ANALYSIS OF GLOBAL CHICKPEAS TRADE: PROSPECTS FOR UKRAINIAN AGRIBUSINESS IN THE CONTEXT OF PRODUCTION AND EXPORT OF NICHE CROPS
Bibliographic record
Abstract
The article examines trends in global production and trade of chickpeas, analyzes the dynamics of Ukraine's export-import operations in this segment, and outlines the prospects for increasing the export of culture by domestic agribusiness. It is noted that over the past decade, the world market of chickpeas has been characterized by a tendency to increase its capacity due to the growth in demand for the crop, caused by the spread of various types of vegetarianism, concepts of healthy nutrition, the development of the chickpea protein market, etc. The dynamics and structure of global chickpea production by country as of 2022 were analyzed. It was found that the top five importers of chickpeas are Pakistan, Bangladesh, the United Arab Emirates, Turkey and India. Ukraine ranks 24th in the world ranking of chickpea exporters. It was noted that among all leguminous crops, chickpea production was the most affected by the war in Ukraine, as it is grown mainly in Odesa, Kharkiv and Kirovohrad regions. In 2022, the volume of crop supply to foreign markets was almost 5 times smaller compared to the previous period. It was revealed that the main buyers of Ukrainian chickpeas are Turkey, Saudi Arabia and Israel, in 2022 more than half (52.4%) of all exports were sold to these countries. It was established that the countries of the European Union import an average of 150,000 tons of chickpeas annually, mainly from Mexico, Turkey, Canada, Argentina and the USA. Attention is focused on the forecast of the global chickpea market capacity. It is noted that the dynamics of growth in the capacity of the world and European market of chickpeas, in particular, creates prospects for foreign trade in crops for Ukrainian agricultural producers, which is important from the standpoint of niche diversification of agribusiness.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".