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不同红芸豆超声辅助浸泡过程的研究及近红外光谱法对浸泡水的成分分析

Investigation of the Ultrasonic Treatment-Assisted Soaking Process of Different Red Kidney Beans and Compositional Analysis of the Soaking Water by NIR Spectroscopy.

作者信息

Lukacs Matyas, Somogyi Tamás, Mukite Barasa Mercy, Vitális Flóra, Kovacs Zoltan, Rédey Ágnes, Stefaniga Tamás, Zsom Tamás, Kiskó Gabriella, Zsom-Muha Viktória

机构信息

Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Somlói út 14-16., H-1118 Budapest, Hungary.

Department of Postharvest, Supply Chain, Commerce and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Ménesi út 43-45., H-1118 Budapest, Hungary.

出版信息

Sensors (Basel). 2025 Jan 7;25(2):313. doi: 10.3390/s25020313.

DOI:10.3390/s25020313
PMID:39860682
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11769365/
Abstract

The processing of beans begins with a particularly time-consuming procedure, the hydration of the seeds. Ultrasonic treatment (US) represents a potential environmentally friendly method for process acceleration, while near-infrared spectroscopy (NIR) is a proposedly suitable non-invasive monitoring tool to assess compositional changes. Our aim was to examine the hydration process of red kidney beans of varying sizes and origins. Despite the varying surface areas, the beans' soaking times of 13-15, 15-17, and 17-19 mm did not reveal significant differences between any of the groups (control; low power: 180 W, 20 kHz; high power: 300 W, 40 kHz). US treatment was observed to result in the release of greater quantities of water-soluble components from the beans. This was evidenced by the darkening of the soaking water's color, the increase in the a* color parameter, and the rise in the dry matter value. NIRs, in combination with chemometric tools, are an effective tool for predicting the characteristics of bean-soaking water. The PLSR- and SVR-based modelling for dry matter content and light color parameters demonstrated robust model fits with cross and test set-validated R values (>0.95), suggesting that these techniques can effectively capture the chemical information of the samples.

摘要

豆类的加工始于一个特别耗时的过程,即种子的水合作用。超声处理(US)是一种潜在的加速加工过程的环保方法,而近红外光谱(NIR)是一种被认为适合用于评估成分变化的非侵入性监测工具。我们的目的是研究不同大小和来源的红芸豆的水合过程。尽管表面积不同,但13 - 15毫米、15 - 17毫米和17 - 19毫米的豆子浸泡时间在任何组(对照组;低功率:180瓦,20千赫兹;高功率:300瓦,40千赫兹)之间均未显示出显著差异。观察到超声处理导致从豆子中释放出更多的水溶性成分。浸泡水颜色变深、a*颜色参数增加以及干物质值上升证明了这一点。近红外光谱结合化学计量工具是预测豆类浸泡水特性的有效工具。基于偏最小二乘回归(PLSR)和支持向量回归(SVR)对干物质含量和浅色参数的建模显示出稳健的模型拟合,交叉验证和测试集验证的R值均大于0.95,表明这些技术能够有效地捕捉样品的化学信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/20a292d99e6e/sensors-25-00313-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/2f63056616e0/sensors-25-00313-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/e80de9a0db76/sensors-25-00313-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/50314b55c30d/sensors-25-00313-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/20a292d99e6e/sensors-25-00313-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/2f63056616e0/sensors-25-00313-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/eb76277bcc26/sensors-25-00313-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/8ef0ab70e02d/sensors-25-00313-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/b438141a2151/sensors-25-00313-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/b8d3e1625f45/sensors-25-00313-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/e80de9a0db76/sensors-25-00313-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/50314b55c30d/sensors-25-00313-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f79/11769365/20a292d99e6e/sensors-25-00313-g008.jpg

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