Durum wheat: production, nutritional value and economic importance
Bibliographic record
Abstract
Durum wheat is the second most important crop of wheat and the tenth most important crop in the world, which includes about 6% of the area under wheat cultivation and its annual production is between 37-40 million tons. Countries with Mediterranean climates are the largest producers of durum wheat and the largest consumers of durum wheat products. Historically, durum wheat is well adapted to a dry area with variable precipitation rates and terminal heat stress, such as the Mediterranean basin. In fact, the countries of the Mediterranean basin (Algeria, Turkey, Italy, Morocco, Syria, Tunisia, France, Spain, and Greece) account for almost 50% of the world's cultivated area and production of durum wheat. Outside this basin, Canada, Mexico, the United States, Russia, Kazakhstan, Azerbaijan, and India are the largest producers of durum wheat, respectively. Durum wheat is genetically, morphologically, and physiologically different from bread wheat, and in terms of chemical compounds, its amount of protein, minerals, vitamins, and carotenoid pigments is higher than bread wheat. Durum wheat with hard vitreous and yellow grains, in addition to providing an important source of energy, possessing a wide range of minerals and vitamins, protein and gluten, beta-carotene pigment (antioxidants and anti-cancer compounds) as well as simple carbohydrates, minerals, and other nutrients compounds that are essential in the human diet. Durum wheat is one of the most important foods with a high percentage of protein (12-14% and sometimes up to 22%) compared to rice (7%) and bread wheat (10 to 12%). In durum wheat, the amount of calcium, iron, magnesium, phosphorus, potassium, zinc, and copper is much higher than the amount of these elements in bread wheat and brown and white rice. The high content of these elements in durum wheat grain indicates the importance of the nutritional value of this product compared to the mentioned products that provide a major part of the consumer's food basket. In addition to semolina, which is used in the preparation of paste products such as macaroni and spaghetti, lasagna, noodle, etc., durum wheat is used in the making of other products such as bulgur, couscous, freekeh, durum wheat bread, etc. In this review article, the aim is to study the geographical distribution and production of durum wheat in different regions of the world, to introduce the nutritional value of the products and their products and their preparation, as well as to study the economic value of this valuable product. Moreover, new-released durum wheat cultivars with appropriate agronomic characteristics will be introduced.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".