I could have sworn I had at least Nibbled Our World in Data’s Is organic farming better for the environment than conventional farming? But it doesn’t look like it. Fortunately, Jeremy gets to grips with it in his latest newsletter. Along with that autumnal favourite, the apple, and lots of other interesting stuff.
Brainfood: From data to action
- A three-decade-long analysis shows rising threatened species and responsibility gaps in global supply chains. Data says that we must make responsibility for biodiversity traceable from production to final demand.
- Development of an evidence-based integrated germplasm prioritization framework for conservation and breeding. Data says: here’s how to extract some defensible conservation and breeding priorities from this large collection.
- A methodological framework for the standardised evaluation of olive genetic resources: GEN4OLIVE harmonized protocols. Data says that we should standardise phenotyping across countries to make olive germplasm more useful in breeding.
- High-throughput phenotyping of Bambara groundnut [Vigna subterranea (L.) Verdc.] seed morphometrics using videometer. Data says that we should use multispectral imaging to really speed up seed characterization and breeding in Bambara groundnut.
- Predicting the cross-continental spread of the cassava brown streak disease epidemic in sub-Saharan Africa. Data says that we must strengthen surveillance and delivery systems for clean planting material before cassava brown streak disease reaches Nigeria.
- The Sustainability of Robusta Coffee Under Global Change—A Review. Data says that we must match robusta production to genuinely suitable environments, plus invest in lower-input cultivation and alternative coffee species.
- Borassus Akeassii Facing Societal and Environmental Challenges: Case Study of the Gouin Society of Southwestern Burkina Faso. Data says that we need to conserve this multipurpose palm once central to Gouin livelihoods together with the local knowledge and practices that make it useful.
The NPGS after Beltsville
The USDA has decided to close its iconic flagship site, the Beltsville Agricultural Research Center (BARC) in Maryland. Everyone in plant genetic resources knows about the place simply known as “Beltsville.” Cost is apparently to blame: the agency says modernizing just 11 of BARC’s 400-plus buildings and carrying out deferred maintenance would require a $500 million one-time investment plus $40 million a year ongoing, which it calls financially unsustainable. That’s about 3 hours of US defence spending.
What does this mean for the National Plant Germplasm System (NPGS)?
The NPGS’s actual seed and other collections are already distributed across the country, and USDA is using the closure to invest in new infrastructure elsewhere, including a centralized germplasm distribution centre in Ames, Iowa. Which is good.
But what happens to the National Germplasm Resources Laboratory, a key denizen of BARC? The NGRL is not a genebank. It’s a team of people who, from Beltsville, “facilitates the acquisition, exchange, and documentation of crop genetic resources important to world food security.” In other words, it provides some of the connective tissue that turns a bunch of genebanks spread around the country into a national system.
The USDA announcement is not clear about the NGRL. It does says that research projects at Beltsville will be redistributed among other USDA locations, but not what will happen to NGRL staff and its system-wide functions. Ames will gain an important new distribution facility, but that’s not the same as the NGRL as a whole.
It will be interesting to see whether USDA moves the NGRL’s expertise and functions intact, or divides them among different locations: dispersion runs the danger of weakening the institutional knowledge of how acquisition, documentation, quarantine, distribution and international exchange fit together. For the NPGS, that may ultimately be the most important consequence of the Beltsville reorganization. Stay tuned.
LATER: Some people don’t like what’s happening.
Brainfood: Opportunity crops, meet your constraints
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There’s a wave of groundwork being laid — genomic, cultural, and geospatial — for opportunity crops, but the governance, disease-pressure, market and environmental constraints that marginalized them in the first place are still very much active, and in some cases actively winning.
- Constraints on crop diversification under drought: Multi-scale evidence from California’s San Joaquin Valley. Consolidation, land tenure and water access limits farmers’ ability to switch crops.
- Fragmented urban food governance and impacts on the marginalisation of indigenous crops in Ghana. City plans sideline indigenous crops, and communities pay the price.
- Full Genome Characterization of the Causal Virus of Yellow Mosaic Disease in Mungbean Minicore Accessions. Technical barriers block the path from potential to harvest.
- Capsicum pubescens Ruiz & Pav.: evolutionary history, domestication, genetic resources and future opportunities for an overlooked Andean crop. Genomic evidence reveals substantial diversity in this overlooked Andean pepper but also major conservation gaps, particularly in Bolivia, highlighting opportunities for both crop improvement and biocultural conservation.
- Bitter vetch (Vicia ervilia (L.) Willd.): current research advances and future perspectives for a neglected legume crop. It was dropped because of anti-nutritional quirks, but should, and could, return for marginal lands.
- Genetic characterization of a global collection of common buckwheat to harness genetic resources for agricultural diversity. Hidden diversity is still out there.
- Genotype-by-sequencing of global hyacinth bean (Lablab purpureus) collections provides genomic resources for crop conservation and improvement. Diversity survives in farmer fields and genebanks.
- Wild Edible Greens Heritage in Western Crete and Its Resilience Across Greek Islands: The Role of Small-Scale Farming, Biodiversity, and Isolation. Small-scale farming sustains knowledge of wild edible greens across Greek islands, showing that opportunity crops depend on living farming cultures.
- African Crop Calendar: A geo-referenced dataset of crop growing seasons across diverse agro-ecological regions. Where (or should that be when) alternative crops might fit within agricultural systems.
The case for a case manager
In an earlier post I argued that the crop diversity conservation and use system has a missing middle: someone whose job it is to get the whole way from an agricultural problem to a diversity-based solution.
That would address the perceived problem of “underuse” of genebanks collections better, I think, than making more data on collections available, or easier to search. I know we now have cheap genome sequencing and high-throughput phenotyping and powerful databases and AI on our phones, for pity’s sake. But we’ve been counting on the latest technological leap for quite a while now, and I figured it was time to look elsewhere for a solution.
I compared this missing role or function to that of an insurance broker.
I still think there’s a missing middle; but that was the wrong analogy. Insurance brokers navigate a liquid market of interchangeable, price-comparable products with a client who already knows they want insurance. That’s not like working with genebanks, if you think it through better than I originally did. I think I was seduced by the notion that crop diversity is a form of insurance.
There’s a better fit: medical case manager.
That’s the person who follows the patient through the maze of the health system. They don’t do the surgery or prescribe the drugs. They make sure the referrals happens, the test results gets chased, the specialists talk to each other, and nobody quietly drops the ball because, well, their particular bit of the system is working perfectly well.
Sound familiar?
A breeding programme can have a perfectly good reason for aiming for a particular combination of traits. A genebank can have exactly the right diversity to test. The accessions can be sequenced, well characterized, searchable through a beautifully designed database, and readily available. The breeders might be excellent breeders.
And still nothing might happen. Not because anyone screwed up necessarily, but because nobody owned the process as a whole, and thus put the entire package together.
That, I think, is the missing middle.
And this better analogy points to something else that the insurance-broker metaphor rather conveniently (for me) glossed over: independence.
Independence as a structural necessity. Someone sitting inside Genebank A, however well-intentioned, is going to have a harder time saying “actually, the stuff you need is in Genebank B,” because their salary, mandate and incentives all live inside Genebank A.
A case manager, on the other hand, is supposed to follow the patient, not defend the department.
The starting point should be the agricultural problem. The answer might be in a genebank. It might be in another genebank. It might be on a farm, in a community seed bank, in a breeding programme, or nowhere in the genetic-resources system at all. The case manager needs to be positioned so that they have no stake in which collection, programme or database ends up being the answer.
There is another useful thing about the case-manager analogy: it is not hypothetical. Health systems have been paying people to do this for decades. And they have had to work out some fairly prosaic questions that we tend to skip when talking about “unlocking” genebank diversity.
Who pays? What counts as success? How do you stop the navigator becoming a glorified administrator? What happens when whoever pays the salary starts deciding where the patients should go?
These are not trivial details. Getting them right is what turns a nice metaphor into an institution that might just work.
Start with the problem. Find the relevant expertise and diversity, wherever it happens to be. Get the handoffs made. Notice when things stall. Keep going until there is an outcome, including, if necessary, the conclusion that crop diversity wasn’t the answer.
We’ve gotten better at opening the door to genebanks over the years. We have lots of data, fancy databases and AI. What we’re still missing is the person who walks through that door with you, the user, and is knowledgeable and independent enough to help you figure out whether the answer lies inside, elsewhere in the system, or somewhere else altogether. Call it a broker or a case manager, or whatever else you like, but that’s what I believe we need.
Again, this is just me thinking out loud here. Maybe I’m the patient who has been sent home with a stack of test results, a list of specialists and a phone number for the hospital switchboard, and is trying to work out what to do next. Help me out.