Evidence map›Paper›PMID 32893250›Full record

ArticleAnalytical sciences : the international journal of the Japan Society for Analytical Chemistry2021

Simultaneous, Rapid and Nondestructive Determination of Moisture, Fat Content and Storage Time in Leisure Dried Tofu Using LF-NMR.

Alin Xia, Yu Zhang, Liangzhong Zhao, Pan Qin

Abstract read
PubMed Publisher
In one paragraph

Article in Analytical sciences : the international journal of the Japan Society for Analytical Chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Unlocking the potential of bioanalytical data through machine learning.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2023
    Article
  2. Article
  3. 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

4 authors.

Alin XiaCollege of Food and Chemical Engineering, Shaoyang University, Shaoyang, 422000, China. alinxia@126.com.
Yu ZhangCollege of Food and Chemical Engineering, Shaoyang University, Shaoyang, 422000, China.
Liangzhong ZhaoCollege of Food and Chemical Engineering, Shaoyang University, Shaoyang, 422000, China.
Pan QinSichuan Yijie Technology Co., Ltd, 36 Chadianzi West Street, Jinniu District, Chengdu, 610036, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leisure dried tofu is a kind of small packaged food which is popular with consumers in China. However, during the storage of leisure dried tofu, moisture and fat may be lost and deteriorate. For their own benefit, bad business operators might forge or mark the production date and shelf life. Therefore, it is necessary to explore a method to determine simultaneously the moisture, fat content, and storage time of leisure dried tofu. Samples were measured for obtaining transverse relaxation data by using low-field nuclear magnetic resonance (LF-NMR) spectrometer. The experimental data were analyzed and modeled by methods including partial least squares (PLS) or back-propagation artificial neural network (BP-ANN). The results show that the models can be used to predict the moisture, fat content, and storage time rapidly, nondestructively, accurately, and simultaneously. Furthermore, in order to explore the changes of nutrients in leisure dried tofu with the storage time, the storage dynamics of moisture and fat was considered by a using corresponding calibration model.

Indexed as

Food StorageChinaFatsHumidityMagnetic Resonance SpectroscopySoy FoodsTime FactorsFatsfat contentLeisure dried tofuLF-NMRmoisturestorage dynamicsstorage time

Identifiers

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.