- Another genebank in Australia. Unclear how it relates to the existing ones.
- Ghana’s genebank in funding trouble.
- How to run a community seed bank, according to the Bureau of Indian Standards. Apparently includes things like its relationship with other genebanks and funding.
- How to change legislation in Kenya to be more supportive of genebanks.
- Why we need genebanks in the first place.
- Otherwise decent podcast on the potato manages not to mention genebanks.
- Otherwise decent article on ube (Dioscorea alata) manages not to mention genebanks.
- Otherwise excellent dissection of the strawberry manages not to mention genebanks.
Himalayan maize: The saga continues
I decided to dig a little deeper into the climatic adaptation of Himalayan maize. You may remember from my last post on this that Genesys has 96 maize accessions from over 2000 masl in the Himalayas, collected at some 50-odd unique localities. When I ran these accessions through the Subsetting Tool in Genesys, I got the following histogram.
What struck me — and surprised me — was the spike of sites way at the left hand of the precipitation plot. So I took a closer look at the results of the subsetting analysis. And the clustering algorithm it uses to look for similar sites did in fact identify two climatically quite different groups of locations: 45 of the unique high altitude maize collecting sites (the blue ones) are indeed drier than the other 7 (in orange).
Much drier. (And also colder actually, but that’s another story.)
They’re the ones mainly collected in Pakistan and Afghanistan.
Now, I don’t know whether these areas really get 135 mm of annual precipitation, which seems really low, and in any case the agriculture there is clearly irrigated.
But those maize samples, mainly now conserved at CGN in the Netherlands incidentally, the results of something called the 1976 Netherlands-Pakistan Expedition by the Stichting voor Plantenveredeling, do seem to have some very unique adaptations.
Maize location, location location…
A quick search on Genesys revealed 302 maize accessions from above 1500 masl in the Himalayas, and 62 above 2500 masl. Of course, there are many more maize accessions from high altitudes in Central and South America, but their photoperiod adaptation (among other things) is likely to be quite different.
That’s from a post I put up here a few days ago. Some people said I should back up that “among other things,” so here goes.
I extracted from Genesys lat/longs for 2,388 maize landrace accessions collected above 2000 masl in the Andes, and for 96 in the Himalayas. I then asked ChatGPT to calculate separate averages for the two sets of accession collecting localities for two climate variables, i.e. mean annual temperature and precipitation. It asked me to supply it with the WorldClim data as a zip file, which I duly did.
It told me the Andean sites had a mean annual temperature of about 12°C and the Himalayan ones of about 6°C. Mean annual precipitation was around 750mm and 640mm, respectively. So there could well be some significant overall differences in adaptation between the two sets of germplasm.
But…
I used the coarsest WorldClim dataset, which is probably not a great idea in mountain areas. And many accessions were collected at the same sites: those 96 Himalayan maizes for example come from only 52 distinct places. I should probably have only used unique collecting localities to make the calculations. The “Subsetting Tool” in Genesys does do that, and displays nice histograms, but it doesn’t give you average values for the whole subset. Incidentally, when I looked at the histogram for total precipitation for the Himalayan material, there was a suspiciously big spike way at the dry end. Really not sure what’s happening there.
Maybe some climatologists or geographers or GIS jockeys can explain. And do a better analysis. And come up with a really easy way of extracting climate data for a long list of localities.
Brainfood: Diversity of Oats, Cotton, Sugarcane, Rice, Amaranthus, Vegetables, Agroforestry, Value chains
- Genome-wide comparative diversity uncovers population structure, global distribution, and targets of selection in hexaploid oat. A worldwide survey reveals how oat diversity is structured, spread, and shaped by breeding, helping pinpoint untapped genetic resources for future improvement.
- Genomic diversity and the domestication history of cotton (Gossypium hirsutum). Its genome traces cotton’s journey from its wild origins in Mesoamerica while documenting the genetic narrowing that accompanied domestication.
- Genetic architecture of sugarcane traits in a polyploid genomics framework. New genomic tools finally begin to untangle the diversity of one of agriculture’s most genetically complex crops, exposing the basis of traits breeders have long selected largely in the dark.
- Projected warming will exceed the long-term thermal limits of rice cultivation. Rice has historically thrived within remarkably stable climatic boundaries. Those boundaries are now on course to be crossed across major growing regions, with profound implications for global food security. Diversity to the rescue?
- An inter-specific Amaranthus pangenome captures genetic variation potentially underlying key leafy vegetable traits in this underutilised crop. A rich reservoir of previously hidden diversity emerges from across multiple cultivated amaranths, offering breeders new options for improving a neglected but nutritious vegetable.
- Impact of gardening and nutrition support provided to women in refugee camps in Cox’s Bazar, Bangladesh. Even in one of the world’s most challenging humanitarian settings, greater interspecific crop diversity translated into better diets, improved food security, and enhanced wellbeing.
- Designing perennial crop-based agroforestry systems: specificities, challenges, and opportunities. Diversification does not stop at the field edge: how perennial crops can be combined with trees to deliver productive, resilient, and biodiversity-friendly farming systems.
- Towards Nature Positive supply chains: From biodiversity commitments to organisational action. What would it take to move biodiversity from corporate promises to business practice? Maybe the above examples can help turn aspiration into measurable action.
Stairway to maize diversity
There’s a nice article in Rising Kashmir highlighting that region’s cold-tolerant maize landraces as a unique source of genetic diversity. What I liked about it is that it doesn’t condescend to its audience. It’s unapologetically technical and niche, while successfully (I think) striving to be understood by all. That’s rare. The author, Dr Salika Ramazan, argues that long adaptation to Himalayan environments has produced valuable traits for climate resilience and future maize breeding, and advocates for urgent conservation before this irreplaceable diversity is lost.
A quick search on Genesys revealed 302 maize accessions from above 1500 masl in the Himalayas (yellow on the map below), and 62 above 2500 masl (red). Of course, there are many more maize accessions from high altitudes in Central and South America, but their photoperiod adaptation (among other things) is likely to be quite different.
