Precision agriculture and the farmers who adopt it
Precision and smart agriculture, plant disease detection and agricultural technology adoption appear on 148 recent papers, split between AI and economics; 47 of them carry an adoption, farmer, cost or income keyword. AI papers detect disease on leaves; economics papers study adoption of older technologies. Do the new tools reach farms, and do they raise income?
What prompted this#
Since October 2025, 148 papers carry a precision-agriculture, smart-agriculture, plant-disease, crop-yield, agricultural-technology or digital-agriculture keyword (90 in AI journals, 45 in economics): "precision agriculture" on 28, "smart agriculture" on 26, "plant disease detection" on 18, "agricultural technology adoption" on 11, "crop yield prediction" on 3. Forty-seven of them also carry an adoption, farmer, smallholder, economics, cost, profit, income, deployment, welfare or policy keyword, almost all in the economics journals.
Questions#
- Of the plant disease and yield models published in AI journals, which have been deployed in apps that farmers use, and does their field accuracy match the published accuracy?
- For smallholders, do app-based diagnoses change input use and yields, and does the benefit cover a smartphone and data?
- Do large farms' gains from precision application widen the gap with small farms, and do subsidies narrow it?
Data that could help#
Usage data from agricultural advisory apps, farm surveys with technology use and yields, and field validation studies of published models.
Next step#
Validate three published plant disease models on images collected by farmers in the field through an advisory app, and compare accuracy with the published figures.