Canopy Structure Influence the Critical Period for Weed Removal of Three Cassava (Manihot esculenta Crantz) Varieties in Zambia
Bibliographic record
Abstract
Cassava (Manihot esculenta Crantz) is an important crop for food, feed and income security. Cassava productivity is limited by poor weed management. Field trials were conducted in Zambia to determine the Critical Period for Weed Removal (CPWR) on 3 cassava varieties (Chila, Mweru and Nalumino), with contrasting canopy structure, using a split-plot design in randomized blocks. Nine weeding treatments, i.e., control, 21, 42, 63, 84, 105, 126, 147, 168 days after planting (DAP), were applied on two sets of weeding regimes. In one set, weeds were allowed to grow followed by a weed free period while in the second, plots were kept weed-free followed by a period of natural weed infestation at Kabangwe and Kaoma. Cassava varietal means were in the order Chila (10,199 kg ha-1) > Nalumino (9,047.6 kg ha-1) > Mweru (8,429 kg ha-1). Chila, a branching cassava variety, significantly out-yielded (P < 0.05) other varieties. Fresh cassava root yields were higher at Kabangwe (23,270 kg ha-1) compared to Kaoma (21,347 kg ha-1). The CPWR was determined to be 60 DAP (48-73 DAP), at both sites. Yield differences among weeding treatment ranged between 18% and 75%. The determined CPWR is a determinant of weed management strategy for branching cassava varieties. The branching canopy architecture smothered weeds and hence is considered an important cassava varietal attribute. The yields in the current study are doubled the regional yield average of 8000 kg ha-1 and four times the Zambian average of 5000 kg ha-1.
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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 | 0.000 |
| 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 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".