Design and experiment of a bionic vibratory subsoiler for banana fields in southern China
Bibliographic record
Abstract
Abstract: Subsoiling is essential in the tillage of banana planting, as banana plants have a fairly sturdy pseudostem and wide row spacing while soil tends to be compacted. In this study, a bionic vibrating subsoiler for banana fields was developed, verified, and evaluated. The vibrator was designed based on crank-rocker mechanism while the bionics design was used for subsoiler development. The forces on the susboiler were analyzed to verify the strength of the subsoiler tine. To test the performance of the subsoiler, field tests were conducted to measure the draft force and fuel consumption. There was approximately 14% reduction in the draft force and 22% increase in the fuel consumption in vibrating mode compared with that in non-vibrating mode. In conclusion, the study results could be applied in China’s tropical agricultural regions. Keywords: vibratory subsoiler, tillage, simulation, bionics, banana field DOI: 10.3965/j.ijabe.20160906.1923 Citation: Zhang X R, Wang C, Chen Z H, Zeng Z W. Design and experiment of a bionic vibratory subsoiler for banana fields in southern China. Int J Agric & Biol Eng, 2016; 9(6): 75－83.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".