A review of research on plant‐based meat alternatives: Driving forces, history, manufacturing, and consumer attitudes
Bibliographic record
Abstract
The topic of plant-based meat alternatives (PBMAs) has been discussed for several decades, but it has only recently become one of the hottest topics in the food and research communities. With the purpose of investigating the current situation of scientific research on PBMA and determining future research opportunities, the driving forces for PBMA development, a brief history of its progression, key technologies required for production, and the resulting consumer attitudes are summarized. Environmental, human health, and animal welfare concerns are the main factors that have driven the development of PBMA. Although its history can trace back to ancient Asian civilizations, the first generation of PBMA originated in 1960s and a new generation of PBMA designed for carnivore was developed in recently years. Structuring methods such as extrusion and shear cell techniques have been widely studied, but improvements toward the overall appearance and flavor, biological and chemical safety control, as well as the selection of protein sources are also very important for PBMA production. The consumer acceptance of PBMA remains unsatisfactory but is continually improving. Based on those knowledge, future research opportunities include developing more effective strategies for consumer education, providing more scientific evidence for the health properties of PBMA, finding more suitable protein sources to improve the quality of the final products, improving the appearance and flavor, further examining and securing the chemical safety, exploring the structure formation mechanism during the extraction or shearing processes, and developing methods and standards for a quality evaluation of PBMA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".