- Genomics reveals new landscapes for crop improvement. Which are dominated by the looming presence of Mount Phenotyping.
- Where Have All the Crop Phenotypes Gone? Someone mention phenotyping?
- Smallholder agricultural commercialization for income growth and poverty alleviation in southern Africa: A review. On balance, it’s a good thing.
- Genetic diversity of yacon (Smallanthus sonchifolius (Poepp. & Endl.) H. Robinson) and its wild relatives as revealed by ISSR markers. Low diversity among the cultivated stuff, which is quite distinct from the wilds. All due to clonal propagation. No concrete recommendations apart from conserving all you can find. Pity.
- Molecular Genetic Diversity of Major Indian Rice Cultivars over Decadal Periods. Genetic diversity among high yielding varieties released in India went up between 1970 and 2010.
- Ten principles for a landscape approach to reconciling agriculture, conservation, and other competing land uses. Adapt, involve, multitask. And more, much more, from Mongbay.
- Uncertainty, ignorance and ambiguity in crop modelling for African agricultural adaptation. Be open about assumptions, communicate with and involve diverse stakeholders in appropriate ways, accept feedback from policy-makers. Could be talking about GMOs. Or the above.
- The effect of rising food prices on food consumption: systematic review with meta-regression. Worse for poorer countries, and worse for poorer households in all countries.
Root and tuber online mapping bags award
Congratulations to the GIS folks at CGIAR:
RTBMaps — a web-based GIS (Geographic Information Systems) tool to help planners visualize data and analyze options for using roots, tubers and bananas to improve food security, nutrition and income — has been selected for a Special Achievement in GIS (SAG) Award, presented today at the 2013 Esri International User Conference.
The thing is still in Beta, and there’s a lot more to come, both data and functionality:
RTBMaps is being launched with approximately 25 map layers, which are based on data for RTB crop distribution, indicators for poverty and food-security and some production constraints. However, the number of layers will grow as the GIS specialists at the research centers upload maps for additional pests and diseases, social indicators and other pertinent data. The RTB GIS team will also add applications for simple functions such as printing, or downloading maps for use in presentations. The team has also developed a priority setting application that allows users to weight the importance of different criteria — based on their own research, or consultations — and run analyses that result in unique maps.
Actually that priority-setting bit seems to be already there (more on this below). But for sure it will be nice to be able to share the results, which you can’t really do easily at the moment. And to import your own data, like localities of germplasm accessions, say. Which you also can’t do right now.
What can you do? Well, I couldn’t find much in the way of documentation, but playing around on the site suggests that basically what you can do is display those 25 layers in whatever combination you want on a map of the world. The layers include harvested area for potato, sweet potato, cassava, yam, banana and plantain, and a bunch of other variables: biotic (e.g. cassava mealybug climatic suitability), abiotic (e.g. length of growing period), socio-economic (e.g. % children underweight) and management (e.g. N fertilizer application). Each layer comes with a little pop-up which gives you the legend and lets you change its transparency, so that you could, for example, display cassava area together with climatic suitability for the cassava mealybug, and figure out where that pest is likely to do the most harm. You’d have to do that by eye, mind you, by tweaking the transparency settings. Tricky, and not hugely satisfying, but possible.
No, but wait. There’s a “Tools” tab: always a good sign. That allows you to run something called Multi-Criteria Decision Analysis, or MCDA. I think that’s the priority-setting application mentioned above. The way it works is that you choose a crop, then choose from a list of six criteria, and I quote: reduce poverty, food insecurity, nutrition and health, sustainability of natural resources, increase productivity and profit 1, and increase market conditions. So I chose cassava as my crop, and reducing poverty plus nutrition and health as my criteria. You then give a weight to each criterion, 50% each in my case.
Ok, so the next step is to choose indicators for each of your criteria. You’re presented with the same list of 12 indicators for each of the criteria, 2 the first six simply the harvested areas for all the crops in the system 3, the others the following, and again I quote: stunting among children under 5, poverty headcount at USD2 a day, absolute number of poors (sic.) at USD2 a day, irrigation areas, failed season, and accessibility. So I chose the poverty headcount as my indicator for reducing poverty, and stunting as my indicator for nutrition and health. If I had chosen more than one indicator for any of my criteria, I would have been able to give each a weight. But frankly, I was confused enough. Fortunately, I got a little reminder of what I’d done:
So I clicked on “Run analysis…”, though more in hope than expectation…
I am absolutely convinced that it is a huge technical achievement that the resulting analysis took only about 30 seconds. As my friend Glenn Hyman, one of the people involved, said in the press release already quoted above:
…RTBMaps is the most comprehensive and collaborative GIS web-mapping project to be undertaken within the CGIAR system to date. He noted that the cloud technology that it is based on has only become available in recent years.
I have no doubt all of that is true, and admirable. However, I also have to admit that I have little idea what the map produced by this cloud-technological, and most comprehensive and collaborative, web-mapping project actually means. Here is that map:
Let me hazard a guess. What I think the map may mean is that if your goal is to reduce poverty and improve nutrition and health, in equal measure, and you want to do this via cassava, the areas in red are…what? The places where you would have the best chance of succeeding? The places where you’re going to have the biggest impact? The places where you should go on holiday?
I should have gone to the workshop, I guess. Maybe if I had, I’d be able to understand the whole thing more, and explain it better. And it is still in Beta, so there’s stuff in the pipeline, including documentation, no doubt. The idea of providing diverse maps online, and allowing users to combine them in fancy ways in support of decision-making, is certainly a great one. I really hope to see the promise of RTBMaps fulfilled.
Nibbles: Brazil nut, PVP, Dog evolution, Plant Treaty in India, Kerala veggies, Rust tracking latest, Adapt or die, Quinoa latest, NZ seed exchange, African soybeans, Ancient aquaculture
- The Brazil nut needs its pollinators.
- How USDA protects plant varieties.
- American dogs are Asian, not European.
IndiaNepal working out how to implement the ITPGRFA.- Kerala’s vegetable terrace gardeners.
- Haven’t heard much about Ug99 lately, have we? Doesn’t mean people aren’t keeping a careful eye on it.
- Climate change 10,000 times faster than vertebrate evolution.
- Why quinoa is not “taking over the world.”
- Not even New Zealand. Though not for want of trying.
- In the meantime, soybeans taking over Africa?
- Aquaculture that’s sustainable and ancient. Includes taro fish ponds, which for some reason seem to me cool beyond measure.
Nibbles: Bahamian pigs, Llamas far from home, Ugandan aquaponics, Better broccoli, African atlas, Chinese sesame imports, Root & tuber maps, NZ genebank access
- The next big livestock thing is swimming pigs.
- Or maybe llamas. Not swimming ones, mind, settle down.
- Nope, it’s farmed fish. Which do swim, though not very far.
- Meanwhile, Cornell re-engineers broccoli.
- And HarvestChoice puts out an African atlas. Online resources coming in due course.
- Which does not show you sesame cultivation in Ethiopia, alas, at least not yet, let’s wait for the online version.
- Speaking of atlases, RTBMaps is in Beta. I’ll have to play with it and get back to you.
- New Zealand changes genebank rules to speed up forage breeding. To do with quarantine rather than ABS, though.
Brainfood: Leafy greens, Korean rice, Molecular breeding, Poultry conservation, Tree genomes, Pathogen genetics, Grazers and CC, Sustainable rangelands, Available land, Ecosystem services
- Analysis of urban consumers’ willingness to pay a premium for African Leafy Vegetables (ALVs) in Kenya: a case of Eldoret Town. An 80% premium! But in Eldoret. And Nairobi?
- Analysis and comparison of the γ-oryzanol content based on phylogenetic groups in Korean landraces of rice (Oryza sativa L.). Some groups are browner than others.
- What is the SMARTest way to breed plants and increase agrobiodiversity? Just another name for MAS. But some crops are SMARTer than others.
- Conservation of local Turkish and Italian chicken breeds: a case study. Turks can learn from Italians. And probably vice versa, I bet, although that’s not explored as much here.
- Open access to tree genomes: the path to a better forest. Hard to argue with. The open access bit more than the genomes bit.
- Evolution, selection and isolation: a genomic view of speciation in fungal plant pathogens. Know your enemy. Easier to figure out how new species become different than how they stay that way.
- Long-Term Climate Sensitivity of Grazer Performance: A Cross-Site Study. Hotter conditions means poorer forage quality means smaller bison. And maybe cattle. All other things being equal, like genetics, and range management. Which of course they never are.
- Ecosystem function enhanced by combining four functional types of plant species in intensively managed grassland mixtures: a 3-year continental-scale field experiment. See what I mean? And more.
- Estimating the world’s potentially available cropland using a bottom-up approach. Less than you’d think.
- Spatial interactions among ecosystem services in an urbanizing agricultural watershed. Very very limited places provide multiple services, especially crop production and water quality, which means you need to protect huge areas. But they’ll be mosaics.

