Yield of Cowpea Genotypes Inoculated With Bradyrhizobium and Azospirillum brasilense in Association With Phosphate Fertilization in Amazonian Soil
Bibliographic record
Abstract
The use of inoculants containing N2-fixing bacteria increases every year in cowpea crop in the North and Northeast regions of Brazil. In this context, this study aimed to evaluate the effects of inoculation with Bradyrhizobium sp. and Azospirillum brasilense in association with phosphate fertilization on the vegetative development, nodulation and yield of cowpea genotypes grown in Southern Rondônia state, Brazil. The experiment was conducted from February to May 2018, in the municipality of Colorado do Oeste, RO. The experimental design was randomized blocks in 4 × 3 × 2 factorial scheme, corresponding to four dose of phosphorus (0, 80, 120 and 160 kg ha-1 of P2O5); absence, inoculation and co-inoculation with rhizobacteria; two cowpea genotypes (White and Butter), with three replicates. Cowpea seeds were inoculated with the commercial inoculant TotalNitro Cowpea with strains of Bradyrhizobium sp. (Semia 6462 and Semia 6463); co-inoculation was performed using the commercial product, containing a combination of strains of Azospirillum brasilense, both in liquid formulation. Co-inoculation (Bradyrhizobium sp.+ Azospirillum brasilense) did not influence the production components of cowpea plants. Inoculation with Bradyrhizobium sp. associated with phosphate fertilization of 120 kg ha-1 of P2O5 was sufficient to promote maximum growth and development of cowpea plants in Amazonian soil. The genotype White had higher capacity of nodulation, dry matter production and grain yield. Inoculation of Bradyrhizobium sp. increased N and P contents in the leaves. The genotype Butter was superior to the genotype White with respect to the accumulation of P, K, Ca and Mg in the leaves.
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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) | 0.001 | 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".