Farmers in three countries, including in India, have turned into citizen scientists, helping generate data on crop varieties that adapt best to potential climatic changes.

In a study spanning India, Nicaragua and Ethiopia, researchers have demonstrated how farmers’ involvement in scientific studies can improve and accelerate crop variety recommendations.

Scientists applied a nifty crowdsourced citizen science approach called tricot – triadic comparisons of technologies – in which each farmer plants seeds of three crop varieties randomly assigned to them from a broader set of varieties.

The farmer then ranks the varieties according to different characteristics such as early vigour, yield, and grain quality.

There are several advantages in getting farmers to participate in data gathering, according to Jacob van Etten, senior scientist at Bioversity International and lead author of the paper.

“Farmers are the final users of the seeds, so they know best what works for them under local conditions,” van Etten told Mongabay-India. “They test in the environment to which the varieties should be adapted. Also, by doing this on their own farm, they are able to see the full crop cycle from seed to final product.”

He added: “In other formats for on-farm experimentation, farmers only get snapshots of the crop. Another aspect is that farmers contribute with their land and effort, reducing the costs of the trials. Seeds are generally provided for free, but other formats of experimentation often require renting land.”

Varied sample

The researchers spread out the tricot trials over different seasons and landscapes to obtain a unique dataset covering 842 plots of common bean (Phaseolus vulgaris) in Nicaragua, 1,090 plots of durum wheat (Triticum turgidum ssp. durum) in Ethiopia and 10,477 plots of bread wheat (Triticum aestivum) in India.

Trials were carried out between 2012 and 2016 during three cropping seasons in Ethiopia, five cropping seasons in Nicaragua, and four cropping seasons in India (Uttar Pradesh and Bihar), as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security. The CGIAR is the world’s largest global agricultural innovation network.

The rank-based feedback format allowed even those with low literacy skills to contribute their evaluation data through various channels, including mobile telephones. Scientists then linked the farmer-generated data with agroclimatic and soil data.

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Video by Bioversity International/Nora Capozio

“We combined the data from farmers with data on the seasonal climate of each plot,” van Etten explained. “Farmers told us when they planted, and we had GPS coordinates of their farms. This allowed us to link the relevant weather data that occurred during the trial on each plot. We then used statistical analysis to see how the seasonal climate influenced how well the varieties did on each farm.”

Seasonal climate data was sourced from weather stations and satellites.

It was a lot of fun to visit the plots and talk with the farmers. Each plot had its own little story: wheat growing in an orchard or next to a cooperative and women’s groups getting involved, the researcher recalled in a blog post.

“One thing we want to test is whether this approach is more cost-effective and less complicated than the usual demonstration plots or participatory variety trials,” he said. “In the new setup, logistics are less complicated because the seed comes to the farmer and the farmer doesn’t come to the demonstration plot.”

As the plots are smaller (with only three varieties from 120 grams of seed), they are easier to accommodate.

Discussing the significance of the study, Ambica Paliwal of Bioversity International, India, emphasised that in vulnerable, low-income areas, climatic analysis of variety performance is possible with trial data generated directly by farmer citizen scientists on farms.

The unique contribution of the tricot approach is that it integrates aspects of approaches such as multilocation trials, participatory variety selection, variety dissemination and others into a simple trial format.

This simple format addresses the challenge of variety replacement for climate adaptation in a way that is, at the same time, scalable and demand led.

Tricot trials can track climate trends as they manifest themselves on farms, adjust variety recommendations and recommendation domains, and contribute to understanding how climate affects on-farm varietal performance.

These are farmers evaluating traits of durum wheat varieties in Ethiopia. Photo credit: Samantha Collins/Bioversity International.
These are farmers evaluating traits of durum wheat varieties in Ethiopia. Photo credit: Samantha Collins/Bioversity International.

Indian preferances

For Nicaragua, bean variety performance was linked to the highest night temperature while in Ethiopia the minimum night temperature played a key role in durum wheat’s behaviour.

For bread wheat in India, diurnal temperature range during the vegetative period, determined which varieties do better and which worst under certain seasonal climate conditions.

Varietal performance patterns changed with the diurnal temperature range, which is the difference between the minimum and maximum daily temperatures.

“When the diurnal temperature range is low, the weather is more cloudy, rainier and less sunny,” explained Jacob van Etten. “Certain varieties do better under these conditions. Other varieties do better under high DRT, which means few clouds, little rain and much sun.”

To assess what the tricot trial results mean in practice, results were weighed against existing recommendations. For India, findings were compared with the front-line demonstrations of the Indian Institute for Wheat and Barley Research.

Some varieties performed well under both high and low diurnal temperature range, especially the double dwarf wheat variety HD 2967. HD 2967 was indeed the top variety in the tricot trial among the varieties considered by the IIWBR. In the tricot trials, however, K 9107 (a variety released in 1996) outperformed HD 2967 (released in 2011).

A key insight was that certain older varieties such as K 9107 are still preferred by farmers, researchers said. “Also, we found that variety recommendations which were homogeneous for the Indo-Gangetic Plains, can benefit if they are more location-specific and based on climate analysis,” van Etten pointed out.

“A limitation is the use of the tricot method by government-funded institutions,” he said. “The current approach is to use frontline demonstration plots. The results of the study suggest that the tricot approach could complement that approach, to allow for a more scientific analysis of the climate adaptation of varieties.”

Wheat varieties grown as part of crowdsourcing trials in India. Photo credit: T.Rastogi/Bioversity International.
Wheat varieties grown as part of crowdsourcing trials in India. Photo credit: T.Rastogi/Bioversity International.

Researchers’ challenges

Farmers have shown a lot of interest, the researchers observed. As end users, they were keen to carry out field trials and then adopting varieties as per their experiences, said Ambica Paliwal.

“They return data in almost all cases, and if they didn’t it was mostly due to external causes, such as the loss of the plot to drought,” added van Etten. “Variety adoption has been very high. We have measured yield increases of more than 30%. This is a very important achievement, that will be published soon.”

During the execution of the project, some challenges did come up. Seed arrived late in the first cycle, but farmers were ready to remove other crops or clear spaces to plant the trial seeds since little land is required. Another challenge was to get the women involved.

“In the first year, few women participated,” van Etten noted. “For cultural reasons, crop variety evaluation is often seen as mainly of interest to men. We thought that their participation was important, however as women are often knowledgeable about different aspects than men, especially food preparation.”

He added: “We reached out to women self-help groups in different areas and this proved a good strategy. Many women were very enthusiastic to participate.”

A survey conducted in April 2017 in Bihar indicates that 83% of farmers in Samastipur, 95% in Chhapra and 95% in Vaishali districts want to grow the varieties evaluated in the participatory trials under Bioversity International’s “Seeds for Needs” initiative which works with farmers to research how crop diversity can help minimise the risks associated with climate change.

Before the intervention, the farmers usually used only two to three varieties, but now they know of more than ten varieties of rice and wheat, and their response to different climatic conditions.

For instance, Jagdish Singh of Mukundpur village in Bihar says he assesses all the varieties and then selects the better ones for use in the subsequent years.

Nirmala Devi, a farmer with a landholding of an acre in Bhatadasi in Bihar, pointed out that before the trials, she knew about only two to three varieties available in the local market. Currently, she grows five wheat varieties on her farm.

Jacob van Etten underscored the importance of collaborating with farmers: “I think that farmer collaboration is essential for selecting climate-resilient varieties. Without feedback from farmers, scientists may be promoting varieties that have low acceptance among farmers, even though they may be very tolerant of extreme weather.”

He added: “Stress tolerance is only one aspect, and farmers look at the whole crop and its product to evaluate its value to them. On the other hand, farmers have the capacity to produce data that make good sense from the perspective of a crop scientist. The insights we obtained from their data matched other scientific findings well.”

Woman farmer testing three wheat varieties as part of the crowdsourcing component of Seeds4Needs project. Photo credit: J. van Etten/Bioversity International.
Woman farmer testing three wheat varieties as part of the crowdsourcing component of Seeds4Needs project. Photo credit: J. van Etten/Bioversity International.

This article first appeared on Mongabay.