Addressing food insecurity: An exploration of wheat production expansion
Bibliographic record
Abstract
Wheat plays a crucial role in global food security, serving as a vital food crop that feeds billions of people worldwide. Currently, Russia and Ukraine are responsible for exporting approximately 25% of the world's wheat, making any issues in these regions a cause for concern regarding global wheat supply. The problems faced in these areas have led to a surge in wheat prices worldwide. Consequently, it becomes necessary to explore alternative regions that can compensate for the decline in wheat production and supply. This study focuses on wheat production and yield in major producing countries, utilizing the GYGA (Global Yield Gap Atlas) protocol for predictions. The findings reveal a global wheat production gap of 270,378,793 tons. Notably, the largest gap in irrigated wheat production exists in countries like China, India, Pakistan, Turkey, Iran, Afghanistan, Uzbekistan, Egypt, and Azerbaijan. Additionally, the rainfed wheat production gap on a global scale amounts to 545,215,692 tons, with Russia, the USA, Kazakhstan, Australia, Ukraine, China, Turkey, Canada, India, and France having the most significant production gaps. Through boundary line analysis, specific criteria were identified for suitable areas of irrigated and rainfed wheat cultivation. For irrigated conditions, the temperature range of 3000 to 7000 GDD (Growing Degree Days) and a temperature seasonality of 3 were determined as favorable. Under rainfed conditions, the suitable areas encompass a temperature range of 2000 to 4000 GDD, an aridity index exceeding 600, and a temperature seasonality of 2. Thirteen countries possess extensive agricultural land within the climatic codes favorable for irrigated wheat cultivation. Approximately 50% of the agricultural lands within these countries, corresponding to the total arable area for irrigated wheat, fall within the climatic codes 3403, 5403, 5303, 4303, 5503, 5203, 3503, 3303, and 4103. China, the United States, Ukraine, Russia, and Iran are the top five countries with favorable lands for irrigated wheat cultivation. Similarly, fourteen countries have significant agricultural lands within the favorable climatic codes for rainfed wheat cultivation. Around 52% of the agricultural lands within these countries are within the climatic codes 3702, 2702, 2802, and 4602. France, Germany, Britain, Poland, and Denmark possess the highest potential to expand rainfed wheat cultivation areas within these favorable climate codes, with respective areas of 2.7, 2.6, 1.6, and 0.9 million hectares. According to the study, the North China Plain emerges as a primary region for increasing irrigated wheat production, both in terms of cultivated area and yield potential. For rainfed conditions, the European continent stands out as a significant region to enhance wheat production.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".