Science losing its way: examples from the realm of microbial N2-fixation in cereals and other non-legumes
K.E. Giller; Euan K. James; Julie Ardley; M. Unkovich · 2024 · Plant and Soil
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract Background Despite more than 50 years of research, no robust evidence suggests that inoculation of cereals and other non-legumes with free-living and/or endophytic bacteria leads to fixation of agronomically significant quantities of dinitrogen gas (N 2 ) from the atmosphere. A plethora of new products claims to increase the growth and yields of major cereals and other crops through stimulating N 2 -fixation by inoculating with bacteria. Scope We review the literature on N 2 -fixation by bacteria in the rhizosphere and as endophytes in non-legume plants. We find no unequivocal evidenc
Abstract by K.E. Giller; Euan K. James; Julie Ardley; M. Unkovich, Plant and Soil (2024) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Catastrophic Natural Disasters and Economic Growth
Negative / Null Result ReportBrain anomalies in children exposed prenatally to a common organophosphate pesticide
Negative / Null Result ReportPhylogenomic Insights into the Evolution of Stinging Wasps and the Origins of Ants and Bees
Negative / Null Result ReportSpecies Richness and the Temporal Stability of Biomass Production: A New Analysis of Recent Biodiversity Experiments
Negative / Null Result ReportNew Insight into the History of Domesticated Apple: Secondary Contribution of the European Wild Apple to the Genome of Cultivated Varieties
Negative / Null Result ReportIncreasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1007/s11104-024-07001-1
