Changing the Game on Potato Late Blight Management: Workshops Highlight Innovative Scenarios
by Jorge Luis Alonso with ChatGPT
A study conducted by Wageningen University & Research presents model-based scenarios to groups of farmers and, following discussions, uses qualitative and quantitative measures to analyze the impact of the workshop on farmers’ perceptions of late blight control. A summary of the contents is given below.
Introduction
Late blight, caused by Phytophthora infestans, is a major problem in potato production, particularly in the Netherlands, where high potato density and favorable weather conditions contribute to frequent outbreaks of the disease. Fungicides are the dominant method of control in conventional agriculture, but this is expensive and harmful to the environment. Organic farmers, who are not allowed to use chemicals, often experience dramatically lower yields in years with early outbreaks of the disease.
To address these challenges, the development of resistant varieties can play a key role in sustainable disease control. However, the emergence of new virulent strains can cause resistance to break down and become less effective over time. Therefore, farmers play a critical role in the control of late blight by making crop management decisions that directly affect the spread of the disease.
In this context, Wageningen University & Research has created a computer model that can predict how diseases spread in a specific area. This model can assist farmers to make smarter decisions and know how different management strategies will impact their crops.
To help farmers understand how the model works, a simplified version was used in workshops. They were then able to see how different scenarios played out and understand the relationship between the environment and disease outbreaks. By discussing these scenarios together, stakeholders were able to make better decisions about how to manage their crops.
The workshops focused on disease outbreaks that occurred over a long period of time. They also looked at how farmers’ ideas about how to control blight changed over time. The goal was to help them work together and come to an agreement on how to better manage their crops and prevent the spread of disease.
In addition, these meetings included both conventional and organic farmers, who have different ways of managing their farms and dealing with blight. They developed different scenarios to compare the use of fungicides and plant resistance to control the disease. The workshops also analyzed different strategies for managing resistance to increase its durability.
After the meetings, they used both qualitative and quantitative methods to measure their impact on farmers’ understanding of blight management. This allowed them to assess how much knowledge was gained and improve the learning process.
Methods
One of the program’s assumptions was that farmers would have a choice between two types of potatoes: one susceptible to disease and the other resistant. Although the resistant type had a lower potential yield, it could be protected with fungicides. The program simulated the impact of weather on crop growth and assumed that only certain types of potatoes could be infected by the pathogen.
The scientists used the simulation to test various scenarios for controlling the spread of the disease. They experimented with different proportions of fields growing susceptible and resistant potatoes, as well as various frequencies of fungicide applications. Their aim was to find the most effective strategy for reducing the spread of the disease in the landscape. During the workshops, organic potato growers provided feedback to improve the simulation.
Results
Model scenarios
The research team looked at different ways of managing disease in crops. They considered three different scenarios.
In the first scenario, they used fungicides in some fields that were susceptible to disease. This resulted in better crop yields compared to the fields where no fungicides were used. Without fungicides, yields were unpredictable because the disease spread quickly. Although fungicides didn’t completely stop the disease from spreading, they did help control it to some extent. Disease incidence varied from 20% to 70% in different areas.
In the second scenario, they tried to use plant resistance to control the disease. Initially, this worked well, resulting in high yields with very low disease incidence. But after four years, a new type of disease emerged that was much more dangerous. Because most fields had already been planted with resistant crops, no fungicides were used and the disease spread rapidly. This led to reduced yields in both resistant and susceptible fields.
In the third scenario, they used both fungicides and resistant crops to control the disease. They found that using fungicides on susceptible fields resulted in the highest yields, followed by using resistant crops, and then not using fungicides at all. They also looked at different ways of managing resistance and found that using fungicides on all susceptible or resistant fields prevented the disease from spreading. Using a resistant crop with two resistance genes also worked well. Destroying resistant crops immediately after infection prevented the new, dangerous strain of the disease from taking hold. However, clustering resistant crops in one area did not work well to control the spread of the disease.
Workshop results
In one of the workshops, participants were given different situations and asked to answer multiple-choice questions about management strategies and model processes. There were both organic and conventional farmers in the group, and they had different expectations about potato yield, plant resistance, and resistance breakdown.
When discussing the model results, the farmers were surprised to see a high incidence of disease in scenario 1, despite frequent fungicide applications. They suggested that spraying schedules should be adjusted according to favorable weather conditions to effectively suppress the disease. The model was seen as a simplified way of understanding the processes that affect resistance breakdown, but not as an accurate predictor.
Many growers did not expect resistance to breaking down as quickly as shown in Scenario 2. The use of potato varieties with multiple resistance genes was seen as the best option for resistance management, but farmers were dependent on breeding companies to develop these varieties.
The workshop led to a change in the perception of late blight control among organic farmers. They agreed that immediate haulm destruction is important to increase the durability of resistance in single-gene varieties until varieties with multiple resistance genes become available. On the other hand, conventional farmers emphasized the use of fungicides in resistance management.
In summary, the workshop helped farmers understand the importance of adapting their spraying schedules and using potato varieties with multiple resistance genes. It also highlighted the need for immediate action to increase resistance durability in the absence of such varieties.
Discussion
The study identified several resistance management strategies that could help increase the durability of resistant varieties. The immediate destruction of infected plants in resistant fields was found to be effective, but the spatial allocation of resistant fields through clustering did not prevent resistance from breaking down.
In addition, the study found that farmers who participated in the workshops gained a better understanding of the late blight control system and agreed that different stakeholders need to work together for effective and sustainable disease control.
The researchers recommend that farmers use resistance management strategies, such as fungicide application and immediate destruction of infected plants, to prevent the emergence and spread of the virulent strain. They also suggest that the development of resistant varieties with multiple resistance genes should be a long-term strategy. Finally, the team proposes a systematic approach involving multiple stakeholders, such as the government, breeders, and retailers, to achieve sustainable disease control.
Summary
The study utilized an agent-based model to educate farmers on sustainable potato late blight control, which resulted in action-oriented outcomes:
- Presenting farmers with disease scenarios at a landscape level over ten years.
- Enabling farmers to understand potential disease patterns and make informed decisions on management.
- Demonstrating the need for low disease pressure and collective action to prevent the emergence and spread of virulent strains.
- Organizing workshops to promote a shared understanding of late blight control and emphasize the importance of collaboration.
- Using model scenarios to initiate discussions among participants and encourage the sharing of views to negotiate possible solutions.
- Utilizing agent-based modeling to communicate complex dynamics to stakeholders and using surveys and qualitative data to analyze changes in perception.
- Planning future research to involve breeding companies and policymakers to engage other stakeholders in disease management workshops.
Overall, the research outcomes demonstrated that agent-based modeling could effectively communicate complex dynamics to stakeholders and provide insights to analyze changes in perception, making it a valuable tool for future research in disease management.
Source: Francine C.A. Pacilly, Edith T. Lammerts van Bueren, Jeroen C.J. Groot, Gert Jan Hofstede. Moving perceptions on potato late blight control: Workshops with model-based scenarios. Crop Protection, Volume 119, 2019.
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