Driving Profitability and Sustainability: The Smart Agriculture Double Dividend

According to the United Nations (UN), the world’s population reached 8 billion in mid-November 2022. In 1950 it was 2.5 billion, meaning the population more than tripled in 72 years. Moreover, the world’s population is expected to increase by nearly 2 billion in the next 30 years, to reach 9.7 billion in 2050, and the UN estimates it could peak at nearly 10.4 billion in the mid-2080s.

The UN has also reported that the world is facing a widespread hunger crisis, saying: “After decades of progress in combatting hunger, the number of people facing acute food insecurity is rising again due to the combined impact of armed conflict, climate change and the cost-of-living crisis.”

Challenges

Understandably, ensuring food security is important now and will be even more so in light of the population growth predictions. But providing that security is not going to be easy. Farmland and rural spaces are being lost to urban development. Also, a recent Geographical magazine article reported that the world is losing healthy land at a rapid rate as a result of desertification, stating “[d]ata shows at least 100 million hectares of healthy land is lost each year to desertification, drought, and land degradation.”

The article quoted Barron Orr, lead scientist for the UN Convention to Combat Desertification (UNCCD): “Land degradation is the result of human activities that exploit the land, leading to a decline in its utility, biodiversity, fertility and overall health. Our current land use and management practices are the main drivers of land degradation. They cause soil erosion worldwide at a rate up to 100 times faster than natural processes can replenish it.”

In addition, farming is facing resource shortages—one of which is water (see figure 1).

Figure 1. Agriculture uses about two-thirds of the world’s freshwater supply. (Source: World Bank, Schroders, July 2021)

And in many countries, there are labor and skill shortages with which to contend; and a Newsweek article from March 2024 reported: “With roughly 2.4 million farm jobs needing to be filled, according to the American Farm Bureau Federation, the current system's restrictions on year-round labor contribute to the farming crisis by inadequately supporting the full spectrum of agricultural labor demands.”

Big Data

Smart agriculture (a.k.a. smart farming) is heralded as the solution to the above problems and core to future agribusiness. Indeed, market research company Statistica puts the value of smart agriculture at $15 billion in 2022 and predicts the market will be worth $33 billion by 2027.

A variety of technologies are used to create a smart agriculture ecosystem (see figure 2). Integral to the ecosystem is “big data,” the term relating to the collection, analysis and (making) appropriate use of a large volume of data. The technologies used include in-field sensor-based IoT devices for monitoring temperature, humidity and soil health and drones fitted with different types of cameras (RGB, multispectral, hyperspectral, for instance) for monitoring crop health, satellite imagery and GPS.

Figure 2. The smart farming ecosystem

The big data is available for human analysis and interpretation but the tasks are increasingly being performed by artificial intelligence (AI); this has given rise to AI-based big data services, with market.us estimating “[t]he global AI In Agriculture market size is expected to be worth around USD 10.2 billion by 2032 from USD 1.5 billion in 2023, growing at a CAGR of 24.5% during the forecast period from 2022 to 2032.”

Within this ecosystem of big data, edge-processing is playing an increasingly important role. For example, machine learning (ML) algorithms are used in “smart” sensor-based systems to create ML models upon which predictions are made at the location at which the data is collected. This reduces the volume of data that needs to go to the cloud, is more secure and, above all else, enables real-time decisions.

Sustainability

The use of big data, particularly when it includes real-time information about soil or plants at a precise location, makes possible precision agriculture (PA), which the US Government Accountability Office says involves “…collecting, analyzing and taking actions based on data. It can help the agricultural sector meet increasing demand for food products, while also helping farmers improve efficiencies such as through reduced input costs.”

PA sees the application of inputs such as seeds, fertilizers, pesticides and water, only where they are needed and in optimum quantities. This greatly reduces waste (and as figure 1 showed, 45% of freshwater used in agriculture is wasted), which is a big step in making agriculture more sustainable. Indeed, the U.S. Department of Agriculture (USDA) defines Sustainable Agriculture as “…farming in such a way to protect the environment, aid and expand natural resources and to make the best use of nonrenewable resources.”

The USDA adds that sustainable agriculture is effectively an integrated system of plant and animal production practices with a site-specific application that will over the long-term: satisfy human food and fiber needs; enhance environmental quality and the natural resource base upon which the agriculture economy depends; make the most efficient use of nonrenewable resources and on-farm resources and integrate, where appropriate, natural biological cycles and controls; sustain the economic viability of farm operations; and enhance the quality of life for farmers and society as a whole.

As mentioned, PA uses technologies such as GPS to make farms more efficient. For example, farmers can use auto-steering equipment to precisely plant a field. GPS can also be used within systems to monitor the location and health of livestock. Figure 3 shows the extent to which PA is practiced in the US.

Figure 3. Precision Agriculture in the USA

In addition to big data being useful in PA, if the data also pertains to the condition of farm equipment and machinery, this makes predictive maintenance possible. This is the practice of servicing machinery based on wear and tear rather than an elapsed period of time (e.g. calendar year) or so many recorded hours of use. For example, accelerometers are used to measure vibration levels, as an increase in vibration can be indicative of bearings failing. Monitoring vibration, along with parameters like temperature and current draw, can also provide the earliest warning of imminent failure and enable equipment to shut down before damage is done.

Predictive maintenance is used extensively in many industries, including manufacturing, mining and petrochemicals, but the beauty of it contributing to the big data within the agriculture sector is that servicing can be synchronized with the equipment’s near- and short-term (planned) requirements for use, the weather (if applicable) and the likelihood of the machinery being needed for an emergency.

Farm to Fork

Making agriculture more sustainable involves more than improving yield and reducing waste. According to an article by Foresight, the CMCC observatory says regarding climate policies and futures: “…agriculture currently generates 19–29% of total greenhouse gas (GHG) emissions, consumes large amounts of natural resources, results in biodiversity loss and negative health impacts (due to both under- and over-nutrition) and does not allow fair economic returns and livelihoods for all actors, in particular for primary producers.”

The article also mentions the European Union’s Farm to Fork strategy, part of the European Green Deal, and how it is aiming to make food systems fair, healthy and environmentally friendly. The strategy stresses that today’s food systems—which account for nearly one-third of global GHG emissions, consume large amounts of natural resources and result in biodiversity loss and negative health impacts—must be redesigned.

The strategy also states that “[p]utting our food systems on a sustainable path also brings new opportunities for operators in the food value chain. New technologies and scientific discoveries, combined with increasing public awareness and demand for sustainable food, will benefit all stakeholders.”

In summary, profitability and sustainability can go hand in hand. They need not, and should not, be mutually exclusive objectives. Thankfully, both can be achieved through smart agriculture, where the agriculture sector (as a whole) is essential for human life and plays a crucial role in global economic development.