Effect of mulch and water absorbent on morphological characters and membrane permeability of potato
Bibliographic record
Abstract
The effect of mulch and water absorbent on morphological characters,leaf membrane permeability and yield were studied using potato variety Kexin 1.Eight treatments were consisted,including control group(CK), control group-water absorbent junction(CKB),straw mulch(PF),straw mulch-water absorbent junction(PFB),film mulching on furrows(UPF),film mulching on furrows-water absorbent junction(UPB),film mulching beside furrows(SPF),film mulching beside furrows-water absorbent junction(SPFB).The results were concluded that plant height and plant fresh weight showed an increasing tendency with the growth duration.The plant height of CK and PFB were significantly higher than the other treatments(P0.01) at starch accumulation stage;Fresh weight of SPB and SPFB were significantly higher than others(P0.01),but the plant height and plant fresh weight of these two treatments were lower.The value of relative membrane permeability first reduced and then increased with the growth duration,and MDA content presented basically an increasing trend.The MDA content of UPF and UPFB were much higher.The yield of PF and PFB were significantly higher than others(P0.01),and the value of UPF and UPFB were lowest.The yield of PFB remained 169.65% more than UPF,and 214.20% more than UPFB.In all,straw mulch,film mulching beside furrows and film mulching beside furrows-water absorbent junction treatments produced more potato yield.
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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) | 0.001 | 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".