ORGANIC VEGETABLE CULTURE IN MISSISSIPPI: GROWING AND PROFITABLE
Bibliographic record
Abstract
Yield and economics of vegetable crops are being evaluated in non-adjacent organic (OG) and nonorganic (NOG) vegetable production field areas in Crystal Springs, Mississippi. Each production area has six sections in which crops are rotated over several seasons and years. Production techniques and management are as similar in timing and methodology as possible between the systems without compromising either system. Production methods, timing, and costs are recorded for each operation. These are combined with yield data to create budgets and estimated returns for each production system/crop combination. When possible, harvested produce is marketed by a cooperating grower-retailer at a local mid- to up-scale farmers market. Three years into the study, positive returns have been found for several crops including potato ( Solanum tuberosum L.), lettuce ( Latuca sativa L.), summer squash ( Cucurbita pepo L.), cucumber ( Cucumis sativa L.), and others. Marketable new potato yields in 2005 were under 10,000 lb/acre for Yukon Gold and Red Lasoda in either production system. Estimated net returns, based on an actual $2.00/lb market price, were positive for all system/cultivar combinations although final budget numbers are not firm. Significant differences in yield among cultivars were seen in potato, lettuce, summer squash, and cucumber. Organic production budgets for other crops in the study are also being developed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".