Agricultural Biodiversity Weblog

August 20, 2026August 20, 2026

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:

restoration objectives

environmental conditions

species distributions

functional traits

seed zones

future climate scenarios

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:

orthodox — tolerant of drying and suitable for conventional storage

recalcitrant — sensitive to drying and therefore requiring different handling

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:

What is the state of the site?

Is active planting actually necessary?

What natural regeneration is occurring?

What ecosystem are you trying to recover?

What functions are missing?

What species are already present?

What are the local threats?

What restoration approach is appropriate?

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:

Site assessment: What needs restoring? Gap

Restoration design: What restoration approach is appropriate? Gap

Species & provenance selection: What should we plant? D4R

Seed sourcing: Where can we obtain seeds? SeedPOD/Gap (collecting)

Seed handling/storage: How should we handle the seeds? Wyse–Dickie

Germination/propagation: How do we produce seedlings? GEA

Traceability & deployment: Where did every seed/seedling go, and what happened to them? MyFarmTrees

Monitoring: Did restoration succeed? Gap/MyFarmTrees

Interested in seeing where all this goes, as I am? Start by registering for the re-run of the webinar on 30 September.

August 19, 2026August 18, 2026

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.

August 18, 2026August 19, 2026

A picture is worth a thousand descriptors

For decades, germplasm characterization has relied on people looking at plants, seeds and fruits and recording what they see; first on paper forms, more recently admittedly on tablets and the like. I’ve done that myself, and let me tell you, recording the colour of taro stems on bits of damp paper in the middle of a forest clearing in Vanuatu is no fun.

Lately, thankfully, the camera has been taking over.

A recent overview of new tools for plant genebanks highlights digital photography as a way of capturing standardized information on the colour, size and morphology of seeds and other plant parts, alongside more sophisticated technologies such as hyperspectral imaging and mobile field sensors. The attraction is obvious: instead of recording a handful of descriptors by eye, images can capture a much richer set of characteristics that can subsequently be measured and analysed at your leisure.

The potential is particularly striking for fruit crops. A new study of heritage apples used controlled multi-view imaging to characterize about 350 accessions over three years and two locations. Fancy maths achieved 95% accuracy in distinguishing 38 cultivars, rising to 99% when images of three fruits were combined.

And the technology does not necessarily require sophisticated equipment. In a recent demonstration with beans with complex colour patterns, Miguel Angel Acosta Chinchilla used ordinary photographs, image pre-processing and clustering algorithms to extract dominant palettes and colour distributions.

We’re moving from a limited number of human-defined descriptors to infinitely explorable machine-readable phenotypes. An image can preserve information that nobody thought to score at the time, and algorithms can return to it later to measure traits that were not originally part of the characterization protocol. For genebanks, that could be transformative. A photograph taken today may become a source of data for questions that don’t actually arise until tomorrow.

I wish I had a digital camera with me in that taro patch twenty-odd years ago. Goodness knows what people could be finding in those photos now.

August 17, 2026August 17, 2026

Mo’ better veggies

In the latest Eat This Newsletter I shared this item, which may be relevant here too.

There’s no shortage of advice that we should all eat more vegetables. They are undoubtedly good for long-term health, and not eating enough vegetables is one of the top five dietary risk factors for disease. And yet, despite all the exhortations and official guidelines, globally around the world people eat only 60% by weight of the vegetables they should. What to do?

The facts above are just some I lifted from a recent paper in the Proceedings of the National Academy of Science: Reversing vegetable biodiversity loss to diversify diets. The authors are a who’s who of agricultural biodiversity and nutrition (many of them familiar to Eat This Podcast). They offer a four-pronged solution, avoiding the whole fruit-vegetable schism with a wise reflection: “Because culinary traditions and nutritional perceptions vary across regions, the specific edible parts and species considered vegetables can differ across cultures”.

Prong 1: Secure vegetable biodiversity for the future. Collect more vegetable diversity and make sure that existing diversity in collections is kept in good working order.

Prong 2: Harness vegetable biodiversity to deliver new varieties. Give farmers, researchers and breeders access to the collected diversity and information about it so that they can improve varieties across the whole range of vegetable species.

Prong 3: Promote vegetable biodiversity to diversify diets. Include more and more different vegetables in meals at school and at home, primarily by linking local growers to school feeding programmes and local markets.

Prong 4: Integrate vegetable biodiversity into policy frameworks for long-term impact. Of course, as night follows day, policy frameworks follow suggestions for action.

The paper is a really interesting read. It emerges from a three-year pilot project in four African countries and summarises a lot of thinking over the years. I’d love to see all countries grasp the four prongs and run with them. But, NGL, and with the greatest respect to the authors, that seems unlikely. Please, prove me wrong.

August 17, 2026August 17, 2026

Brainfood: Mung bean pan-genome, Sunflower resistance, Olive adaptation, Allergic peanuts, Weird coffees, Chinese tea, Measuring selection

Graph-based pan-genome reveals structural variations associated with agronomic traits in mung bean. Pan-genome captures extensive structural variation missed by a single reference genome, providing new targets for mung bean improvement.
Wild genes to the rescue: high-throughput genomics reveals the wild source of broomrape resistance in sunflower. Combining high-throughput root phenotyping with genomics identifies wild introgressions underlying broomrape resistance in sunflower and exposes valuable adaptive variation for breeding.
Genomic insights into the local adaptation of spontaneous olive trees in the Mediterranean Basin highlight the need for conservation planning in the face of global change. Genomics of wild West Mediterranean olive trees reveals patterns of local adaptation across temperature and rainfall gradients that it will be important to conserve as climates change.
Genetic regulation of major immunogenic protein accumulation in peanut seeds. Genomics provides targets for breeding peanuts with reduced allergenicity.
Genomic elucidation of hybridization between Liberica and excelsa coffee and its implications for coffee crop development. Genomics confirms that Liberica and excelsa coffee readily hybridize and produce fertile, genetically diverse offspring with intermediate agronomic traits, a possible source of diversity to broaden coffee’s climate resilience.
Simple sequence repeat (SSR) marker-based genetic diversity and population structure of large-leaf tea germplasm across four major tea-producing regions of Yunnan, China. Genomics of Yunnan’s large-leaf tea germplasm finds substantial genetic diversity but remarkably little regional differentiation, showing that seed propagation, natural crossing and human movement have maintained genetic connectivity across tea-growing regions.
Measuring maternal line selection driven by differential survival in ex situ collections for plant conservation. A new method distinguishes random mortality from selection among maternal lines in ex situ collections, offering conservationists a way to detect whether plant deaths are systematically eroding the genetic variation they are trying to preserve. And no genomics involved.