Effect of bentonite as a soil amendment on field water-holding capacity, and millet photosynthesis and grain quality
Bibliographic record
Abstract
Abstract A field experiment was conducted in a semi-arid region in northern China to evaluate the effects of bentonite soil amendment on field water-holding capacity, plant available water, and crop photosynthesis and grain quality parameters for millet [ Setaria italic (L.) Beauv.] production over a 5-year period. Treatments included six rates of bentonite amendments (0, 6, 12, 18, 24 and 30 Mg ha −1 ) applied only once in 2011. The application of bentonite significantly ( P < 0.05) increased field water-holding capacity and plant available water in the 0–40 cm layer. Bentonite also significantly ( P < 0.05) increased the emergence rate, above-ground dry matter accumulation (AGDM), net photosynthesis rate (Pr), transpiration rate (Tr), soil and plant analysis development (SPAD) and leaf water use efficiency (WUE). It also increased grain quality parameters including grain protein, fat and fiber content. Averaged over all the years, the optimum rate of bentonite was 24 Mg ha −1 for all plant growth and photosynthesis parameters except for grain quality where 18 Mg ha −1 bentonite had the greatest effect. This study suggests that bentonite application in semi-arid regions would have beneficial effects on crop growth and soil water-holding properties.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".