Meeting Tomorrow’s Food Needs with a Little Help from Technology
Some start-ups are using artificial intelligence while others are deploying computer vision and aerial imagery analytics to help farmers make better decisions to improve yield and productivity.
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Disruptive technologies have been overturning nearly every idea we have harboured of what it means to travel, bank, communicate and shop. These technologies are now set to storm a traditional industry that has so far been largely untouched by tech-driven transformations—namely agriculture.
Unlikely as this may seem, it is a development that was waiting to happen. As the world’s population continues to expand, so will the need to provide people with food. According to a recent report by the Food and Agriculture Organization (FAO) of the United Nations, there will be 10 billion mouths to feed by 2050, requiring a 50% increase in agricultural output worldwide. At the same time, there will be a dramatic drop in the number of agricultural workers—with a nearly 32% drop in developed countries and a 33% drop in developing countries since 1950.
To add to this will be the stark reality of climate change. Climate change is already creating unexpected weather conditions that impact soil quality, crop cycles and overall farm productivity. It is expected to further complicate how food is grown in the years ahead.
Deploying Technology in Agriculture Leads to Positive Results
Although technology cannot be applied indiscriminately to every process that constitutes farming, I do see its relevance in creating a more resilient, efficient and productive food system.
Let us look at some of the start-ups in the agriculture space that are applying technology to boost farm productivity. While some are enabling ‘precision farming’ others are assisting farmers in collecting accurate information about fertiliser and irrigation requirements among other functions.
When companies apply analytics to farming, they use data generated from satellite-monitoring technologies or weather simulations reveal insights at the level of individual farms. This data provides detailed information to farmers on soil composition, weather patterns and pest surveillance, which in turn helps them tweak existing arrangements.
According to research conducted by the Stanford Graduate School of Business team, a survey of American farmers who used precision technology witnessed substantial gains: average cost reductions of 15% along with a 13% increase in yields.
But analytics can also be used in other areas. For example, a start-up launched by Stanford graduates is helping farmers collate data on field irrigation and fertiliser usage through sensors and cameras attached to small planes. Through aerial spectral imaging, they are providing farmers with information on water, fertilisers, pest, and disease issues weeks before anyone on the ground detects a problem. I believe such applications of data analytics will play a crucial role in securing sustainable and efficient food production systems for the future.
Adopting Automation Technology to Optimise Resources
Besides data analytics, automation technology is also playing a role in transforming agriculture. I see automated tractors enabling farmers to work several fields at the same time with the same number of workers — or even fewer — while being able to operate equipment day and night. Similarly, automated irrigation systems that are equipped with sensors to collect information about soil and water levels are empowering farmers to use water more efficiently.
The other opportunities I foresee emerging in the field of agri-tech include the rise of digital marketplaces. Leveraging on the connectivity that the Internet and connected devices enable, I see farmers helping each other to connect better with their local customers, pool resources for improved insurance cover and lease out farm equipment. Equally promising is the rise of new irrigation systems that deploy highly targeted quantities of water and fertilisers, by using data monitoring tools that can prescribe the exact amounts of both resources to run a farm productively. Such systems help farmers economise resources while providing robust yields.
Convincing Farmers in Labour-Intensive Economies to Adopt Tech
In developing countries like India, I see agri-tech making steady inroads into the country’s farming space as innovative start-ups introduce efficient, cost-effective ways to help farmers boost agricultural productivity. Some start-ups are using artificial intelligence while others are deploying computer vision and aerial imagery analytics to help farmers make better decisions to improve yield and productivity.
A Madhya Pradesh-based start-up, for example, is using agronomic intelligence to provide input to farmers during their entire crop cycle, including tips on how to better manage their crops and soil quality. This input has reportedly led to improved productivity and higher price for their produce.
Others are deploying remote sensing technology to provide regular crop monitoring of large farmlands for timely maintenance and higher yields. Such initiatives are prompting farmers to vary land tilling, seeding, irrigation and pesticide use based on data gathered via sensors.
However, a principal challenge to the wider application of new technology to agriculture in countries like India is the lack of trust in new technology-enabled tools among farmers. Being able to demonstrate the positive outcomes of using technology in farming will be a key requirement. I am certain as more start-ups join the agri-tech field, farmers will be able to see the benefits that lie in partnering with them.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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