Biological N2-fixation and grain yield of pigeon pea: The role of biochar and conservation agriculture in low-input systems
Bibliographic record
Abstract
Biological N 2 -fixation by legumes such as pigeon pea is a potentially important nitrogen input and a pathway for replenishing soil nitrogen (N) in maize dominant cropping systems. Biochar has been reported to affect N cycling, yet there are no studies on the synergism of conservation agriculture (CA) and biochar amendments on biological N 2 -fixation of pigeon pea in low input systems of sub-Saharan Africa. The objective of this study was to investigate the effect of biochar amendments under CA systems on biological N 2 -fixation, as these practices are promising sustainable intensification options in SSA. Specifically, we explored the effects of pigeon pea rotation and biochar amendments under CA on (1) biological N 2 -fixation, and (2) pigeon pea grain yield at three sites located in different agro-ecological regions of Uganda. We hypothesized that application of biochar under CA leads to greater biological N 2 -fixation and grain yield, than CA alone or conventional tillage. We set up three on-station experiments; one in Central Uganda (Mubende district), and two in Northern Uganda (Alebtong and Gulu districts) for two seasons. CA involved minimum tillage with planting basins established by hand hoeing. We investigated four treatments (1) conventional tillage with crop rotation (Conventional), (2) minimum tillage with crop rotation (CA), (3) CA and 2 Mg ha −1 of biochar, applied in both first and second year (CA+BC+BC), and (4) CA and 4 Mg ha −1 of biochar, applied once in the first year (CA+BC). Biological N 2 -fixation was high in Gulu, compared to Alebtong and Mubende; and this was mainly related to low soil N and greater percent of N derived from the atmosphere (%Ndfa), compared to other sites. Treatment effect on biological N 2 -fixation was variable across seasons, biochar application in CA systems did not affect biological N 2 -fixation in 2022 in Alebtong and Mubende. In 2023, biochar amendments in CA systems significantly increased biological N 2 -fixation in all sites. Grain yield was significantly increased by biochar application in CA systems compared to conventional practices, in all seasons and sites. A single dose application or split application of 4 Mg ha −1 biochar had similar effects on biological N 2 -fixation and grain yield. Biological N 2 -fixation was positively influenced by biochar application under CA systems. The additional N input associated with biological N 2 -fixation was up to 106 kg N ha −1 in Gulu and it significantly increased grain yield. There were no differences between once off application of 4 Mg ha −1 of biochar or applying 2 Mg ha −1 in the first year followed by 2 Mg ha −1 in the second year. • Combined effect of conservation agriculture (CA) and biochar on biological N 2 -fixation of pigeon pea in low input systems is not well understood. • Biological N 2 -fixation was variable across sites. • Biochar and CA enhanced biological N 2 -fixation and grain yield of pigeon pea. • Both single dose and split application of 4 Mg ha −1 biochar under CA had comparable results on biological N 2 -fixation and grain yield. • Biological N 2 -fixation was negatively correlated with soil N.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".