Society faces enormous challenges in the transition to sustainable rural development. We are unlikely to make this transition unless we move away from the 20th-century paradigm that sees the world as a logical, linear system focused on “scaling up” the use of technologies to reach hundreds of millions of smallholders.
In a new article published this week on NextBillion, Lennart Woltering of CIMMYT contends that “farming communities are unlikely to continue using a new practice or technology if the surrounding system remains unchanged, since it is this very system that shaped their conventional way of farming.”
Woltering calls on the research for development community to work towards producing deeper system change and offers some key considerations for moving in the right direction.
The International Maize and Wheat Improvement Center (CIMMYT) operates five agricultural experiment stations in Mexico. Strategically located across the country to take advantage of different growing conditions — spanning arid northern plains to sub-tropical and temperate climatic zones — the stations offer unique and well-managed testing conditions for a variety of biotic and abiotic stresses.
Heat and drought tolerance in wheat is the focus of study at Ciudad Obregón, while the humid, cool conditions at Toluca are ideal for studying wheat resistance to foliar diseases. The tropical and sub-tropical settings of Agua Fría and Tlaltizapán respectively are suited to maize field trials, while at El Batán researchers carry out a wide variety of maize and wheat trials.
A new video highlights the important and valuable contribution of the five experimental stations in Mexico to CIMMYT’s goal of developing maize and wheat that can cope with demanding environments around the world, helping smallholder farmers in Africa, Asia and Latin America adapt to challenges like climate change, emerging pests and disease, and malnutrition.
Featuring aerial cinematography and interviews with each station’s manager, the video takes viewers on a journey to each experimental station to highlight the research and management practices specific to each location.
In addition to their role in breeding maize and wheat varieties, CIMMYT’s experimental stations host educational events throughout the year that train the next generation of farmers, policymakers and crop scientists. They also provide the canvas on which CIMMYT scientists develop and test farming practices and technologies to help farmers grow more with less.
Some of the stations also hold historical significance. Ciudad Obregón and Toluca are two of the sites where Norman Borlaug set up his shuttle breeding program that provided the foundations of the Green Revolution. It was also in Toluca, while at a trial plot alongside six young scientists from four developing nations, where Borlaug first received news of his 1970 Nobel Peace Prize award.
Farmers frequently encounter trade-offs between maximizing short-term profits and ensuring sustainable, long-term production. Santiago López-Ridaura, a senior scientist at the International Maize and Wheat Improvement Center (CIMMYT), says these trade-offs are even more complicated for small-scale farmers who grow a mix of crops and raise livestock. With computer models to play out different scenarios, he and his team are helping them find optimal solutions.
“If you have $100, one hectare of maize, a half hectare of beans and three cows, you have limited resources,” indicates López-Ridaura. “You have to decide how you allocate those resources.”
Should the farmer use the money to buy new equipment or vaccinate the cows? What would happen if the farmer replaced the half-acre of beans with maize? These trade-offs, López-Ridaura explains, are one aspect of a farming system’s complexity.
“The other is that these farmers are trying to satisfy multiple objectives,” he adds. “They want to generate income. They want to produce enough food to feed their family and they may be trying to maintain cultural values.”
For example, a hybrid maize variety may produce higher yields under certain growing conditions, but the farmer could decide to continue growing the native variety because it carries cultural or even religious importance. Seasonal migration for off-farm jobs, climate change and access to markets are just some of the other factors that further complicate the decision-making process. López-Ridaura points out many models in the past have failed to capture these complexities because they have focused on one objective: productivity at the plot level.
“Our models show the bigger picture. They take a lot of time to develop, but they’re worth it,” says López-Ridaura.
Custom solutions to farming challenges
The models start with hundreds of in-depth household surveys from a specific region. López-Ridaura and his team then organize the large pool of data into several categories of farming systems.
“We make a model that says, ‘OK, this farm in Oaxaca, Mexico, has five hectares, 20 sheep and five people,” he explains. “We know how much the animals need to eat, how much the people need to eat, how much the farm produces and how much production costs.”
He and his team can then adjust certain factors in the model to explore different outcomes. For example, they can see how much water the farmer could use for irrigation to maximize his/her yields without depleting the local water supply during a drought. They can see which farmers would be the most vulnerable to a commodity crop price drop or who would benefit from a new policy.
Santiago López-Ridaura (left) asks a farmer in Guatemala about his priorities — produce food, generate income, maintain soil health and feed his livestock — and the reasons behind his agricultural practices. (Photo: Carlos Sum/Buena Milpa)
“The political guys often want a simple solution so they may say, ‘We should subsidize inputs such as seeds and fertilizers.’ In Mexico, for example, you might miss 60-70% of farmers as they don’t use much of these inputs,” López-Ridaura says. “So that’s great for 30% of the population, but why don’t we think about the other 70%? We must be able to suggest alternatives from a basket of options, considering the diversity of farming systems.”
López-Ridaura emphasizes that the models on their own do not provide solutions. He and his research team work with farmers to learn what they identify as their main challenges and how best to support them.
“We have networks of farmers in Guatemala and Oaxaca, and some may say, ‘Well, our main challenge is being self-sufficient with forage crops,’ and we’ll say, ‘OK, why don’t we try a crop rotation with forage crops? Our model suggests that it might be an appropriate option.’”
He and his team can then help the farmers access the right kind of seed and find out how best to grow it. This relationship is not a one-way street. The farmers also provide feedback on what is or is not working on the ground, which helps the researchers improve the accuracy of their models. This approach helps the researchers, farmers and policymakers understand different pathways forward and develop locally adapted, sustainable solutions.
Santiago López-Ridaura and his team work in Africa, Latin America and South Asia. Their funding often comes from development agencies such as IFAD and USAID.
