Impact of Water and Nutrient Supplementation on Yield of Prairie Plantings of Juneberry Amelanchier alnifolia Nutt., Cultivar and Windbreak Plantings
Bibliographic record
Abstract
Amelanchier alnifolia Nutt. (Juneberry, Saskatoon berry or Serviceberry) fruit historically played an important role as fresh or dried food and as a medicinal staple in the Mandan, Hidatsa, and Arikara Tribal Nations. Natural Juneberry stands were lost during the creation of Sakakawea Reservoir on the Fort Berthold Reservation. Reintroduction of the Juneberry is important to the tribal communities. Therefore, the impact of water and fertilizer supplementation was explored in two mature Juneberry cultivar (Honeywood, Martin, and Smokey) plantings and a seedling windbreak planting. Yield was examined in three consecutive years with three treatments: (1) natural conditions (control; no additional water or fertilizer); (2) irrigation during flowering and fruit ripening period (irrigated); and (3) fertilization plus irrigation during flowering and fruit ripening period (fertilized). Yield varied from 5 to 258 g/0.03 m−3 across locations, treatments, and years. There was no difference in yield across locations and treatments in year one. Yield was greater in the second year than first year, but not different across locations or treatments. The fertilized treatment showed increased yield in the third year in contrast to irrigated treatment across locations. New plantings can be established more economically using seedling material and the yield increased if watered and fertilized during fruit development.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".