Evidence map›Paper›PMID 39619960›Full record

ArticleFood science & nutrition2024

Ultrasonic-assisted extraction of nanocellulose from sweet potato residue and its application in noodles.

Xueli Gao, Guanghui Li, Yonghui Wang, Weiyun Guo, Shenghua He, Jihong Huang

Abstract read
In one paragraph

Article in Food science & nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Ultrasound-Assisted Enzymatic Extraction ofFood science & nutrition · 2025
    Article
  2. 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

6 authors.

Xueli GaoFood and Pharmacy College, Xuchang University Xuchang China.
Guanghui LiFood and Pharmacy College, Xuchang University Xuchang China.ORCID https://orcid.org/0000-0003-4459-3621
Yonghui WangFood and Pharmacy College, Xuchang University Xuchang China.
Weiyun GuoFood and Pharmacy College, Xuchang University Xuchang China.
Shenghua HeFood and Pharmacy College, Xuchang University Xuchang China.
Jihong HuangFood and Pharmacy College, Xuchang University Xuchang China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enhancing the amount of dietary fiber without compromising the quality of noodles remains a challenge in the food industry. This study aimed to optimize the ultrasound-assisted extraction parameters to enhance the yield of nanocellulose from sweet potato residue (SPR) using a response surface methodology. The impact of SPR nanocellulose on noodles' physicochemical properties was also explored. Results showed that the optimal extraction conditions for nanocellulose from SPR were identified as 180.73 U/mL cellulase concentration, 4.28 h ultrasonic time, 444.12 W ultrasonic power, and 14.17 h enzymatic hydrolysis time. The max yield of nanocellulose was 15.93% at optimum extraction conditions. Increasing the amount of SPR nanocellulose resulted in a reduction in the optimal cooking time, water absorption, elongation index, and springiness, as well as an increase in the breaking rate, cooking loss, hardness, gumminess, and chewiness of the noodles. Sensory analysis revealed higher acceptability of the noodles with 6%-12% SPR nanocellulose compared to other treatments. Microstructure demonstrated that noodles with 0%-18% SPR nanocellulose exhibited fewer holes and denser network structures, but higher SPR nanocellulose damaged the protein network. Those findings suggested that noodles with less than 12% SPR nanocellulose exhibited higher quality. This research provided the foundation for the development of nanocellulose-enriched foods.

Indexed as

nanocellulosenoodlessweet potato residueultrasonic‐assisted extraction

Identifiers

PMID39619960
PMCPMC11606810

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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.