Nibbles: Switchgrass mixtures, Groundnut genomes, Bean genome, New wild tomato, CC Down Under, Aussie foods, Natural history collections, Wheat genebanks, Pompeii vineyards, Colombian exhibition, Portuguese collard, Istanbul bostan, Kenyan adaptation, Norwegian adaptation, Hybrid wheat, GMO bananas, Indian organic, Coconut generator

The hipster future of coffee starts with a genebank

I started a post a few days ago with a quote suggesting that all that commercial farmers are interested in is yield. So let’s balance that today with this:

Geisha in undoubtedly a luxury, but in one important way, it deserves the hype. It is the first coffee to be grown commercially just because it tastes good.

coffee 002We blogged about the journey of the remarkable coffee landrace called Geisha (or Gesha) a few years ago: from Ethiopia’s forests to the CATIE genebank in Costa Rica to the Peterson family farm in Panama to all over the world, or, more specifically, a hipster coffee shop in Taiwan. But Hanna Neuschwander‘s Coffee in the New Millennium tells the story at much greater length, not to mention with much greater skill. For example, I wish I had thought to describe hillside coffee plantations, with their neat, undulating rows of bushes, as “living corduroy.”

The piece ends with a neat juxtaposition between World Coffee Research’s monumental International Multi-location Variety Trials and the more geographically focussed, but no less ambitious, in its own way, effort by the Peterson family. They’re looking for a new Geisha among hundreds of other Ethiopian landraces they are now testing on their Panamanian farm. I only have one bone to pick with Ms Neuschwander: why not fully acknowledge the role of the genebank at CATIE in all this, rather than just referring, anonymously, to “a research facility in Costa Rica”?

Nibbles: Poleward migration, Pulse infographic, Vodka, Ancient horse DNA, Old fish, Certified cacao, On farm book, Coarse millets, Banana diversity, Pearl millet demo

Tweeting crops

Jack Grieve is a computational linguist at Aston University in Birmingham, England. I came across him on Twitter, where he occasionally posts fun maps showing the geographic distributions (usually within the USA) of different words, usually dialectical variants, based on their appearance in geocoded tweets. He very kindly ran a couple of crop names through his magic box for us, and this is what he got. I wanted to know if the distribution of crops could be inferred from where people tweet about it more than the average. I’ve placed his map for each crop side by side with the relevant distribution map from USDA.

crops in USA

Not a perfect match by any means, but not too bad. Except for cotton, that is. Any ideas why people should be tweeting so much about cotton in the northern Great Plains? They’re certainly not growing it.

Jack’s dataset apparently only covers the US and the UK at the moment, which means I can’t check whether Kenyans, say, are tweeting about maize particularly assiduously where they’re growing it, or indeed about maize lethal necrosis where they’re worried about it. Google famously tried to predict flu outbreaks from search patterns, but that seems to have fizzled out. Could tweeting trends help pinpoint crops (or livestock?) and their pests and diseases in space and time? I don’t see much of that kind of thing in the discussion of ICTs in agriculture.