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Rice provides 20% of the world’s food energy, with expected demand rising by 60% by 2050, but climate change, more extreme weather and evolving pathogens threaten farmers’ ability to produce enough of the crop. To help better predict crop yield — and how interventions may improve yield — an international research team has developed an approach that farmers may be able to implement using just a smartphone.
The demand for rice across the world has been projected to increase considerably by 2050, thereby needing viable intensification of present croplands.
The global demand for rice is projected to rise significantly by 2050, necessitating sustainable intensification of existing croplands. Now, Japanese researchers have made significant progress by developing deep-learning algorithms that can rapidly estimate rice yield through the analysis of thousands of photographs. The model exhibited high precision across diverse conditions and cultivars, surpassing previous methods, while effectively detecting yield differences between cultivars and also with different water management practices.