Storage Properties and Shelf-Life Prediction of Fresh-Cut Radishes Treated by Photodynamic Technology.

Sijia Ruan, Tong Zhu, Changzhou Zuo, Jing Peng, Liwang Liu, Weijie Lan, Leiqing Pan, Kang Tu

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2024. 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.

Research Progress of Machine Learning in Extending and Regulating the Shelf Life of Fruits and Vegetables.Foods (Basel, Switzerland) · 2024
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

8 authors.

Sijia RuanCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.

Tong ZhuCollege of Food Science and Technology, Yunnan Agricultural University, Kunming 650201, China.

Changzhou ZuoCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.

Jing PengCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0002-0300-6147

Liwang LiuCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-7355-4408

Weijie LanCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-7997-3080

Leiqing PanCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-5587-3544

Kang TuCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0003-4314-2896

Funding

Fundamental Research Funds for the Central Universities (KYCYXT2022005), the Jiangsu Agricultural S&T Innovation Fund [CX(23)1013] and Jiangsu Agricultural Industry Technology System ( JATS[2023]421). (KYCYXT2022005)[CX(23)1013] ( JATS[2023]421)

6 · The paper itself

Abstract

Fresh-cut radishes are susceptible to quality loss and microbial contamination during storage, resulting in a short shelf life. This study investigated the effects of photodynamic technology (PDT) on fresh-cut radishes stored at 4 °C for 10 d and developed appropriate models to predict the shelf life. Results showed that curcumin-mediated PDT maintained sensory acceptability, color, and firmness, decreased weight loss, and increased ascorbic acid and total phenolics of samples by inactivating polyphenol oxidase and peroxidase, resulting in improved antioxidant capacity and quality. The total bacteria count in samples was significantly (

Indexed as

kinetic modelminimally processingphotodynamic treatmentshelf lifestorage quality

Identifiers

PMID39123557

DOI10.3390/foods13152367

PMCPMC11311309

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.