What is digital agriculture?

Digital agriculture has diverse meanings, origins and applications. Digital agriculture is about integration – the science of genomics and genetics, soil nutrition and crop  science,  meteorology and hydrology, software engineering, cyber-physical hardware design and manufacture, agribusiness and innovation in business  models, finance and investment, supply chain logistics, market research and marketing. 

Effective digital agriculture should integrate the key elements of agriculture – the biological and biophysical, with the mechanical, the environment with people, investments with markets and producers with consumers.

The impact of digital agriculture should be productivity gains for low cost investments, upskilling rather than deskilling, increased production and quality for lower price, improvement in land as an asset, and increased sustainability of the farming enterprise through sustainable land and farm management practices. 

Some of the key application areas of digital technology in agriculture include:

• Farm system management
• Genomics, genetics and crop science
• Supply chains and markets
• Financial, economic and biophysical data capture, integration and analytics.
• Connectivity and coordination of devices, automated cyber-physical infrastructure, information, knowledge and strategy through the internet of things

As digital technology moves from novel to pervasive across an industry, as it has in social media, disruption will become the norm. Agriculture is yet to experience the full impact of digital technology and the pace of change being experienced in more technologically dependent industries such as biotechnology, aeronautics, mining, and advanced manufacturing.

Digital should be about connectedness, it should be about having better knowledge to predict outcomes, or at least increasing confidence that an outcome will occur. Digital is meant to free up time, energy, space to enable more innovative thinking.

The potential impact of digital agriculture

Recent estimates of productivity gains possible through digital agriculture published in the Farm Policy Journal (Heath, 2018, 9) pointed to:

A 25% boost to the value of Australian agriculture ($20.3 billion increase from 2014–15 GVP) with all sectors benefitting. .. biggest cross-sectoral gains were labour savings from automation ($7.4 billion), genetic gains through objective data ($2.9 billion), closer tailoring of inputs to needs ($2.3 billion), and enhancements to market access and biosecurity ($1 billion). 

Digitising knowledge, information and data

Agriculture is beginning to benefit from the digitisation of data, a critical channel to capturing data on a streaming basis rather than intermittently. Streaming data, a fundamental feature of big data (the other key dimension being diversity/complexity) is essential to building the evidence base needed for effective decision making. This applies at multiple levels from product, to producer, to supply chain, to local, regional, state, national and international development, policy and governance decisions, as well as investment, divestment, and diversification decisions.

Digital technology is only ever a means to an end. The end may be decision making, though it can be transparency/provenance, quality, communication, pricing, market connectivity, market power, market access, market growth, responsiveness and agility or simply enhanced market intelligence.

Coordinating cyber-physical systems - artificial intelligence and machine learning

Digital technologies are fundamental to artificial intelligence, and its lesser sibling machine learning. AI and ML have wide application across finance, genomics, robotics, crop science, climate modelling, and the integration of disparate data sources. AI is essential to precision farming with and without robotics. Automation can drive efficiency and overcome labour shortages. AI increases predictive ability, the major limiting factor facing agriculture.

Assumptions about the internet of things include eventually fully automating production, administration, systems management, transport and logistics, and even market selection as well as market access. While this scenario is rare currently, supported only by exemplar cases, this is a window to a future that is closer than many anticipate. In any area of technology there is an individual, a farm, corporation, institution, government or agency working vigorously on the solution. Enabling technology platforms will also assist the rapid integration of what may currently seem disparate solutions.

Digital is at the heart of genetics and genomics

The impact of genomics in agriculture is allowing producers to increase yield, reduce the need for chemicals as fungicides, herbicides, insecticides and nematicides. New plant and animal varieties ad variations to breeding is having a massive benefit to those producers targeting high value markets internationally as well as domestically.

Agribusiness transformed

Remote management and spatial flexibility will add to productivity. From the farmer who installs a cistern sensor in his well, giving him a remote readout and saving him four hours driving a day to make sure his cattle are well watered. To the full implementation of mesh networks for pre and post-harvest measurement and performance monitoring integrated with market and consumer data to ensure the peas that are sold on the spot market are sold in peak condition for the highest price.  These examples are already in place in Queensland and are being supported by UQ technology, knowhow and expertise. 

New digital technologies such as blockchain and distributed ledger are seen to be enablers for coordination and transparency across supply chains, supporting provenance and value adding. However blockchain is also being used by major players in value chains to maintain and increase their bargaining power over the chain.

For example a project on building farm financial models, supported by the rapid uptake of accounting systems such as Xero and MYOB,  I am leading is designed to enhance the evidence base for better decision making at a number of levels. However the market and competitive intelligence it provides can also be used to stifle competition in order to gain market power.

Accessing new markets 

Connectedness may be about data, but technology is almost always about people, so digital agriculture should be about connecting with people more effectively. That could mean producers having greater depth of knowledge about how their supply chain partners operate, or who in a particular Chinese city is buying their product and why. Deep learning is a term associated with AI. Deep learning techniques can be as valuable in targeting untapped niche and meganiche markets as they can for integrating the omics to enhance animal and crop science.

Adoption of digital agriculture technology

Agriculture takes a lead in some areas of technology adoption such as genetics and genomics, however lags in other areas of adoption such as financing instruments, automation and market access. Lead times in bringing on and adopting new technologies can be long. As usual the story isn’t just about the technology, it’s usually about people. Investment and adoption decisions are risk based decisions, and this is one of the greatest hurdles for farmers, which are often asset rich but cash poor.

Adoption also often depends on enabling technologies. Digital connectivity has long been an issue in regional Australia, and continues to be. Without the resolution of this roadblock adoption of digital agriculture will remain patchy.

Will there be a net socio-economic benefit nationally and at the regional levels?

There are countervailing effects of digital and digitisation – greater productivity and improved business models on farms will lead to improved returns, and the potential for greater investment in the agricultural sector as the uncertainty for investors is reduced. This will drive economic growth in rural and regional Australia. However digital technology means that fewer jobs may be required on farms, and that many services can offered remotely. So the socio-economic impacts may be a net negative in many regional areas. Nonetheless improvements in productivity, profitability, balance sheets, investment and diversification all potentially enabled by digital will bring direct economic benefits to regions.

The ability to counter the effects of climate change more effectively will also have positive environmental effects as well as productivity and profitability benefits. In the medium to long term, predictability will provide a strong evidence base on which to make decisions about geographical and product diversification. The enhanced predictiveness and predictability will assist in planning around weather events of greater frequency and severity to maintain a growth trajectory for individual farms and regions. 

Responses by farms, institutions, governments supply chain partners and consumers to the impact or input of digital technologies will occur at different speeds. Digital technologies can cause information asymmetries, but also offer solutions to those same asymmetries.