Evidence map›Paper›PMID 39860682›Full record

ArticleSensors (Basel, Switzerland)2025

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

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

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Matyas LukacsDepartment 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.ORCID 0009-0004-9613-910X
Tamás SomogyiDepartment 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.
Barasa Mercy MukiteDepartment 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.
Flóra VitálisDepartment 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.ORCID 0000-0002-4198-2202
Zoltan KovacsDepartment 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.ORCID 0000-0003-0641-8830
Ágnes RédeyDepartment 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.
Tamás StefanigaDepartment 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.
Tamás ZsomDepartment 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.
Gabriella KiskóDepartment of Food Microbiology, Hygiene and Safety, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, Somlói út 14-16., H-1118 Budapest, Hungary.ORCID 0000-0003-3344-5308
Viktória Zsom-MuhaDepartment 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.ORCID 0000-0002-7048-9767

Funding

Doctoral School of Food Science of the Hungarian University of Agriculture and Life Sciences 0the KDP-2023 Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund KDP-2023
6 · The paper itself

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

Indexed as

PhaseolusSeedsWaterSpectroscopy, Near-InfraredWatercanningchemometricshydrationNIR spectroscopypulsetechnology

Identifiers

PMID39860682
PMCPMC11769365

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.