Deep Learning for Early Blight Detection in Potato: Where Field Images Break Laboratory-Trained Models
DOI:
https://doi.org/10.5281/zenodo.22664408Keywords:
Deep Learning for Early Blight Detection in Potato; Agro-informatics; Precision agriculture; Evidence synthesis; On-farm technologyAbstract
Deep Learning for Early Blight Detection in Potato has moved quickly from a research idea to something a working farm can
actually use, but the evidence behind it has not always kept pace. We pull together the current evidence for deep learning for early
blight detection in potato, covering the methodological, practical, governance and cost angles, with an eye on where practice has
genuinely settled and where farms and advisors are still largely working it out for themselves. Selective, context-specific adoption
looks better supported by the evidence gathered here than either broad rollout or blanket avoidance
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