Evaluation of Cowpea (Vigna unguiculata L.walp) Genotypes for Biological Nitrogen Fixation in Maize-cowpea Crop Rotation
Bibliographic record
Abstract
Nitrogen is a major plant nutrient which is most limiting in the soil due to soil losses of mineral nitrogen (N) form. To ensure availability of nitrogen in the soil, the study was conducted to screen four cowpea genotypes for Biological Nitrogen Fixation (BNF) and their contribution to maize yield in maize- cowpea rotation. The cowpea genotypes used were mutants LT11-3-3-12 (LT) and BB14-16-2-2 (BB) and their parental varieties Lutembwe (LTPRT) and Bubebe (BBPRT) respectively. Trials were established at two sites (Chisamba and Batoka) of different soil types. The Randomized Complete Block Design (RCBD) with three replications was used. Labelled 15N urea was applied at 20kgNha-1 on the four cowpea genotypes during 2015/16 growing season. Cowpea plant parts were dried and milled for 15N isotopic analysis. The data collected included Nitrogen content and atom % 15N excess in the fixing cowpea genotypes and non-nitrogen fixing pearl millet to determine total nitrogen derived from the atmosphere (TNdfa) and total nitrogen (TN) in plant parts which were further used to compute Biological Nitrogen Fixation (BNF). The results showed that BNF by cowpea genotypes at Chisamba was 63.9 kg ha-1 and was significantly (P<0.001) more than BNF of 6.6 kgha-1 at Batoka. The LT mutant fixed significantly (P<0.001) higher nitrogen of 86.1 kgha-1 and 16.5kg ha-1 at Chisamba and Batoka respectively than other genotypes. However, both BB and LT mutants significantly fixed more nitrogen than their parents and have demonstrated to increase maize grain yields up-to 12 tha-1 in the maize – cowpea rotation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".