser-light backscattering, biospeckle, Filter- and LED-based imaging techniques) in the spectrum range of 400-1700 nm with the aim of prediction of total polyphenols, total carotenoids, vitamin C (ascorbic acid), soluble solid contents (SSC), moisture content, shrinkage, rehydration, and firmness of apple, potato, and carrot (two varieties and maturities each) during a hot-air drying process. Most research in the field of optical monitoring of foodstuffs exposed to drying process is limited to the measurement of moisture content. There is a severe lack of knowledge in optical measurement of polyphenols, carotenoids, and vitamins (particularly vitamin C) during the drying process, particularly with a view of the development of non-invasive real-time measurement devices and protocols. Furthermore, previous studies have mainly focused on the application of the hyperspectral imaging technique, whilst the current research will investigate the possible replacement of hyperspectral imaging with different multispectral imaging techniques with the aim of delivering a smart drying system which is in line with the principles of Agriculture 4.0 and Industry 4.0. Biospeckle imaging, one of the multispectral imaging techniques which has a great potential for the inclusion in drying process, will for the first time be studied for its appropriateness. The results of this study will significantly contribute to a deeper understanding of optical techniques and their potential use in real-time observation of drying processes. The developed methods and set-ups will also open new possibilities for wider application across the field of food processing and product quality driven process control.

干燥是最广泛使用的食品长期保存方法。目前采用的干燥方法主要导致产品质量保持率低。多酚、类胡萝卜素和维生素是一些对热非常敏感的最重要的营养物质。此外，物理属性在热处理期间经历严重变化。为了优化工艺，必须充分了解产品（及其组件）在整个工艺过程中的动态变化，只有在可靠的非侵入式质量检测系统可用的情况下才有可能。为此，光学技术作为非破坏性的，非接触的，和快速的工具，用于监测暴露于干燥过程中的食品已经获得了显着的兴趣在过去的几十年。目前的研究旨在开发，评估和比较多元回归模型的基础上获得的数据使用高光谱和四个多光谱成像技术在400-1700 nm的光谱范围内，使用激光背散射、生物散斑、基于滤光片和LED的成像技术，预测总多酚、总类胡萝卜素、维生素C苹果、土豆和胡萝卜（各两个品种和成熟度）在热风干燥过程中的抗坏血酸含量、可溶性固形物含量（SSC）、含水量、收缩率、复水率和硬度。在食品干燥过程的光学监测领域，大多数研究仅限于水分含量的测量。在干燥过程中多酚、类胡萝卜素和维生素（特别是维生素C）的光学测量方面，特别是在非侵入式实时测量设备和协议的开发方面，存在严重缺乏知识。此外，以前的研究主要集中在高光谱成像技术的应用上，而目前的研究将探讨用不同的多光谱成像技术替代高光谱成像的可能性，目的是提供一个符合农业4.0和工业4.0原则的智能干燥系统。生物散斑成像是一种多光谱成像技术，在干燥过程中具有很大的潜力，将首次研究其适用性。这项研究的结果将大大有助于更深入地了解光学技术及其在实时观察干燥过程中的潜在用途。开发的方法和设置也将为食品加工和产品质量驱动的过程控制领域的更广泛应用开辟新的可能性。