From the earliest days of recorded history, when ancient Egyptians began diverting the waters of a flooding Nile in order to irrigate their crops, agriculture has been inextricably linked with technology. Humans ever since have been faced with the existential question: How do we utilize the resources at our disposal to feed more people, safely and sustainably?
To answer, we’ve made advancements in engineering, harvesting, cultivating terrain, pasteurization, selective breeding and new fertilizers. Greater production brought about a need for safe storage and transport, initially via pickling and curing, and later through refrigeration. These technologies have helped us survive inhospitable growing environments, nutrient-deficient soil, natural disasters, unpredictable weather, government policies, economic downturns and disease of all kinds, including, we hope, COVID-19.
In fact, as each crisis exposes new gaps in the system, it also arguably hastens innovation.
Consider the Great Famine (or the Irish Potato Famine), which devastated Ireland in the 1840s and forever changed the economic and demographic landscape of the nation and beyond. The blight, which was first seen in the potato crop of the Eastern United States in 1844, likely traveled across the Atlantic on ships out of the ports of Baltimore, Philadelphia or New York. By 1846, the disease had claimed three-quarters of Ireland’s harvest and devastated its seed potatoes. More than a million people died of hunger there, as well as 100,000 more outside; a million more fled Ireland.
In its aftermath, consolidation washed over rural Ireland, and there was as an increased focus on livestock: More than half of Ireland’s land was repurposed for grazing. Some also argue that there was a higher rate of technological adoption, as farms short on labor were helped by automated crop sprayers, harrows, reapers and more.
We’re still understanding how COVID-19 will impact the food supply. But just Irish economic historian Cormac Ó Gráda argues that Ireland was relatively well-positioned to handle the famine—and that, if the blight had been delayed by a few decades, the outcome might have been significantly different—so too are today’s innovations creating an essential hedge. There are now opportunities for everyone from small farmers to commodity traders to harness the powers of artificial intelligence, predictive analytics and machine learning to better manage resources, reduce waste and keep the whole system running efficiently.
To the immense credit of farmers, processors and transporters worldwide, the global food supply has largely remained intact since the onset of the COVID-19 pandemic. Still, like every other industry in the world, agriculture has a COVID-related minefield to navigate.
Early on, on-farm issues “lagged” the crisis itself, with the impact most strongly felt “downstream,” in the beleaguered restaurant industry, for instance. There was also a misconception that the virus was an issue for densely populated areas but would not pose a great threat to rural areas. Not quite British Prime Minister Sir Robert Peel writing in October 1846 that there was “always a tendency to exaggeration in Irish news,” but a damaging miscalculation nonetheless.
COVID has refused to confine itself to urban centers, and concerns have begun to swim upstream. By the pandemic’s onset, the current harvest cycle’s crops had been planted, and animals raised, according to Chinese researchers. Crops and livestock for the next season (at least) are now at risk and, given the sheer size and scope of China’s (and the United States’) food industry and economy, the underlying threat has global ramifications.
With the pandemic (and accompanying economic risks) persisting in the United States and a second wave spreading across Europe, there’s a growing fear that additional closures and lockdowns could threaten the global food supply at a time when population explosion will require 60 percent more food production by 2050.
Luckily, today’s “smart systems”— harnessing the powers of artificial intelligence (AI), predictive analytics and machine learning (ML)—can manage resources, optimize ordering, keep supply chains running efficiently and reduce waste.
Global revenue from AI in agriculture is poised to grow at more than 30 percent annually, from $671.6 million in 2019, to $11.2 billion by 2030, which means that what feels antiquated today will be downright ancient in short order.
A number of world’s top technology and agriculture companies (IBM, Microsoft, Google, Bayer, Deere & Co. and AGCO Corp., among others) have invested in the development and deployment of these technologies. Corteva Agriscience, the agricultural division of DowDupont, now operates the largest agricultural drone fleet in the world, with 400 distributed across three continents.
Still, the future of farming lies not only with the giants but with a number of exciting upstarts.
A pioneer in the use of blockchain in supply chains, Oregon-based Provenance was founded in 2013, inspired by a frustration with the lack of transparency about products’ journey through the supply chain, as well as their impact. Provenance’s technology has evolved over time to “not just track a product as it moves across a supply chain, but to illustrate and improve upon the impact of those products on the environment, local communities, and, eventually, the consumer,” according to a company spokesperson.
Thanks to services and solutions provided by the likes of San Francisco-based Ripe.io; TE-FOOD, a company based in Germany, with operations in Hungary and Vietnam as well; Oregon-based; and Virginia-based 4P Foods, businesses can use intimate knowledge of products they purvey as a point of differentiation, positioning them to thrive in the longer term, as well.
Australian startup The Yield’s sensor-based system, “Sensing+”, provides real-time and historical data on climate, crop health and growth to all parts of the value chain–from field workers, to engineers and agronomists, to finance managers and business owners. The system is equipped to carry out intelligent irrigation, where sensors in a field monitor a range of factors and adjust watering schedules based on prevailing conditions. It can also identify threats to a crop and, through precision spraying, target only weeds and pests, with only the appropriate amount of the correct herbicide. By distinguishing crops from weeds, and then identifying at-risk crops, healthy crops are spared from herbicides.
Similarly, livestock farmers using AI-based livestock monitoring systems like “Ida,” designed by Netherlands-based Connecterra, can, in real-time, monitor each specific animal’s movements, feedings and health, while also assessing data regarding herd size and genetic characteristics that may be predictive of medical risks.
Predictive analytics and machine learning used in most trading platforms have a role to play in agricultural finance as well. Synthesizing historical harvest and soil data, along with forward-looking weather forecasts, smart systems can generate robust financial forecasts. These tools provide valuable, data-driven insights to investors, business owners and lenders regarding expected profitability and risk factors – like volatility in commodity prices, a key area in which UK-based commodity risk management firm Stable specializes.
Smart systems also benefit the supply chain all the way down to consumers, who, more than ever, are concerned with the origin stories of their food products. Even without the resources of the giants, small farmers and artisanal and e-commerce-only food companies that have embraced blockchain and other technologies to provide customers with unprecedented transparency into the life cycle of their food have seen business boom during the pandemic.
It’s never been clearer that optimizing resource use and identifying risk factors are the keys to securing the world’s food supply. During this time of crisis, we need to lean further into technology and sustainably provide high quality foods to a larger portion of the global community.