Electronic agricultural data collection, storage, analysis, and sharing
Digital agriculture, sometimes known as smart farming or e-agriculture, are tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture. The Food and Agriculture Organization of the United Nations has described the digitalization process of agriculture as the digital agricultural revolution. Other definitions, such as those from the United Nations Project Breakthrough, Cornell University, and Purdue University, also emphasize the role of digital technology in the optimization of food systems.
Digital agriculture includes (but is not limited to) precision agriculture. Unlike precision agriculture, digital agriculture impacts the entire agri-food value chain — before, during, and after on-farm production. Therefore, on-farm technologies like yield mapping, GPS guidance systems, and variable-rate application, fall under the domain of precision agriculture "and" digital agriculture. On the other hand, digital technologies involved in e-commerce platforms, e-extension services, warehouse receipt systems, blockchain-enabled food traceability systems, tractor rental apps, etc. fall under the umbrella of digital agriculture but not precision agriculture.
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Historical context.
Emerging digital technologies have the potential to be game-changers for traditional agricultural practices. The Food and Agriculture Organization of the United Nations has referred to this change as a revolution: "a 'digital agricultural revolution' will be the newest shift which could help ensure agriculture meets the needs of the global population into the future." Other sources label the change as "Agriculture 4.0," indicating its role as the fourth major agricultural revolution. Precise dates of the Fourth Agricultural Revolution are unclear. The World Economic Forum announced that the "Fourth Industrial Revolution" (which includes agriculture) will unfold throughout the 21st century, so perhaps 2000 or shortly thereafter marks the beginning of Agriculture 4.0.
Agricultural revolutions denote periods of technological transformation and increased farm productivity. Agricultural revolutions include the First Agricultural Revolution, the Arab Agricultural Revolution, the British/Second Agricultural Revolution, the Scottish Agricultural Revolution, and the Green Revolution/Third Agricultural Revolution. Despite boosting agricultural productivity, past agricultural revolutions left many problems unsolved. For example, the Green Revolution had unintended consequences, like inequality and environmental damage. First, the Green Revolution exacerbated inter-farm and interregional inequality, typically biased toward large farmers with the capital to invest in new technologies. Second, critics say its policies promoted heavy input use and dependence on agrochemicals, which led to adverse environmental effects like soil degradation and chemical runoff. Digital agriculture technologies have the potential to address negative side effects of the Green Revolution.
In some ways, the Digital Agriculture Revolution follows patterns of previous agricultural revolutions. Scholars forecast a further shift away from labor, a slight shift away from capital, and intensified use of human capital — continuing the trend the British Agricultural Revolution started. Also, many predict that social backlash — possibly around the use of artificial intelligence or robots — will arise with the fourth revolution. Since controversy accompanies every societal transformation, the digital agricultural revolution isn't new in that respect.
In other ways, the Digital Agriculture Revolution is distinct from its predecessors. First, digital technologies will affect "all" parts of the agricultural value chain, including off-farm segments. This differs from the first three agricultural revolutions, which primarily impacted production techniques and on-farm technologies. Second, a farmer's role will require more data analytics skills and less physical interaction with livestock/fields. Third, although farming has always relied on empirical evidence, the volume of data and the methods of analysis will undergo drastic changes in the digital revolution. For example, Smart farm systems continuously monitor the behavior of your animals. Giving you insight into their behavior every moment of the day. Finally, increased reliance on big data may increase the power differential between farmers and information service providers, or between farmers and large value chain actors (like supermarkets).
Technology.
Digital agriculture encompasses a wide range of technologies, most of which have multiple applications along the agricultural value chain. These technologies include, but are not limited to:
Effects of digital agriculture adoption.
The FAO estimates the world will need to produce 56% more food (as compared to 2010, under "business as usual" growth) to feed over 9 billion in 2050. Furthermore, the world faces intersecting challenges like malnutrition, climate change, food waste, and changing diets. To produce a "sustainable food future," the world must increase food production while cutting greenhouse gas emissions and maintaining (or reducing) the land used in agriculture. Digital agriculture could address these challenges by making the agricultural value chain more efficient, equitable, and environmentally sustainable.
Efficiency.
Digital technology changes economic activity by lowering the costs of replicating, transporting, tracking, verifying, and searching for data. Due to these falling costs, digital technology will improve efficiency throughout the agricultural value chain.
On-farm efficiency.
On-farm, precision agriculture technologies can minimize inputs required for a given yield. For example, variable-rate application (VRA) technologies can apply precise amounts of water, fertilizer, pesticide, herbicide, etc. A number of empirical studies find that VRA improves input use efficiency. Using VRA alongside geo-spatial mapping, farmers can apply inputs to hyper-localized regions of their farm — sometimes down to the individual plant level. Reducing input use lowers costs and lessens negative environmental impacts. Furthermore, empirical evidence indicates precision agriculture technologies can increase yields. On U.S. peanut farms, guidance systems are associated with a 9% increase in yield, and soil maps are associated with a 13% increase in yield. One study in Argentina found that a precision agriculture approach based on crop physiological principles could result in 54% higher farm output.
Digital agriculture can improve the allocative efficiency of physical capital within and between farms. Often touted as "Uber for tractors," equipment-sharing platforms like Hello Tractor, WeFarmUp, MachineryLink Solutions, TroTro Tractor, and Tringo facilitate farmer rental of expensive machinery. By facilitating a market for equipment sharing, digital technology ensures fewer tractors sit idle and allows owners to make extra income. Furthermore, farmers without the resources to make big investments can better access equipment to improve their productivity.
Digital agriculture improves labor productivity through improved farmer knowledge. E-extension (electronic provision of traditional agricultural extension services) allows for farming knowledge and skills to diffuse at low cost. For example, the company Digital Green works with local farmers to create and disseminate videos about agricultural best practices in more than 50 languages. E-extension services can also improve farm productivity via decision-support services on mobile apps or other digital platforms. Using many sources of information — weather data, GIS spatial mapping, soil sensor data, satellite/drone pictures, etc. — e-extension platforms can provide real-time recommendations to farmers. For example, the machine-learning-enabled mobile app Plantix, Krisikart India diagnoses crops' diseases, pests, and nutrient deficiencies based on a smartphone photo. In a randomized control trial, Casaburi et al. (2014) found that sugarcane growers who received agricultural advice via SMS messages increased yields by 11.5% relative to the control group.
Finally, digital agriculture improves labor productivity through decreased labor requirements. Automation inherent in precision agriculture — from "milking robots on dairy farms to greenhouses with automated climate control" — can make crop and livestock management more efficient by reducing required labor.
Off-farm/market efficiency.
Besides streamlining farm production, digital agriculture technologies can make agricultural markets more efficient. Mobile phones, online ICTs, e-commerce platforms, digital payment systems, and other digital agriculture technologies can mitigate market failures and reduce transaction costs throughout the value chain.
Rarely does one single digital agriculture technology solve one discrete market failure. Rather, systems of digital agriculture technologies work together to solve multifaceted problems. For example, e-commerce solves two efficiency issues: difficulty matching buyers and sellers, especially in rural areas, and the high transaction costs associated with in-person, cash-based trade.
Equity.
Digital agriculture shows promise for creating a more equitable agri-food value chain. Because digital technologies reduce transaction costs and information asymmetries, they can improve smallholder farmers' market access in a number of ways:
Financial inclusion.
Digital agriculture technologies can expand farmers' access to credit, insurance, and bank accounts for a number of reasons. First, digital technology helps alleviate the information asymmetry that exists between farmers and financial institutions. When lenders decide a farmer's credit ceiling or insurance premium, they are usually uncertain about what risks the farmer presents. Digital technology reduces the costs of verifying farmers' expected riskiness. The Kenyan company M-Shwari uses customers' phone and mobile money records to assess creditworthiness. Organizations like FarmDrive and Apollo Agriculture incorporate satellite imagery, weather forecasts, and remote sensor data when calculating farmers' loan eligibility. Drone imagery can confirm a farmer's physical assets or land use and RFID technology allows stakeholders to monitor livestock, making it easier for insurers to understand farmers' riskiness. In all instances, low-cost digital verification reduces lenders' uncertainty: the questions "will this farmer repay the loan?" and "what risks does this farmer face?" become clearer.
Second, digital technology facilitates trust between farmers and financial institutions. A range of tools create trust, including real-time digital communication platforms and blockchain/distributed ledger technology/smart contracts. In Senegal, a digitalized, supply-chain-tracking system allows farmers to collateralize their rice to obtain the credit necessary for planting. Lenders accept rice as collateral because real-time, digital tracking assures them the product was not lost or damaged in the post-harvest process.
Market inclusion.
Middlemen often extract exorbitant rents from farmers when purchasing their harvest or livestock for several reasons. First, smallholders in remote areas may be unaware of fair market prices. As a result, middlemen (who typically have better information about market conditions and prices) accrue significant market power and profits. A study conducted in the central highlands of Peru found that farmers who received market price information via mobile phone SMS increased their sales prices by 13-14% relative to farmers without access to the information. Second, smallholders produce tiny harvests compared to large producers, so they lack bargaining power with middlemen. If smallholders can aggregate or form a cooperative to sell their products together, they have more leverage. Online platforms and mobile phones can facilitate aggregation, such as Digital Green's Loop app. Third, connecting producers with final consumers can eliminate intermediaries' monopsony power, thereby raising producer profits. As mentioned above in the efficiency section, e-commerce or other market linkage platforms can connect a small farmer directly to consumers around the world.
Potential inequities resulting from digital agriculture.
Though digital technologies can facilitate market access and information flow, there's no guarantee they won't exacerbate existing inequalities. Should constraints prevent a range of farmers from adopting digital agriculture, it's possible that the benefits will only accrue to the powerful.
Environment.
Boosting natural resource efficiency is the "single most important need for a sustainable food future," according to the World Resource Institute. As mentioned in the on-farm efficiency section, precision farming — including variable rate nutrient application, variable rate irrigation, machine guidance, and variable rate planting/seeding — could minimize use of agricultural inputs for a given yield. This could mitigate resource waste and negative environmental externalities, like greenhouse gas (GHG) emissions, soil erosion, and fertilizer runoff. For example, Katalin et al. 2014 estimate that switching to precision weed management could save up to 30,000 tons of pesticide in the EU-25 countries. González-Dugo et al. 2013 found that precision irrigation of a citrus orchard could reduce water use by 25 percent while maintaining a constant yield. Basso et al. 2012 demonstrated that variable-rate application of fertilizer can reduce nitrogen application and leaching without affecting yield and net return.
However, precision agriculture could also accelerate farms' depletion of natural resources because of a rebound effect; increasing input efficiency does not necessarily lead to resource conservation. Also, by changing economic incentives, precision agriculture may hinder environmental policies' effectiveness: "Precision agriculture can lead to higher marginal abatement costs in the form of forgone profits, decreasing producers' responsiveness to those policies." In other words, holding pollution constant, precision agriculture allows a farmer to produce more output — thus, abatement becomes more expensive.
Off-farm, digital agriculture has the potential to improve environmental monitoring and food system traceability. The monitoring costs of certifying compliance with environmental, health, or waste standards are falling because of digital technology. For example, satellite and drone imagery can track land use and/or forest cover; distributed ledger technologies can enable trusted transactions and exchange of data; food sensors can monitor temperatures to minimize contamination during storage and transport. Together, technologies like these can form digital agriculture traceability systems, which allow stakeholders to track agri-food products in near-real-time. Digital traceability yields a number of benefits, environmental and otherwise:
Enabling environment.
According to the McKinsey Industry Digitization Index, the agricultural sector is the slowest adopter of digital technologies in the United States. Farm-level adoption of digital agriculture varies