Bibliographic record
Abstract
In the contemporary age, there is an increasing inclination toward embracing a healthy way of life and selecting highly nourishing food options. Pseudocereals like quinoa, amaranth, and buckwheat have attracted considerable interest because of their abundant nutritional content and their ability to thrive in varying climates. Despite being nutritionally superior, pseudocereals are not fully utilized, prompting the exploration of latest biotechnological methods for enhancing crop development and adapting them to cultivation. The aim of the chapter is to comprehensively explore the nutritional intricacies of pseudocereals, address challenges hindering their integration into the broader nutraceutical landscape and highlight their potential contributions to future agricultural practices and the food industry. This chapter synthesizes information from recent research articles and reviews on the nutritional and agricultural potential of pseudocereals. It includes findings from studies on the adaptability, nutritional composition, health benefits, functional food applications, and agricultural resilience of pseudocereals. The chapter also discusses the need for biotechnological interventions to enhance crop improvement and domestication. Grains are rich in essential minerals, fiber, proteins, starch, vitamins, and phytochemicals that promote health. They offer superior nutritional benefits compared to traditional cereals and have diverse health-promoting properties, making them valuable for functional food production and addressing global health concerns such as celiac disease and hidden hunger. Additionally, pseudocereals exhibit resilience to abiotic stresses and have the potential to contribute to environmental sustainability. The chapter highlights the potential of pseudocereals as nutritional powerhouses, climate-resilient crops, and eco-friendly choices for future agricultural practices and the food industry. It emphasizes the need for biotechnological interventions to further enhance the nutritional and agricultural potential of pseudocereals and to overcome current challenges hindering their widespread adoption.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.077 | 0.007 |
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; both teacher heads agree on what is shown here.
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".