A digital twin approach for optimizing okara-based Greek-style yogurt using hybrid Gompertz-LSTM modeling and data assimilation.

Donlaporn Saetae

Abstract read

In one paragraph

Article in Current research in food science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

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1 · What the graph read from it

What it found

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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5 · Who and what money

Authors and funding

1 author.

Donlaporn SaetaeDairy and Beverage Engineering Program, Department of Industrial Engineering, Faculty of Engineering, Mahidol University, Salaya, Nakhon Pathom, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant-based yogurts frequently exhibit inadequate structural integrity and pronounced syneresis. This study formulated a novel okara and coconut milk Greek-style plant-based yogurt and developed a physics-augmented digital twin for robust process control. Rheological and microstructural analyses, yielding a fractal dimension (

Indexed as

Data assimilationDigital twinHybrid machine learningOkara valorizationPlant-based yogurtRheological modeling

Identifiers

PMID42381723

DOI10.1016/j.crfs.2026.101480

PMCPMC13316634

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LicenceCC BY-NC-ND

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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.