Optimum Time for Harvesting Cassava Tubers to Reduce Losses Due to Cassava Brown Streak Disease in Northeastern DRC
Bibliographic record
Abstract
The present study aimed to determine the appropriate time to harvest cassava tuberous root which minimize the losses due to cassava brown streak disease (CBSD) in the region of Yangambi, DRC. To achieve the aim of the study, 38 cassava cultivars were evaluated in Yangambi INERA’s Research Center for CBSD in the roots at harvest time between 9 and 13 months after planting (MAP). All the 38 cultivars tested showed CBSD root necrosis symptoms. Foliar symptoms occurred on 37.6% of the evaluated cultivars while CBSD root necrosis varied significantly among cultivars (7.0% to 82.5%) depending on susceptibility and the age of plant. This indicates the differential response of the cultivars to CBSD infection. Whitefly population density decreased with age of cassava, it was of 3 whiteflies per plant (9 MAP) to 1 (10 MAP). We noticed that in older plants, whitefly population decreased from 1 at 11 MAP to none at 13 MAP. Although, some cultivars did not show CBSD symptoms up to 12 MAP, they were not necessarily less attractive to whitefly. Negative relationship (r = -0.08 and r = -0.25) has been found between whitefly number and foliar symptom severity or between whitefly and tuber necrosis severity. Beyond 12 MAP, CBSD necrosis (severity score 4) was present in the tubers of 3 cultivars (EUR/2011/0148, Yafelamonene and Ybi/2011/258). Our study shows that in order to mitigate the losses due to CBSD necrosis, the optimum harvesting time for cassava tubers in Yangambi is 9 MAP.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".