A Machine Learning Model to Reframe the Concept of Shelf-Life in Bakery Products: PDO Sourdough as a Technological Preservation Model.

Andrea Marianelli, Cecilia Akotowaa Offei, Monica Macaluso, Nicola Mercanti, Bruno Casu, Angela Zinnai

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2025. 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.

Artificial intelligence in bread making: Applications in quality control, formulation and sensory prediction.Food chemistry: X · 2026
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

6 authors.

Andrea MarianelliDepartment of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy.ORCID 0009-0009-7173-6465

Cecilia Akotowaa OffeiDepartment of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy.

Monica MacalusoDepartment of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy.ORCID 0000-0001-7075-4252

Nicola MercantiDepartment of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy.

Bruno CasuINFN Pisa Section, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy.ORCID 0000-0002-1759-463X

Angela ZinnaiDepartment of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy.

Funding

PSR 2014-2022 of the 509 Tuscany Region (2022) PDO ORGANIC bread, PROJECT 16.2, PSR 2014-2022 of the 509 Tuscany Region (2022)

6 · The paper itself

Abstract

Traditional shelf-life (SL) determination in bakery products relies primarily on subjective sensory evaluation, limiting both predictive capability and technological transfer. This study aimed to develop an objective, data-driven framework by integrating statistical and Machine Learning (ML) methods to identify and quantify the core determinants of bread SL. Samples were produced under a 2 × 2 × 2 factorial design (Fermentation, Temperature, Packaging), with continuous monitoring of physicochemical and atmospheric parameters. Three-way ANOVA confirmed that Storage x Temperature (η

Indexed as

computationaldata drivenfermentationmicrostructureoptimizationpredictionstabilitysustainability

Identifiers

PMID41464943

DOI10.3390/foods14244236

PMCPMC12732183

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.