Synergistic Optimization of In Vitro Digestibility and Sensory Quality of Moderately Milled Rice Based on the RiceMambaOpt Model.

Zijun Li, Zhihong Wen, Mengting Ma, Wenshu Niu, Zhongquan Sui, Harold Corke

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in

0citing 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.

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zijun LiDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.

Zhihong WenCollege of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China.ORCID 0009-0006-1313-5889

Mengting MaDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.

Wenshu NiuCollege of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China.

Zhongquan SuiDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-5316-117X

Harold CorkeBiotechnology and Food Engineering Program, Guangdong Technion-Israel Institute of Technology, Shantou 515063, China.

Funding

Shanghai Jiao Tong University JCZXSJB2024-09

6 · The paper itself

Abstract

To address over-processing and limited process-control precision in rice manufacturing, this study developed an artificial intelligence (AI)-assisted optimization framework for rice milling. A data-driven predictive model was constructed to characterize the nonlinear relationships between milling conditions and the in vitro starch-digestibility and sensory attributes of rice. Across the nine physicochemical, in vitro starch-digestibility, and sensory indicators, RiceMambaOpt achieved a mean coefficient of determination (

Indexed as

artificial intelligencedeep learningintelligent controlinverse designmoderate processingrice processing

Identifiers

PMID42650505

DOI10.3390/foods15162812

PMCPMC13512138

What OpenQuestion holds

Textmetadata

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.