Crowd-Sourced, Citizen Science Can Improve Seed Systems and Climate Change Adaptation
This post is written by Jacob van Etten, Alliance Bioversity-CIAT.
Farmer-participatory selection stimulates local interest in new varieties and produces information on variety performance that is immediately relevant to local climate adaptation.
Climate adaptation requires farmers to adjust their crop varieties over time and use the right varieties to minimize climate risk. Variety replacement with new and improved genetics is among the very best strategies for crop yield, quality and productivity improvements in the face of a rapidly changing climate.
But variety replacement in nearly all open-pollinated variety (OPV) crops in Africa has not been effectively addressed. Seed systems in Africa are dominated by saved seed (and cuttings or root stock of vegetatively reproduced crops like cassava and banana), and locally traded or purchased seed. Farmers’ seed systems may be highly resilient in terms of providing adequate volumes of inexpensive seed each season. However, farmers’ seed systems are often limited from where seed is sourced and how much time the systems need to adjust to new conditions. A substantial volume of seed that circulates in such seed systems derives from old varieties released more than a decade ago, sometimes more. This means that farmers miss important opportunities to close the adaptation gap by accessing varieties that are better at coping with new climatic conditions. Breeding programs have not only increased productivity of new varieties, but also their stress tolerance, disease resistance, and often even their genetic diversity. Farmers need to be able to select what is best for their farms from all the options that are available to address climate change.
There are limitations to climate adaptation also within conventional breeding programs. Often, breeding programs have a limited number of centralized research stations that do not capture the full range of environmental (E) and management (M) conditions of farms for which breeders develop the new varieties or genetics (G). This becomes obvious when farmers select and cultivate local landraces that often outperform new varieties from centralized breeding stations. To respond to local cropping needs and climate change, the G x E x M interactions for millions of smallholder farmers must be addressed.
An important approach, which has been tried successfully over the last decades, is to perform selection directly on farms, together with farmers. However, breeding programs have found this difficult to scale to generate meaningful volumes of data that cover diverse growing conditions. To address this, we developed a new approach, building on experiences in crowdsourced citizen science. This new way of doing science allows thousands of citizen scientists to contribute to science by organizing activities in a way that makes it easy and enjoyable to participate, and by using digital tools to facilitate communication and data collection. We developed such an approach for agricultural experimentation: triadic comparisons of technology options (tricot). Tricot trials in farmers’ fields take advantage of their local knowledge and G x E x M diversity. In these evaluations, a farmer plants seeds from a personal test package of three varieties, randomly assigned from a larger pool of tested varieties. Farmers’ on-farm observations are collected and analyzed centrally. A simple, ranked-based feedback format allows even farmers with low literacy to contribute valuable evaluation data.
We found that local farmer observations and ranking could increase prediction accuracy in these challenging and diverse environments. Combining the farm-level data with climate data has generated important insights in climate adaptation. We found that farmers were eager to participate without monetary compensation because they value the interaction with experts and the sharing of seeds and information. Breeders have quicker access to the data, avoid tedious work to transfer data from paper to digital and can generate much richer insights from the data. Extension agents have an easier job in the field to identify farmers who are willing to participate and find pleasure in working with curious, highly motivated farmers.
Tricot trials can help track farm-level climate trends in real time, generate variety recommendations and help researchers understand how climate impacts varietal performance. Combining tricot trial data with other data provides further insight into varietal acceptability and other production factors as influenced by socioeconomic factors. Farmer-participatory selection stimulates local interest in new varieties and produces information on variety performance that is immediately relevant to local climate adaptation. In this way, tricot trials create a combination of supply-driven and demand-driven seed systems and create new opportunities to move new, highly adapted varieties into farmers’ fields.
The tricot citizen science approach has the potential to make an important contribution to farmers’ adaptive capacity and to the mobilization of crop genetic diversity for climate adaptation. For this to happen, creative collaborations and resourcing are needed among farmers, extension agents, plant breeders, agro dealers and seed companies.
For more information, see:
Jacob van Etten, Kauê de Sousa, Amilca Aguilar, et al. 2019. Crop variety management for climate adaptation supported by citizen science. PNAS 116: 4194-4199. www.pnas.org/cgi/doi/10.1073/pnas.1813720116
Kauê de Sousa, Jacob van Etten, Jesse Poland, et al. 2012. Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment. Communications Biology 4:944 https://doi.org/10.1038/s42003-021-02463-w
David Brown, Sytze de Bruin, Kauê de Sousa, et al. 2022. Rank-based data synthesis of common bean on-farm trials across four Central American countries. Crop Science 2022:1-21 DOI: 10.1002/csc2.20817