ReviewFrontiers in nutrition2026
Multiscale time-domain NMR for structural, water, and texture characterization of meat and plant-based food matrices: a mini review.
Review in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Water self-diffusion differentiates two protein-based burger matrices with contrasting sensory juiciness.Current research in food science · 2026Article
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1 author.
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Abstract
Time-domain nuclear magnetic resonance (TD-NMR) is a powerful, non-destructive method for probing water mobility, molecular dynamics, and hierarchical structure in complex food matrices. Over the past several decades, numerous studies have demonstrated that relaxation, diffusion, and relaxometry-derived parameters are closely linked to microstructural constraints, water distribution, texture, and water-holding capacity (WHC) in both muscle and plant-based systems. This mini review synthesizes foundational and recent advances into a unified multiscale TD-NMR framework spanning molecular (μs-ms), mesoscopic (μm), and macroscopic (mm-cm) levels. We show how T₁/T₂ relaxation, diffusion coefficients, and multidimensional correlation methods can be mapped onto structural and functional properties of native meat and engineered plant-based matrices. Integrating these TD-NMR modalities with microstructural imaging and texture profiling provides a quantitative approach for mechanistic understanding and product optimization. Future opportunities include machine-learning tools for multidimensional datasets, physics-guided inversion algorithms, and the development of industrial, inline TD-NMR sensing platforms.
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