An assessment of land for commercial apple orchard potential on CLI class 4 and 5 soils in the Nanaimo B.C. area - a case study
Bibliographic record
Abstract
It is generally accepted in British Columbia that Canada Land Inventory Class 1 to 4 lands are arable, yet in many instances commercial farms exist on lands of lower capability. A case study was done for an area (1.6 km * 2.9 km) southeast of Nanaimo, B.C. to determine if Canada Land Inventory Class 4 and 5 soils are biophysically suitable for Pyrus (pear) and Mai us (apple) orchards, and if such a development would be socioeconomically feasible. The critical biophysical conditions governing orchard development identified were climate (freeze free period, effective growing degree days, dormancy period and minimum winter temperature); soils (depth, drainage, texture/% coarse fragment content and topography); and groundwater availability for irrigation. The critical economic conditions were land tenure (Tree Farms and parcel size); current land use; and fruit yields and prices. While all biophysical conditions were favourable to apple orchards, the soils were found to be too coarse textured for pear orchards. Maps outlining the critical biophysical and socioeconomic conditions were prepared and overlayed. The composite map identified one area with realistic development potential for apple orchards. Although soils, land tenure, parcel size and current land use decreased the area available for orchards, the lack of groundwater for irrigation was found to be the most limiting factor to orchard development. Estimates of costs and returns for a 3.3 ha apple orchard over a 25 year period were done. Using these estimates, the net present value of the orchard was determined for three discount rates: 5%, 8% and 10%; and for five prices per kilogram: $0.15, $0.22, $0.33, $0.44 and $0.66. At prices of $0.15, $0.22, $0.33 and $0.44 (at discount rates of 10% and 8%), orchard establishment was not feasible. However, at prices of $0.44 (and discount rate of 5%) and $0.66, orchard establishment was feasible.
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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 | 0.001 | 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) | 0.002 | 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".