Yield, Fruit Size, Red Color, and a Partial EconomicAnalysis for ‘Delicious’ and ‘Empire’ in the NC-140 1994 SystemsTrial in Virginia
Bibliographic record
Abstract
In 1990 an NC-140 Orchard Systems Trial, involving ‘Empire’ and ‘Delicious’, was established near Blacksburg, VA. The 10 orchard systems were combinations of several rootstocks and three training systems. Rootstocks used for Slender Spindle (SS) planted at 2460 trees/ha, included M.9EMLA, Mark, and Budagovsky 9 (B.9); Vertical Axe (VA) planted at 1502 trees/ha, included M.26EMLA, M.9EMLA, Mark, Ottawa 3 (O.3), and Polish 1 (P.1); Central Leader (CL) planted at 1111 trees/ha, included M.26EMLA and Mark. Annual crop value was estimated each year from fruit packout data based on size and color. Annual costs per ha were estimated for orchard establishment, pruning, grass mowing, and pest control. Annual costs were subtracted from annual crop value to perform a partial economic analysis for each orchard system in each year. Total costs for trees and materials for orchard establishment were $8,888/ha for CL, $ll,937/ha for VA, and $19,680/ha for SS. ‘Delicious’ fruit were highly colored in all systems, but fruit with >70% red color for ‘Empire’ was highest for VA/Mark and lowest for SS/M.9. The percentage of ‘Empire’ fresh fruit was highest for VA/Mark and CL/Mark and lowest for SS/M.9 and SS/B.9, but the percentage of ‘Delicious’ fresh fruit was not significantly influenced by orchard system. After 10 years, the net present value for ‘Empire’ was higher for VA/P.1 and VA/M.9 than for CL/Mark, SS/B.9 and SS/M.9. After 10 years the net present value for the 10 ‘Delicious’ systems did not differ at the 5% level of significance, but the net present value was more than $16,000/ha higher for VA/M.26 than for SS/B.9.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".