Performance and Quality of Sweetpotato Cultivars Grown in Quebec, Canada with Biodegradable Plastic Mulch
Bibliographic record
Abstract
There is an increased interest in producing sweetpotato ( Ipomoea batatas ) in parts of eastern Canada, which are farther north and have fewer growing degree days (GDD) than traditional production regions in the southern United States. There is currently little information on cultivar selection for farmers in these northern regions. We evaluated yields and quality of 15 sweetpotato cultivars and selected lines grown with black plastic mulch but without pesticides. The best marketable yields (18–25 t·ha −1 ) in this trial were comparable to average marketable yields obtained in traditional sweetpotato-producing regions. Of the orange-fleshed cultivars and selected lines, Beauregard, B94-24, and Evangeline had high yields and warrant further testing. Covington, a common cultivar in North Carolina and Ontario, had poor yields in our conditions: it may require more GDD. ‘Porto Rico’ and ‘Ginseng Red’ had poor yields mainly because their storage roots were too small. The yellow-fleshed ‘Georgia Jet’ and GJ2010 had very vigorous vines and produced high yields, but had a high culling rate because of malformed or cracked storage roots. The white-fleshed ‘Murasaki-29’, ‘O’Henry’, and ‘Japanese’ also had high yields; whereas ‘White Travis’ and ‘Korean Purple’ had poor yields with small storage roots. Establishing the crop with rooted transplants instead of slips was satisfactory as long as the transplants were less than 4 weeks old. On the basis of our limited data, the following cultivars and selected lines may be suitable for Quebec, Canada: Beauregard, B94-24, Evangeline, Georgia Jet, GJ2010, and Murasaki-29. ‘Evangeline’ and ‘Covington’ had higher soluble solid contents than the other cultivars. High percent soluble solids may be desired by consumers. In spite of the absence of pesticides, very few pest or disease problems were observed except for some postharvest soft rot.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".