A Modified Soil Fertility Assessment Method Using Earthworm Density and Microbial Biomass C at Various Land Uses in Wonogiri, Indonesia
Bibliographic record
Abstract
Soil fertility is the integrative effect of chemical, physical, and biological soil properties.A modified soil fertility assessment method that adds biological indicators is essential since this indicator is sensitive to dynamic environmental changes and can better represent the reality of soil fertility compared to the conventional method, which only considers chemical soil properties.The research aims to compare the modified and conventional methods in assessing the soil fertility index at various land uses, namely gardens, paddy fields, and moorland, in the Girimarto district, Wonogiri, Indonesia.The collection of soil samples used purposive sampling with three repetitions on 12 land mapping units (LMUs) obtained from an overlay of land use maps, soil type maps, slope gradient maps, and rainfall maps.Soil fertility index (SFI) assessment is based on the Minimum Soil Fertility Indicators (MSFI), which are selected from Pearson correlation, PCA, weight, and score and followed by stepwise regression analysis.The research showed that the modified method represents the soil fertility level better than the conventional one.The soil fertility index on three land uses using the modified method is lower than the conventional method, i.e., between 0.33 to 0.40 and 0.55 to 0.72, respectively.The modified method is more sensitive to dynamic environmental changes due to the contribution of soil biological indicators to the SFI value.Therefore, the biological indicators can represent soil fertility levels closer to reality.Future research needs to validate the modified method in different soil types, land uses, and areas.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".