Forecasting Root Rot Disease through Predictive Microbial Functional Profiling
Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You +11 more
wiley +1 more source
Mapping the climate and agronomic digital advisory services landscape in West and Central Africa: A step towards making food systems productive and climate resilient. [PDF]
Singh M +7 more
europepmc +1 more source
Evaluating iSAT climate-informed agro-advisories for farm decisions and system performance in Senegal's drylands. [PDF]
Joseph JE +9 more
europepmc +1 more source
Assessing the Impact of Agricultural Information Utilization on Wheat Productivity of Smallholder Farmers: Evidence From Northwest Ethiopia. [PDF]
Shitaye Z, Tadesse B, Enkuahone K.
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Reply to Yang et al.: Synergies between photovoltaic development and innovative agricultural practices for combating desertification. [PDF]
Wang X +5 more
europepmc +1 more source
<i>Uvpks1</i>, Involved in Ustilaginoidin Biosynthesis, Contributes to the Metabolic Profile, Development, Stress Responses, and Pathogenicity in <i>Villosiclava virens</i>. [PDF]
Hou X +9 more
europepmc +1 more source
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