Evidence map›Paper›PMID 35741911›Full record

ArticleFoods (Basel, Switzerland)2022

Characterization of Quality Properties in Spoiled Mianning Ham.

Yanli Zhu, Wei Wang, Yulin Zhang, Ming Li, Jiamin Zhang, Lili Ji, Zhiping Zhao, Rui Zhang, Lin Chen

Open access · goldAbstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 21 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Yanli ZhuKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.ORCID 0000-0003-4170-7697
Wei WangKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Yulin ZhangKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Ming LiKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Jiamin ZhangKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Lili JiKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Zhiping ZhaoKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Rui ZhangKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Lin ChenKey Lab of Meat Processing of Sichuan Province, Chengdu University, Chengdu 610106, China.
Chengdu University · CN

Funding

Liangshan Science and Technology Program 21CGZH0001National Modern Agricultural Industrial Technology System, Sichuan Innovation Team Construction Project SCSZTD-2022-08-07Sichuan Science and Technology Program 2020YFN0147
6 · The paper itself

Abstract

Deep spoilage is a cyclical and costly problem for the meat industry. Mianning ham is a famous dry-cured meat product in Sichuan, China. The aim of this work was to investigate the physicochemical characteristics, sources of odor, and associated microorganisms that cause spoilage of Mianning ham. High-throughput sequencing and solid-phase microextraction-gas-chromatography (SPME-GC-MS) techniques were used to characterize the physicochemical properties, microbial community structure, and volatile compounds of spoiled Mianning ham and to compare it with normal Mianning ham. The results showed that spoiled ham typically had higher moisture content, water activity (a

Indexed as

deep spoilagehigh-throughput sequencingMianning hamphysicochemical propertiesvolatile compounds

Identifiers

PMID35741911
PMCPMC9223196
OpenAlexW4283448545

What OpenQuestion holds

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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.