Taming the wild: domesticating untapped northern fruit tree and shrub resources in the era of high-throughput technologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract New crop`s need to emerge to provide sustainable solutions to climate change and increasing abiotic and biotic constraints on agriculture. A large breadth of northern fruit trees and shrubs exhibit a high potential for domestication; however, obstacles to implementing traditional breeding methods have hampered or dissuaded efforts for improvement. This review article proposes a unique roadmap for de novo domestication of northern fruit crops, with a focus on biotechnological (e.g. genome editing, rapid cycle breeding, and in planta transformation) approaches that can boast rapid evolutionary gains. In addition, numerous biotechnological (e.g. virus-induced flowering and grafting-mediated flowering) and breeding strategies (e.g. adaptation of speed breeding to fruit trees) that can hasten the transition from juvenility to sexual maturity are described. A description of an accelerated genetic breeding strategy with insights for 16 underutilized species (e.g. shagbark hickory, running serviceberry, horse chestnut, and black walnut) is provided to support their enhancement. Deemed unrealistic only a decade ago, progress in the realm of bioengineering heralds a future for northern orphan crops through the implementation of fast-tracked crop improvement programs. As such, the roadmap presented in this article paves the way to integrating these novel biotechnological discoveries and propel the development of these forgotten crops in a sustainable and timely manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it