ReviewPlant foods for human nutrition (Dordrecht, Netherlands)2026
Advances in Alternative Protein Design: Nutritional Constraints, Sensory Limits, and Computational Solutions.
Review in Plant foods for human nutrition (Dordrecht, Netherlands), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Development of a Soy-Pea-Based Nugget Using Texturized Commercial Products: Physicochemical and Sensory Evaluation.Plant foods for human nutrition (Dordrecht, Netherlands) · 2026Article
- Rethinking Plant Proteins: Innovations in Nutrition, Processing, and Food Development.Plant foods for human nutrition (Dordrecht, Netherlands) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The transition toward sustainable protein sources has driven growing interest in plant, insects, and microalgae proteins as alternatives to animal-derived ingredients. However, their variable amino acid composition, functional and sensory characteristics limit their application in high-quality food formulations. Computational approaches such as linear programming, mathematical optimization, and artificial intelligence offer powerful tools to design nutritionally balanced and functionally feasible protein blends. By integrating data on protein quality, techno-functional properties, and sensory thresholds, these methods enable the rational selection and combination of ingredients. This review summarizes current advances in computational food design, highlighting how data-driven formulation can accelerate innovation in sustainable protein products and bridge the gap between empirical experimentation and predictive modeling.
Indexed as
Identifiers
42014561What Socratic holds
Registered trials
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 Socratic graph.