Evidence map›Paper›PMID 39272495›Full record

ArticleFoods (Basel, Switzerland)2024

Fast and Reliable On-Site Quality Assessment of Essential Raw Brewing Materials Using MicroNIR and Chemometrics.

Giuseppina Gullifa, Chiara Albertini, Elena Papa, Rita Petrucci, Paola Di Matteo, Martina Bortolami, Stefano Materazzi, Roberta Risoluti

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Giuseppina GullifaDepartment of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.ORCID 0000-0001-9252-8205
Chiara AlbertiniDepartment of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.ORCID 0009-0003-5090-3179
Elena PapaDepartment of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.ORCID 0000-0001-9262-9006
Rita PetrucciDepartment of Basic and Applied Sciences for Engineering, Sapienza University of Rome, Via Castro Laurenziano, 7, 00161 Roma, Italy.ORCID 0000-0003-2411-825X
Paola Di MatteoDepartment of Basic and Applied Sciences for Engineering, Sapienza University of Rome, Via Castro Laurenziano, 7, 00161 Roma, Italy.ORCID 0000-0001-8837-6317
Martina BortolamiDepartment of Basic and Applied Sciences for Engineering, Sapienza University of Rome, Via Castro Laurenziano, 7, 00161 Roma, Italy.ORCID 0000-0001-5740-6499
Stefano MaterazziDepartment of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.ORCID 0000-0002-8468-5291
Roberta RisolutiDepartment of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.ORCID 0000-0002-6213-5387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interest in the quality control of the raw materials, intermediates, and final products, as well as production methods, of beer has increased significantly in recent decades due to the needs and expectations of consumers. Increasing in the industrialization and globalization of beer supply chains led to a need for novel analytical tools suitable for the rapid and reliable characterization of the materials involved. In this study, an ultracompact instrument operating in the NIR region of the spectrum, microNIR, was tested for the chemical investigation of barley malts. The essential raw materials for brewing require careful control since they deeply affect the characteristic flavor and taste of the final products. Therefore, a robust prediction model able to classify base and specialty barley malts was developed starting from NIR measurements. Soft Independent Class Analogy (SIMCA) was selected as the chemometric technique for the optimization of two prediction models, and ground and sieved materials were investigated using spectroscopy. The microNIR/chemometric approach proposed in this study permitted the correct prediction of the malt samples included in the external validation set, providing false positive and false negative rates no higher than 3.41% and 0.25%, respectively, and confirming the feasibility of the novel analytical platform.

Indexed as

chemometricsinnovative platformmaltsmicroNIRquality control

Identifiers

PMID39272495
PMCPMC11394839

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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.