Cross-attention fusion of Raman and NIR spectra for glucose soft sensing in fed-batch fermentation.

Boxue Chang, Jingyue Huang, Feng Xu, Yinlan Ruan, Xiwei Tian

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Article in Bioprocess and biosystems engineering, 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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5 authors.

Boxue ChangSchool of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China.

Jingyue HuangSchool of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, China.

Feng XuState Key Laboratory of Bioreactor Engineering, Qingdao Innovation Institute of East China University of Science and Technology, East China University of Science and Technology, Shanghai, 200237, China.

Yinlan RuanSchool of Optoelectronic Engineering, Guangxi Key Laboratory of Optoelectronic Information Processing, Guilin University of Electronic Technology, Guilin, 541004, China. yinlan.ruan@guet.edu.cn.

Xiwei TianState Key Laboratory of Bioreactor Engineering, Qingdao Innovation Institute of East China University of Science and Technology, East China University of Science and Technology, Shanghai, 200237, China. xiweitian@ecust.edu.cn.

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6 · The paper itself

Abstract

Timely and accurate glucose monitoring is essential for maintaining stable substrate supply during fed-batch fermentation, whereas conventional offline assays are difficult to integrate into high-frequency process monitoring. In this study, a Raman-NIR multimodal soft-sensing framework based on a dual-stream cross-attention Transformer (DS-CAT) was developed for glucose prediction in fermentation broth. A total of 142 synchronized Raman-NIR records were preprocessed using Savitzky-Golay first-derivative transformation and standard normal variate normalization. The two spectral modalities were encoded independently and fused through asymmetric cross-attention to integrate broadband NIR information with localized Raman fingerprint features. Model performance was evaluated on the test set, together with leakage-controlled five-fold internal validation within the development set. On the test set, DS-CAT achieved R² = 0.991, RMSE = 1.09 g L

Indexed as

Cross-attention transformerFed-batch fermentationGlucose soft sensingMultimodal spectral fusionNear-infrared spectroscopyProcess analytical technologyRaman spectroscopy

Identifiers

PMID42803924

DOI10.1371/journal.pone.0048127

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