What is she best known for?
The fields of study she is best known for:
Fatima Maria de Souza Moreira mainly focuses on Botany, Rhizobium, Rhizobia, Biodiversity and Ecology.
Her studies deal with areas such as Nitrogen fixation and Root nodule as well as Botany.
Her study in Nitrogen fixation is interdisciplinary in nature, drawing from both Taxonomy and Symbiosis.
In Rhizobium, she works on issues like Microbial inoculant, which are connected to Food science.
Her research investigates the connection between Rhizobia and topics such as Horticulture that intersect with problems in Heavy metals and Burkholderia fungorum.
Fatima Maria de Souza Moreira interconnects Old-growth forest, Land use, Soil ecology, Soil classification and Secondary forest in the investigation of issues within Biodiversity.
Her most cited work include:
- Changes in land use alter the structure of bacterial communities in Western Amazon soils. (251 citations)
- Biodiversity conservation in human-modified Amazonian forest landscapes (201 citations)
- Characterization of tropical tree rhizobia and description of Mesorhizobium plurifarium sp. nov (199 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Botany, Agronomy, Rhizobia, Nitrogen fixation and Horticulture.
Fatima Maria de Souza Moreira has included themes like Bradyrhizobium, Rhizobium, Root nodule, Bacteria and Symbiosis in her Botany study.
Her Rhizobium research integrates issues from Paenibacillus and Sinorhizobium.
Her studies in Agronomy integrate themes in fields like Inoculation, Soil quality and Oxisol.
Her Rhizobia research is multidisciplinary, incorporating perspectives in Randomized block design, Axenic, Legume and Rhizobacteria.
Her work focuses on many connections between Nitrogen fixation and other disciplines, such as Microbial inoculant, that overlap with her field of interest in Phaseolus.
She most often published in these fields:
- Botany (37.70%)
- Agronomy (30.37%)
- Rhizobia (26.18%)
What were the highlights of her more recent work (between 2018-2021)?
- Rhizobia (26.18%)
- Agronomy (30.37%)
- Bradyrhizobium (16.23%)
In recent papers she was focusing on the following fields of study:
Fatima Maria de Souza Moreira mostly deals with Rhizobia, Agronomy, Bradyrhizobium, Botany and Soil quality.
Her Rhizobia study combines topics in areas such as Phaseolus and Horticulture.
Her Agronomy research incorporates themes from Introduced species, Inoculation and Understory.
Fatima Maria de Souza Moreira has researched Bradyrhizobium in several fields, including Microbial inoculant, 16S ribosomal RNA and Root nodule.
Her research investigates the connection with Botany and areas like rpoB which intersect with concerns in Vigna.
In her study, Paenibacillus is strongly linked to Plant growth, which falls under the umbrella field of Rhizobium.
Between 2018 and 2021, her most popular works were:
- Critical mercury concentration in tropical soils: Impact on plants and soil biological attributes. (11 citations)
- Selected bacterial strains enhance phosphorus availability from biochar-based rock phosphate fertilizer (9 citations)
- Microbiological indicators of soil quality are related to greater coffee yield in the Brazilian Cerrado region (9 citations)
In her most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Paenibacillus, Agronomy, Genetic diversity, Bradyrhizobium and Rhizobia.
Her Paenibacillus study combines topics from a wide range of disciplines, such as Shoot, Horticulture, Rhizobium and Phosphate.
Her Horticulture research includes elements of Soil pH and Fertilizer, Phosphorite.
Her biological study spans a wide range of topics, including Inoculation, Cation-exchange capacity, Fluorescein diacetate hydrolysis and Soil functions.
She combines subjects such as Vigna, Botany and rpoB with her study of Bradyrhizobium.
Her Rhizobia research incorporates elements of Rhizoctonia solani, Rhizobacteria, Damping off, Phaseolus and Burkholderia fungorum.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
