Growth and instability in area, production, productivity and export of cashew in India
Bibliographic record
Abstract
Cashew (Anacardium occidentale L.), an economically valuable plantation crop, contributes substantially to India’s foreign exchange earnings and rural livelihood. The crop is cultivated across 1.19 million hectares, with major producing states including Maharashtra, Andhra Pradesh, Odisha and Kerala. This study examined area, production, productivity and export of cashew from India. Using secondary time series data spanning from 2004-05 to 2023-24. For the HS Code 20081910(Roasted or Salted cashew). Compound Annual Growth Rate (CAGR) was used for the analysis to see the growth rate and for variance Coefficient of variation (CV), Cuddy-Della Vella Index and Coppock’s Instability Index. The Compound Annual Growth Rate (CAGR) method revealed that, the area under cashew cultivation in India increased significantly at 2.09% and production at 1.62% per annum, both statistically significant at 1% level. Export-wise, export quantity increased at 17.76% CAGR, while export value rose by 31.52% CAGR, both significant at the 1% level. Country wise analysis revealed that during the overall period of the study Malaysia showed the highest export growth, followed by the USA. In India, productivity showed the least instability (CV: 9.02%, CDVI: 3.15, CII: 11.26), while production was most volatile (CV: 10.55%, CDVI: 6.30). Export performance revealed extreme volatility, export value CV was 85.77% (CDVI: 29.6) and quantity CV 66.19% (CDVI: 34.81). Canada and Malaysia were the most unstable markets, with Canada’s export value CV at 197.91% and quantity CV at 175.94%. The USA, while a major importer, had moderate instability, and the UAE remained relatively stable.
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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 | 0.000 |
| 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) | 0.000 | 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".