ArticleFoods (Basel, Switzerland)2026
A Multi-Task Learning Model Based on DTP-MMoE for Identification of Olive Oil Multi-Adulteration Using Raman Spectroscopy.
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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Abstract
Olive oil adulteration with low-cost vegetable oils poses a serious food safety concern. This study proposes a Dynamic Task Priority Multi-Gate Mixture-of-Experts (DTP-MMoE) model based on Raman spectroscopy to simultaneously perform the qualitative discrimination of adulteration types and quantitative prediction of adulteration ratios. The model learns shared spectral representations through expert networks and task-specific gating mechanisms, while a dynamic task priority loss function adaptively balances optimization between the classification and regression tasks. Experimental results demonstrated that the DTP-MMoE model achieved a classification accuracy of 99.15% and a coefficient of determination (R
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