Lost rice found, again

First there was Carolina Gold. Now there is “upland red bearded” or “Moruga Hill” rice.

Mr. Dennis had heard about hill rice…through the culinary organization Slow Food USA and the Carolina Gold Rice Foundation, the group that brought back Carolina Gold in the early 2000s. He’d also heard stories about it from elderly cooks in his community. Like everyone else, he thought the hill rice of the African diaspora was lost forever.

But then, on a rainy morning in the Trinidad hills in December 2016, he walked past coconut trees and towering okra plants to the edge of a field with ripe stalks of rice, each grain covered in a reddish husk and sprouting spiky tufts.

“Here I am looking at this rice and I said: ‘Wow. Wait a minute. This is that rice that’s missing,’” he said.

It is hard to overstate how shocked the people who study rice were to learn that the long-lost American hill rice was alive and growing in the Caribbean. Horticulturists at the Smithsonian Institution want to grow it, rice geneticists at New York University are testing it and the United States Department of Agriculture is reviewing it. If all goes well, it may become a commercial crop in America, and a menu staple as diners develop a deeper appreciation for African-American food.

And no, they couldn’t have found it in genebanks. This is what Genesys knows from the region. Trinidad is shown by the yellow marker, rice accessions in red. No rice accessions in Genesys from anywhere near Trinidad, alas.

Someone should really have a systematic look at all those red dots, though.

Crowdsourcing genebank training needs

USDA-ARS and Colorado State University are organizing a workshop:

  • To identify the pedagogical options, logistics, and curriculum topics for a U.S. plant genetic resource management training effort, with major emphasis on a distance-learning course.
  • To design a strategy to develop, deliver, and sustain a plant genetic resource management training program.

They’re asking me for an “international perspective” on what genebank managers should be knowledgeable about, so I’m asking you. But don’t send me a laundry list (there are plenty of curriculums out there), or your favourite topic. What I’d like to know is what ONE topic you think has been neglected in teaching crop diversity conservation in the past, and is unlikely to be revived without a major effort.

All contributions will be gratefully acknowledged in my presentation, needless to say (and I’ll post evidence to that effect in due course).


Nibbles: MGIS, DOIs, Lost apples found, Row 7 Seeds, EBN, “Influential” seed people.

  • Banana people release new banana germplasm database, featuring DOIs.
  • Video explaining what DOIs are and why they’re cool.
  • Five apple varieties to get DOIs before it’s too late? Probably not.
  • “A seed company built by chefs and breeders striving to make ingredients taste better before they ever hit a plate.” Whatever next.
  • Occupy the food system.
  • Extension works. In a big way. With agronomy anyway. Think what it could do with seeds…

Spatial data everywhere, but is that enough?

Last week saw something of a Big Spatial Data blitz, and not just Kofi Annan’s Nature piece in which he pithily set out why data — both big and small — is important:

Data gaps undermine our ability to target resources, develop policies and track accountability. Without good data, we’re flying blind. If you can’t see it, you can’t solve it.

The occasion for the aphorism was a monumental study in the same journal on “Mapping child growth failure in Africa between 2000 and 2015,” which plotted various child heath and education variables over the entire African continent at the unbelievable resolution of 5×5 kilometres. Interestingly, other spatial data, this time on agricultural production and nutrient diversity (which we have blogged about), was used to explain patterns in child growth stunting. There was also a call in the correspondence section of Nature to “democratise” smallholders’ access to such data.

But that wasn’t all.

A study in the American Journal of Agricultural Economics on “Food Abundance and Violent Conflict in Africa” used a huge spatial dataset of population, agricultural production and conflict locations. It found that, contrary to expectation, “[a]lthough droughts can lead to violence, such as in urban areas; this was … not … the case for rural areas, where the majority of armed conflicts occurred where food crops were abundant.”

And, finally, there was “Winners and losers of national and global efforts to reconcile agricultural intensification and biodiversity conservation” in Global Change Biology. Unhelpfully titled, the more interesting finding of this study was that the “uneven spatial distribution of both yield gaps and [vertebrate] biodiversity provides opportunities for reconciling agricultural intensification and biodiversity conservation through spatially optimized intensification.”

Will all these pretty maps be used? Perhaps Lawrence Haddad said it best (not for the first time) in a tweet referring to the malnutrition study:

I’d add one thing. It’s probably too much to ask for “the powerful” to learn some GIS, but researchers could get better at helping them to bring together and explore disparate datasets such as these three in powerful, easy-to-use visualisations.

LATER: I forgot one: there’s also a new global dataset on evaporative stress index.

Spatial data everywhere

Looks like mapping is in the air. Hardly had I finished messing around with European trees maps that I ran across this random dump of Brazilian crop distribution data. The source is given as the Brazilian Institute of Geography and Statistics (IBGE), but I was not able to find the original maps there. I still wanted to do a mashup with Genesys, though, of course, which meant a little more messing around.

In the end, it turned out to be fairly easy, though not as easy as with those EUFGIS shapefiles. You have to hack the map off that first website as a screenshot, then add the JPG as an image layer in Google Earth and tweak the corners until it more or less fits on top of the borders of Brazil, which is the bit that takes time. Once you’re happy with the fit, you can download an appropriate KML file from Genesys and plonk it on top. Here’s the result for cassava (click on the image to see it better).

The green splodges mean cassava cultivation according to IBGE, and the red dots are cassava landrace accessions from Genesys. That would be a pretty good way to identify gross geographic gaps in ex situ holdings, but for the fact that, crucially, there’s no data from the national collection at Cenargen in Genesys. Yet. We’re working on it. Stay tuned.