Effect of cropping sequences on soil biological activity in semiarid region of western Canada
Bibliographic record
Abstract
Soil productivity and environmental sustainability hinge on the physical, chemical and biological properties of the soil. Soil dehydrogenases (DHs) are one of the major classes of intracellular oxidoreductase enzymes involved in energy metabolism of living cells. The soil DHs activity is used as an indicator of overall soil microbial activity. This study employed the soil DHs assay to examine the effect of different cropping sequences including wheat, mustard and pulse crops in 4-year rotation on the soil biological activity. The DHs assay used in this study was originally developed by Le Casida et al. (1964). In this method, triphenyltetrazolium chloride (TTC) is used as an indicator dye that helps to observe electron transport system activity. The DHs involved in electron transport system reduce the colourless soluble TTC (substrate) and convert it into an insoluble red colour product, known as triphenylformazan (TPF). TPF can be quantified by spectrophotometry at the visible wavelength of 485 nm. Higher the intensity of the red colour in the soil extract solution, higher is the concentration of TPF and hence the higher DHs activity. In this study, the results of DHs assay of the final year (2014) of different 4-year crop rotations are presented. The study clearly showed that frequent inclusion of pulse crops especially chickpea in the cropping systems is conducive to the soil biological activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".