From Silicon Valley to Tanzania: Putting AI to work for smallholder farmers

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Journey into the field with Project Artemis, a new collaboration putting advanced phenotyping technology in the hands of breeders and smallholder farmers.

Our Land Cruiser plunges through thick dust, past goats picking at sparse weeds and Maasai herding cattle. The soil is cracked and dry, it has been over three months without rainfall.

Tourists know Arusha as Tanzania’s safari capital, a gateway to the Serengeti as well as the mountains Meru and Kilimanjaro. Our destination is in the shadow of Kilimanjaro; a patchwork of fields that farmers rely on for vegetables, fruit, and most importantly, beans – a valuable source of both dietary protein and income. But even with irrigation, the area is feeling the strain of climate change.

“This year because we didn’t have rains, the season has failed, the weather condition is very bad for every type of plant,”  says farmer Sembuli Mohamed Mkilaha.

Farmers are under increasing pressure, as weather becomes more extreme, pests and diseases more prevalent, and fertilizers more expensive (prices have more than doubled in the past year), to identify more resilient varieties of their staple crops. A bean variety that reaches maturity a few weeks earlier, is a bit hardier during a drought, tolerates pests and diseases, or produces a handful more pods per plant… this can be the difference between debt and hunger, or a well-fed and prosperous family. 

But how do farmers know which varieties are best suited to their fields? And how can crop breeders develop locally-adapted varieties to meet urgent, changing environmental conditions?

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