Predictive Models of Phytosterol Degradation in Rapeseeds Stored in Bulk Based on Artificial Neural Networks and Response Surface Regression.

Jolanta Wawrzyniak, Magdalena Rudzińska, Marzena Gawrysiak-Witulska, Krzysztof Przybył

Open access · goldAbstract read

In one paragraph

Article in Molecules (Basel, Switzerland), 2022. 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

0.1field-weighted citation impact, top 68% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

Optimization and Modeling ofSensors (Basel, Switzerland) · 2023
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 at 1 institution in 1 country.

Jolanta WawrzyniakFaculty of Food Science and Nutrition, Poznań University of Life Sciences, 60-624 Poznań, Poland.ORCID 0000-0002-6720-891X

Magdalena RudzińskaFaculty of Food Science and Nutrition, Poznań University of Life Sciences, 60-624 Poznań, Poland.ORCID 0000-0001-6343-332X

Marzena Gawrysiak-WitulskaFaculty of Food Science and Nutrition, Poznań University of Life Sciences, 60-624 Poznań, Poland.

Krzysztof PrzybyłFaculty of Food Science and Nutrition, Poznań University of Life Sciences, 60-624 Poznań, Poland.ORCID 0000-0002-2535-8370

University of Life Sciences in Poznań · PL

Funding

Polish Ministry of Science and Higher Education 005/RID/2018/19

6 · The paper itself

Abstract

The need to maintain the highest possible levels of bioactive components contained in raw materials requires the elaboration of tools supporting their processing operations, starting from the first stages of the food production chain. In this study, artificial neural networks (ANNs) and response surface regression (RSR) were used to develop models of phytosterol degradation in bulks of rapeseed stored under various temperatures and water activity conditions (

Indexed as

Brassica napusPhytosterolsNeural Networks, ComputerTemperatureWaterPhytosterolsWaterartificial neural networksphytosterol degradationpostharvest preservation systemspredictive modelingrapeseed storageresponse surface regression

Identifiers

PMID35458643

DOI10.3390/molecules27082445

PMCPMC9027000

OpenAlexW4223533590

What Socratic 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 Socratic graph.