Evidence map›Paper›PMID 36193374›Full record

ArticleJournal of food science and technology2022

Evaluating the ability of rapid evaporative ionization mass spectrometry to differentiate beef palatability based on consumer preference.

Chaoyu Zhai, Bailey Schilling, Jessica E Prenni, J Chance Brooks, Jerrad F Legako, Rhonda K Miller, Michael J Hernandez-Sintharakao, Cody L Gifford, Robert Delmore, Mahesh N Nair

Abstract read
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In one paragraph

Article in Journal of food science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
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.

Chaoyu Zhai *Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA.
Bailey Schilling *Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA.
Jessica E PrenniDepartment of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523 USA.
J Chance BrooksDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409 USA.
Jerrad F LegakoDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409 USA.
Rhonda K MillerDepartment of Animal Science, Texas A&M University, College Station, TX 77843-2471 USA.
Michael J Hernandez-SintharakaoDepartment of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA.
Cody L GiffordDepartment of Animal Science, University of Wyoming, Laramie, USA.
Robert DelmoreDepartment of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA.
Mahesh N NairDepartment of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA.ORCID 0000-0002-2917-1028

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid Evaporative Ionization Mass Spectrometry (REIMS) is a type of ambient ionization mass spectrometry, which enables real-time evaluation of several complex traits from a single measurement. The objective of this study was to evaluate the capability of REIMS analysis of raw samples coupled with chemometrics to accurately identify and predict cooked beef palatability. REIMS analysis and consumer sensory evaluation were conducted for beef arm center roasts (n = 20), top loin steaks (n = 20), top sirloin steaks (n = 20), and 20% lipid ground beef (n = 20). These data were used to train predictive models for six classification sets representing different sensory traits. The maximum prediction accuracies achieved (from high to low): beefy flavor acceptance (86.25%), juiciness acceptance (83.75%), overall acceptance (81.25%), overall flavor acceptance (81.25%), grilled flavor acceptance (78.75%), and tenderness acceptance (75%). The current study demonstrates that REIMS analysis of raw meat has the potential to predict and classify cooked beef palatability. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05562-6.

Indexed as

Beef flavorConsumer panelCross validationJuicinessMetabolic fingerprintingREIMS

Identifiers

PMID36193374
PMCPMC9525463

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.