Evidence map›Paper›PMID 38384537›Full record

ArticleHeliyon2024

Determining food safety in canned food using fuzzy logic based on sulphur dioxide, benzoic acid and sorbic acid concentration.

Nidhi Rajesh Mavani, Jarinah Mohd Ali, M A Hussain, Norliza Abd Rahman, Haslaniza Hashim

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
8.2field-weighted citation impact, top 1% 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

5 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Food preservatives: natural or synthetic?Archives of microbiology · 2026
    Review
  3. Article
  4. Article
  5. 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

5 authors at 2 institutions in 1 country.

Nidhi Rajesh MavaniDepartment of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia.
Jarinah Mohd AliDepartment of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia.
M A HussainDepartment of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Norliza Abd RahmanDepartment of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia.
Haslaniza HashimDepartment of Food Sciences, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia.
National University of Malaysia · MYUniversity of Malaya · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Canned food market demand has arisen due to the higher need for instant and ready-to-eat food. Food preservatives are often added to canned and processed foods to prolong their shelf life and help to sustain the quality, taste, color, and food texture. However, excessive usage of such food preservatives can lead to various diseases and health issues including palpitations, allergies, and cancer. Therefore, food preservative detection in food samples is essential for safe consumption and health well-being. This paper proposed a fuzzy logic framework to determine the safety of food products based on the concentration of sulphur dioxide (SD), benzoic acid (BA), and sorbic acid (SA) in five different food categories as referred to the Food Acts 1983 and Food Regulations 1985 in Malaysia. The fuzzy logic framework comprises of Mamdani inference system design with 90 fuzzy rules, 15 and 5 membership functions for both the input and output parameters respectively. 50 random values and 10 lab analysis results based on the industrial samples were used to validate the developed algorithms in ensuring the safety of the food products. The membership functions generated for the three inputs (SD, BA, and SA) during the fuzzification steps are based on the maximum allowable limit from the food acts. The defuzzification of fuzzy logic gave an average output value of 0.1565, 0.1350, 0.1150, 0.1100, and 0.1550 for chicken curry with potatoes, satay sauce, sardine in tomato sauce, anchovies paste, and sardine spread accordingly. Results obtained from the fuzzy logic framework concluded that all the industrial samples are safe to be eaten and comply with the Sixth Schedule, Regulation 20 in both Acts.

Indexed as

Artificial intelligenceFoodFood preservativesFood safetyFuzzy logic

Identifiers

PMID38384537
PMCPMC10879013
OpenAlexW4391718300

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.