Taro (Colocasia esculenta)-An Important Staple Food for the General Population of Fiji Islands
Bibliographic record
Abstract
Taro production in Fiji is fluctuating in a yearly basis due to presence of devastating pests and diseases. Lack of knowledge in controlling these pests and diseases and the availability of controlling resources is another problem, which farmers in Fiji are currently facing. Taveuni being the largest supplier of taro in Fiji, is experiencing problems related to mono-cropping which in cooperates problems like soil degradation, unwanted weeds and minor pests and diseases. This research article mainly focuses on pests and diseases associated with taro production in Fiji and possible control measures to help farmers in Fiji to enhance their knowledge in controlling these pests and diseases. A thorough survey of taro farmers and exporting companies in Fiji was done to evaluate the problems that have directly or indirectly affected taro production in Fiji in previous years. As shown in figure 2, Fiji has experienced the shortages of taro in the year 2010, 2012 and 2014 as a result of increasing pest and diseases. This shortage not only has affected the demand from overseas market but also farmers in terms of earning for their livelihood. If these problems are not solved at an earliest, the taro industry in Fiji may collapse resulting in greater number of problems in future.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".