Impact of long-term fertilization on soil organic carbon dynamics and biological health of soils under Pearl millet -mustard-cowpea cropping sequence in an inceptisol of Gujarat
Bibliographic record
Abstract
The study was undertaken by utilizing an ongoing long-term experiment on continuous cropping at Anand Agricultural University that began in 1980. From 1994 onwards, a modification was made by including Farmyard Manure (FYM) treatments for studying the following objectives: long-term effect of fertility levels with and without FYM on changes in soil organic carbon pools for assessing the role of organics and chemical fertilizers on soil organic carbon buildup and their interrelationship with soil aggregate stability under the pearl millet-mustard-cowpea (F) cropping sequence. Under F1 (FYM @ 10 t/ha) and FL3 (NP application @150 percent of RDF), there was a considerable improvement in the status of Walkley and Black C (WBC), Soil Microbial Biomass Carbon (SMBC), and Total Organic Carbon (TOC) compared to the control in both depths (0-15 and 15-30 cm). Long-term manuring and fertilization practices affect aggregate development and stabilization. In all depths, the highest soil macroaggregates and microaggregates were found when FYM @ 10 t/ha and FL3 (150 percent NP) were applied. Under FYM treated plots and with the greater dose of NP (NP application @150 percent of RDF) in both the surface and sub-surface layers, the maximum water-stable aggregate expressed as mean weight diameter (MWD) was recorded. Furthermore, a significantly positive correlation was observed between SMBC and enzymatic activities (phosphatase, urease, and dehydrogenase) in both the soil depths; indicating the effect of labile C on the biological activities of soil which might be achieved by means of changes in microbial diversity of the soil.
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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 | 0.000 | 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) | 0.000 | 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".