Crop diversification and seed inoculation strategies effects on soil microbial community in soybean cropping systems
Bibliographic record
Abstract
Crop diversification has gained importance in Brazilian soybean (Glycine max L.) cropping systems, usually cultivated in soybean/2nd season maize (Zea mays L.) successions. Brachiaria grass (Urochloa spp.), a forage highly grown in Brazilian livestock systems, can be a suitable option for the soybean systems diversification. Brachiarias are well adapted to tropical conditions, produce high amounts of above and belowground biomass, have high nutrient cycling capacity, and release exudates known as biological nitrification inhibitors (BNI). All these traits might increase soybean yield and nutrient use efficiency in the agroecosystem.Brazilian cropping systems rely on plant growth-promoting bacteria (PGPB), like seed inoculation of soybean with the nitrogen-fixing bacteria Bradyrhizobium, alone or in combination with Azospirillum, to replace mineral N fertilizers.In this study, we aimed to investigate the soil bacterial community (activity and diversity) response to the diversification of soybean/maize cropping systems with Urochloa ruziziensis and inoculation with different combinations of PGPB. We hypothesize that inoculation with PGPB and diversification of the system with maize intercropped with Brachiaria will enhance microbial community activity and diversity.A 5-year experiment has been conducted in Londrina (Paraná State, Southern Brazil) in a randomized complete block design with a split-plot arrangement and six replicates. Main plots consisted of soybean during the cash crop season (S: soybean without inoculation; Si: soybean inoculated with Bradyrhizobium; Sc: soybean co-inoculated with Bradyrhizobium + Azospirillum). Sub-plots consisted of different diversification systems after the cash crop season (M: succession with maize; M+U: maize intercropped with U. ruziziensis; Mi+Ui: maize intercropped with U. ruziziensis, both inoculated with Azospirillum). After the soybean harvest in the 2021/2022 cropping season, soil samples were taken at the 0-10 cm soil layer. We analyzed soil enzymes (arylsulfatase, β-glucosidase, and acid phosphatase), environmental factors (soil pH and nutrients), and the 16S gene sequence.Preliminary results suggest an increase in the relative abundance of some bacterial phyla with Brachiaria. The phylum Proteobacteria, which harbors numerous PGPB, showed higher relative abundance in the cropping systems with Brachiaria, independently of the inoculation strategy in the summer soybeans. On the other hand, for the Nitrospirota phylum, which contains nitrite-oxidizing bacteria, higher relative abundance was observed in S/MiBi and Si/MiBi, compared with Sc/MiBi. Additional results on bacterial community diversity and composition and their relationship with microbial activity and environmental indicators will be discussed.This study provides novel insights into how crop diversification combined with PGPB affects the soil microbial community and nitrogen dynamics, supporting agricultural and soil management practices to achieve more sustainable production systems.
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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".