Evidence map›Paper›PMID 37614741›Full record

ArticleFrontiers in nutrition2023

Effect of ultrasonic treatment on the quality of Mianning ham.

Jiaju He, Wei Wang, Jiamin Zhang, Yanli Zhu, Wenli Wang, Ting Bai, Lili Ji, Lin Chen

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2023. 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

8 authors.

Jiaju HeKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Wei WangKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Jiamin ZhangKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Yanli ZhuKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Wenli WangKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Ting BaiKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Lili JiKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.
Lin ChenKey Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper investigates the optimal process for ultrasonic desalination of Mianning ham. The study analyzed various factors such as ultrasonic treatment time, temperature, and power to determine their impact on the rate of desalination of hams. A single factor test was conducted to study the rate of desalination. Further, A Box-Behnken experimental design was used to evaluate the effect of Mianning ham desalination. The design examined the impacts of ultrasound on the physicochemical properties, texture, and sensory of the ham. Response surface processing group underwent oral processing to determine the optimal ultrasonic treatment conditions with the highest acceptance level. The results show that the best conditions were: ultrasonic time 84.56 min, ultrasonic temperature 40.35°C, and ultrasonic power 150.85 W. The average desalination rate of the ham under the optimal conditions was 25.93% ± 0.69%, and the hardness was 4.48 N ± 0.62 N. Overall, this process significantly improved the desalination rate, texture, and sensory quality of Mianning ham, providing solid theoretical support for desalination processing at the back end of ham.

Indexed as

desalting technologyMianning hamoral processingresponse surface methodologyultrasonic

Identifiers

PMID37614741
PMCPMC10443918

What OpenQuestion holds

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LicenceCC BY
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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.