Factors affecting production of Chinese Chestnut in Xinxian County, Henan Province, China
Bibliographic record
Abstract
Chestnuts, Castanea mollissima Blume, are an important non-wood forest product in XinXian County, Henan Province, China. As part of an effort to improve capacity to reduce crop losses caused by insects and other damaging factors, a monitoring system was established in four orchards representing various ages, growing conditions and management practices. Monitoring consisted of periodic observations of the condition of chestnuts through a portion of the 2000 season on sample trees. Resulting data were summarized into life tables.The monitoring indicated that less than 50% of the chestnut burrs present on the trees in early July survived to harvest. Missing burrs were the highest cause of chestnut loss in three of the four orchards sampled. This may in part be the result of chestnut burrs aborting because of insect attack, spontaneous abortion or early maturation of chestnuts. Losses that could be directly attributed to insects ranged between 12.75 and 28.58%, caused mainly by several species of caterpillars that bore into chestnuts. Occurrence of "empty burrs" was roughly equal to insect damage levels in two orchards that did not receive a supplemental boron fertilizer treatment at the time of flowering.Based on monitoring data obtained during the 2000 growing season, opportunities to increase chestnut production in XinXian County include application of boron to increase nut set and development of an Integrated Pest Management (IPM) system with emphasis on management of lepidopterous borers. Key words: Chinese chestnut, Castanea mollissima, integrated pest management, life tables, insect pests, non-wood forest products
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".