Breadfruit (Artocarpus altilis): Processing, nutritional quality, and food applications
Bibliographic record
Abstract
Breadfruit is an underutilized but highly nutritive crop containing complex carbohydrates while being low in fat. It is also a good source of essential amino acids (leucine, isoleucine, and valine). With a better understanding of breadfruit's morphology, its potential as a global solution to food security has been gaining popularity. Breadfruit has been forecasted to have a larger amount of suitable cultivable land area compared to major crops such as rice and wheat, making its cultivation more desirable. Due to its highly perishable nature, good post-harvesting and post-processing practices are essential to extend the shelf life of breadfruit for global transportation and consumption. This paper aims to provide a comprehensive review on various processing methods of flour and starch, nutritional significance and new food applications of this novel food staple. In this review, the effects of the different processing and post-processing methods of breadfruit flour and starch have been described, and the nutritional composition and application of breadfruit flour as an ingredient replacer in various food applications have been discussed. It is vital to understand the processing and post-processing methods of breadfruit flour to enhance its shelf-life, physicochemical and functional properties. Furthermore, a compilation of novel food applications has been done to promote its use in the food industry. In conclusion, breadfruit flour and starch are highly versatile for use in numerous food products with added health benefits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".