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Deploying precision agriculture in developing countries provides opportunities, challenges

Deploying precision agriculture in developing countries provides opportunities, challenges
By Cameron Rudolph
 
Pressure on farmers is high. A growing world population, estimated to reach nearly 10 billion by 2050, means a growing demand to produce more food. But more people will also require more housing and industrialization, and that will mean less land to farm.
 
For farmers, the endless amount of data available can be daunting, not to mention trying to keep pace with rapid-fire advancements in technology. This all can equate to a perfect storm of sorts, especially for small farmers in developing countries.
 
No one knows the international challenges quite like Michigan State University’s Karim Maredia, who leads World Technology Access Program (WorldTAP), which draws on expertise from MSU and around the world to offer short- and long-term trainings, advisory services and consultation in diverse areas of agricultural research and development.
 
The vast majority of farmers in developing countries are smallholder farmers, meaning that they grow food on a small piece of land to feed their families and might have some left over to sell at local markets. They often make field decisions on the basis of generic recommendations or historical information rather than scientific data.
 
“There are many instances with fertilizers, and pest and disease management, where farmers are just blindly applying inputs,” Maredia said. “They do what they’ve always done. There are many cases of overuse, underuse and misuse of inputs. We want to work with people to change that.”
 
Maredia has spent more than three decades assisting developing countries with capacity building, technology transfer and policymaking.
 
In 2017, he was named the only non-African on the High Level African Panel on Emerging Technologies, which was commissioned to unite scientists from agriculture, public health and natural resources management to discuss ways that new technologies could foster economic growth.He said the need for more precision agriculture technologies is vital to the future of farming, especially for smallholder farms.
 
The recent proliferation of cell phones in the developing world has enormously shifted how people interact with one another and exchange information. They have also drastically changed how businesses operate, and farms are no different.
 
According to a 2018 survey of 22 developing countries by the Pew Research Center, close to 60 percent of responders said they had smartphones. In the United States, 77 percent own smartphones.
 
From Michigan to Malawi, smartphones are becoming ubiquitous in agriculture. And it’s not simply a matter of speedy communication. The real value lies in using mobile applications to quickly collect and analyze data, an invaluable resource for high-pressure, real-time decision making.
 
Though access to data is mostly a problem of the past, implementing leading technologies remains a huge challenge.
 
Small farm, big responsibility
 
According to the Food and Agriculture Organization of the United Nations, the bulk of the 570 million global farms are operated by smallholder farmers. More than 80 percent of the food consumed in sub-Saharan Africa and Asia is grown on such farms. Smallholder farms are frequently the lifeblood of their communities, relied on for food security in some of the world’s poorest areas.
 
Despite the integral nature of these operations and rising availability of data, smallholder farmers have gaps in technology and knowledge.
 
To help fill these voids, Maredia and his WorldTAP colleagues train scientists, regulators and policymakers on a variety of topics, including food safety, sustainable agriculture, biotechnology, technology transfer and integrated pest management.
 
For example, Maredia is a principal investigator at MSU on a new 2019 project funded by the U.S. Agency for International Development to create an Egyptian Center of Excellence for Agriculture. The five-year, $30 million grant is led by Cornell University in partnership with MSU, Purdue University, the University of California-Davis, Sathguru Consultants, Cairo University and four other Egyptian universities.
 
Maredia and fellow MSU researchers are overseeing the Exchanges, Training and Scholarships component, in which faculty members and students will be trained on an assortment of agricultural topics.
 
Maredia has also identified programs from MSU that could be useful to scientists, extension specialists and farmers in developing countries. One is PhotosynQ, an initiative led by David Kramer, a John A. Hannah distinguished professor and MSU AgBioResearch scientist.
 
With a small, $100 handheld device, PhotosynQ users collect immediate data on plant health in the field or in the laboratory. They then upload that information through a smartphone app to the PhotosynQ website.
Sharing this data broadly has spawned a vast network of collaboration on topics from management techniques to plant variety choices. To date, more than 3,800 users have made more than 1.1 million contributions to the database.
 
“PhotosynQ is just one example where connecting people has resulted in a lot of information and knowledge being shared,” Maredia said. “This is a simple but elegant device. These are the types of technologies that farmers in developing countries are interested in because they are low in cost and high in benefit.”
 
Pressure-packed predictions
 
Forecasting crop yields is a valuable strategy for any farmer. The advantages of understanding how weather, soil conditions and management affect output are evident. That information ultimately aids in the formation of a cropping plan.
 
Access to sophisticated modeling methods, however, is limited. Farmers in developing countries often don’t have the opportunity to simulate a multitude of scenarios before making decisions.
 
But these are exactly the people who may benefit from it most. For many, production is a matter of survival.
 
Amor Ines, an assistant professor in the MSU Department of Plant, Soil and Microbial Sciences, wants to give farmers the chance to learn from technologies they may not otherwise have access to. He helps farmers in developing countries by matching access to information at the farm and policymaking levels and showing them how to use the knowledge.
 
“It’s one thing to give someone more data, but it’s quite another to show them how to use it effectively,” Ines said. “We can put simple sensors in a field and extract soil data, use remote sensors, collect aerial imagery, and put that together with weather forecasts. Factoring in management, we can start to use models to see what practices make the most sense. In developing countries, especially, there are limited resources that must be used efficiently.”
 
For several research endeavors, Ines has partnered with a company in Japan called ListenField, which connects satellite, drone, sensor and on-farm data, then delivers analysis and recommendations. The company provides a mobile application, FarmAI, that links these technologies and helps farmers manage day-to-day operations.
 
ListenField has collaborated with numerous organizations in Japan. One notable project involves working with universities in Japan, India and Thailand on data-based farming in the face of climate change.
 
Dealing with a changing climate is one of the more difficult aspects of modern-day agriculture. In the Philippines, where rice production is critical to the country’s food security, Ines and scientists from the International Research Institute for Climate and Society at Columbia University are merging crop modeling with seasonal climate forecasts to generate a decision-support tool.
 
For farmers and governments in developing countries, crop modeling can help them prepare for undesirable circumstances such as drought. In 2019, the Philippines have been experiencing severe drought due to El Niño.
 
“Seasonal climate forecasts aren’t very helpful for farmers without understanding of how that translates to recommendations,” Ines said. “Combining forecast data with the crop models allows us to present data-supported recommendations that are implementable at small and large scales. These farmers have never had information like this before, which makes this work very exciting.”
Source : msu.edu

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