Coffee‐husk biochar application increased AMF root colonization, P accumulation, N<sub>2</sub>fixation, and yield of soybean grown in a tropical Nitisol, southwest Ethiopia
Bibliographic record
Abstract
Abstract Low soil fertility and soil acidity are among the major bottlenecks that limit agricultural productivity in the humid tropics. Soil management systems that enhance soil fertility and biological cycling of nutrients are crucial to sustain soil productivity. This study was, therefore, conducted to determine the effects of coffee‐husk biochar (0, 2.7, 5.4, and 16.2 g biochar kg−1soil), rhizobium inoculation (with and without), and P fertilizer application (0 and 9 mg P kg−1soil) on arbuscular mycorrhyzal fungi (AMF) root colonization, yield, P accumulation, and N2fixation of soybean [Glycine max(L.) Merrill cv. Clark 63‐K] grown in a tropical Nitisol in Ethiopia. ANOVA showed that integrated application of biochar and P fertilizer significantly improved soil chemical properties, P accumulation, and seed yield. Compared to the seed yield of the control (without inoculation, P, and biochar), inoculation, together with 9 and 16.2 g biochar kg−1soil gave more than two‐fold increment of seed yield and the highest total P accumulation (4.5 g plant−1). However, the highest AMF root colonization (80%) was obtained at 16.2 g biochar kg−1soil without P and declined with application of 9 mg P kg−1soil. The highest total N content (4.2 g plant−1) and N2fixed (4.6 g plant−1) were obtained with inoculation, 9 mg P kg−1, and 16.2 g biochar kg−1soil. However, the highest %N derived from the atmosphere (%Ndfa) (> 98%) did not significantly change between 5.4 and 16.2 g kg−1soil biochar treatments at each level of inoculation and P addition. The improved soil chemical properties, seed yield, P accumulation and N2fixation through combined use of biochar and P fertilizer suggest the importance of integrated use of biochar with P fertilizer to ensure that soybean crops are adequately supplied with P for nodulation and N2‐fixation in tropical acid soils for sustainable soybean production in the long term.
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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) | 0.000 | 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 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".