- Herbaria viva: proto-genebanks of Mendel’s contemporaries in Moravia. The early 19th century living plant collections of Moravia (the world Mendel grew up in) were a kind of proto-genebank, systematically maintaining and circulating crop diversity decades before genetics had a name.
- Saving evolutionary time: Conflicting planetary temporalities in the genetic diversity debate, 1967–1980. Looking back 50 years, and 50 years after the Moravian proto-genebanks, a historian of science traces how Otto Frankel and Erna Bennett, sounding the alarm on genetic erosion in the 1960s-70s, articulated two competing visions of time and responsibility for safeguarding crop diversity, one rooted in development, the other in collective stewardship of evolution itself.
- Utilization and conservation of plant genetic resources for food and agriculture in China: a systematic review of genebanks and farmers’ seed systems. From history to present-day infrastructure. In China, genebanks and farmers’ seed systems have developed together, but gaps between formal and informal conservation remain. Otto and Erna unavailable for comment, alas.
- The effect of crop genetic diversity to food security among smallholder farmers in the global south and the role of community seed banks: a narrative literature review. Here’s the evidence on how community seed banks shape food security for smallholders, but could do more. That’s the informal system at work for you, Erna would say.
- How community seed banks contribute to climate-resilient seed systems: evidence from Ethiopia, Malawi, and Nepal. Speaking of which, a companion study looks at how community seed banks function in practice, finding they do bolster local seed security and climate adaptation, but with real limits: patchy variety availability, uneven quantities, and occasional genetic erosion of their own.
- Varietal development and rice yield growth in India: assessing IRRI’s germplasm contribution. A new assessment of the contribution of IRRI germplasm to Indian rice breeding comes in at around 11% of annual rice yield growth from 1966 to 2021. That’s the formal system at work for you, Otto would say.
- Improving low-pH and high-aluminum field tolerance in alfalfa (Medicago sativa L.). Also on the breeding front, screens of genebank collections and their derivatives for field-level tolerance to difficult soils bear fruit. Or rather, leaves.
- FAIRness at all costs? Practical limitations in applying the FAIR principles to plant genetic resources data. And finally, a reality check for the data side of all this. Applying the FAIR principles to plant genetic resources data isn’t as straightforward as the mandate suggests, with a number of practical friction points standing between the ideal and actual implementation.
The plants that statistics forgot
FAO has just put out new guidance on capturing wild foods and neglected and underutilized species (NUS) in dietary surveys. It’s very much worth a look, even if your interest runs more to grain landraces on the farm than to greens gathered from the forest. The methodology is built to overcome a very real problem: standard dietary assessment tools are generally designed with the main staples in mind, so anything outside that narrow frame (think foraged, seasonal, localized, thinly documented) tends to fall straight through the cracks.
FAO’s fix is a set of very sensible, practical steps: engage local knowledge holders to compile inventories under their own names for things, survey markets to see what’s actually being sold and eaten, map harvest calendars against agroecological zones and seasons, and build simple identification tools (photobooks, reference databases) that let enumerators and communities work from a shared understanding of what they’re counting.
None of that machinery is specific to wild foods though. The same toolkit could easily be adapted to survey the diversity hiding in plain sight on farms: crops and landraces known only by a few, grown in a handful of villages, marginalized, on their way to be forgotten. And invisible to national crop statistics that only track the main crops and the most common named improved varieties, if that. A market survey designed to catch wild greens sold at the roadside works just as well for catching a local bean landrace in the same market. A harvest calendar built to track when forest foods peak works just as well for tracking when fonio gets planted or harvested, and why farmers still bother with it. Great for quantifying the opportunity presented by “opportunity crops.”
And there’s a useful downstream application: surveys built this way could help flag where crop diversity is thinning out on the ground, or where it’s abundant but under-represented in genebank holdings. In other words, the kind of gap analysis that ought to be steering germplasm collecting missions.
FAO’s framing kind of gestures at this already: wild, managed and cultivated aren’t three separate boxes but points on a continuum. A methodology built to navigate that blurriness for wild foods is also a methodology that ought to work for navigating the blurriness at the cultivated end. It would be a shame if this toolkit stayed confined to the wild-food side of the spectrum when the conceptual heavy lifting behind it applies just as well to neglected cultivated diversity.
Putting names and faces to organic seed diversity
LIVESEEDING is a project…
…to foster the growth of the organic sector and transition towards more sustainable local food systems by delivering high quality organic seed of diverse cultivars adjusted to organic farming for a wide range of crops.
It is funded by Horizon Europe (Innovation Action), the Swiss State Secretariat for Education, Research and Innovation and UK Research and Innovation, and gathers 37 partners from 16 countries.
The project is producing some interesting resources, but the ones I like best are actually a little difficult to find on their website. So difficult, in fact, that I have to resort to linking to them via a search result on Organic Farm Knowledge.
They are plant genetic cards, each providing information on a specific cultivar, “supporting its identification, conservation, cultivation and use by farmers, seed practitioners, breeders, researchers and other stakeholders of the seed system.”
Here’s a little piece of one such card from Greece.
There’s also something called the EU Organic Seed Database “to create more transparency for the EU member states and for plant reproductive material suppliers regarding available offers of organic plant reproductive materials and to increase the supply of organic plant reproductive material in the EU member states and Switzerland.”
To be honest, I haven’t really played around with it enough to form a definitive judgement, but it does seem a little complicated to navigate at first blush. If anyone has a go, and has an opinion, please let me know in the comments. However, the plant genetic cards do have links to possible sources of seeds.
Towards a digital workflow for forest restoration
I missed the “From Seeds to Success: Digital Tools for Planning and Managing Forest Restoration” webinar a few weeks ago, jointly organized by the Alliance of Bioversity International and CIAT, the Millennium Seed Bank at the Royal Botanic Gardens, Kew, and the Forest Restoration Research Unit (FORRU), Chiang Mai University. Too busy moving to another continent. But fortunately there are now a handy summary and even a recording online. And there will be a re-run.
To remind everyone what the webinar was about:
The programme featured live demonstrations of five innovative digital tools, developed to support restoration planning, seed sourcing and project management, followed by an interactive discussion, during which participants explored their applications, strengths and future development.
With these five tools, therefore, we have the beginnings of a digital seed-to-restoration pipeline. Which is very exciting to me.
Let’s go through it step by step, and tool by tool.
1. Define the restoration objective and choose species: Diversity for Restoration (D4R)
Picture yourself looking at a site you want to restore. This tool answers the question: What should we plant here?
D4R is the front-end decision-support tool. It combines information on:
to recommend suitable species and seed sources.
2. Find the seed: SeedPOD
Then we need to know: Where can we actually obtain suitable seed?
Once D4R has identified desirable species and potentially appropriate provenances, SeedPOD steps up as the seed-sourcing layer, providing information from different organizations worldwide on the storage, availability, and germination of their seed collections. It is scheduled for launch in September 2026.
3. Decide how to handle and store the seed: Wyse–Dickie Seed Storage-Behaviour Predictor
But you won’t necessarily be able to get such information on all the seeds you might need. So how should we handle those seeds?
This tool predicts whether seeds are likely to be:
using species characteristics, taxonomy and environmental variables. That means you can work out how to process and store them.
4. Germinate and produce seedlings: Germination Experiment Assistant (GEA)
Having the seeds is great, but how do we turn them into viable seedlings?
Where there is little or no published germination information, you will need to generate it yourself. GEA uses experimental data and predictive modelling to produce species-specific germination protocols, including practical procedures for nurseries.
5. Track the material through the restoration operation: MyFarmTrees
Finally, once the work has started, you’ll need to monitor how it’s going: What happened to each seed lot, seedling and planting?
MyFarmTrees is the operational backbone of the five tools. It tracks restoration activities from seed collection to nursery production to field establishment using QR-coded seed lots and mobile technology. This gives you traceability. It also creates the possibility of connecting restoration activities to monitoring and ultimately payment-for-ecosystem-services systems and the like.
Is anything missing?
Having these five tools is great, but they don’t quite constitute the entire restoration workflow. They cover the biological-material pipeline extremely well: selection → sourcing → handling → propagation → deployment → monitoring. But the webinar participants did identify restoration approach selection, as well as planning collecting programmes, as gaps in the current digital toolkit. Along with, inevitably, seamless integration, or at least interoperability, of all the different tools.
So there should maybe be an initial stage to the above sequence:
0. Assess the site and restoration strategy
Because before unleashing D4R, you do need to know a bunch of stuff, for example:
And there should also maybe be a stage parallel to what I labelled 2. Find the seed above. Call it…:
2b. Collect the seed
Because if SeedPOD says suitable seed is available, all well and good. But if it isn’t, it would be nice to have a “seed collection planner” to generate a collecting programme for you, factoring in the distribution, ecology, mating system, and phenology of the target species, the accessibility of potential collecting sites, the budget available, you get the idea.
So maybe eventually the complete architecture of the system will be something along these lines:
Interested in seeing where all this goes, as I am? Start by registering for the re-run of the webinar on 30 September.
The revenge of the sweetpotato
Speaking of digital imagery and its uses in genebanks, get a load of the recently published catalogues of the Cuban sweet potato collection at the Research Institute of Tropical Roots and Tuber Crops (INIVIT), and of Peruvian cacaos. Beautiful. And do yourself a favour and don’t skip the foreword, preface and introduction to the Cuban volume. I found them very eloquent — and moving. Maybe a touch overwrought, admittedly, but it does take some gumption to say, of sweetpotato, in a genebank catalogue of all places, that: “Today, history grants it its revenge.” I just hope it’s true.