Will digital agriculture deliver on the hype? New research and development projects and industry case studies
Will digital agriculture deliver on the hype? New research and development projects and industry case studies
Author: Richard Heath, Australian Farm Institute | Date: 27 Feb 2017
Take home message
The P2D project, jointly funded by all RDC’s and the Federal Government, is investigating solutions for the use of big data in agriculture in Australia.
Case studies investigated as part of the project show that data being accumulated throughout agricultural supply chains are significantly changing the agricultural business environment. The case studies show the potential for decision agriculture to provide platforms that provide data to improve on-farm decision making while at the same time having significant post farm-gate impacts.
Introduction
The Accelerating Precision Agriculture to Decision Agriculture (P2D) project is a bold new initiative funded through the Federal Governments Rural R&D for profit program and all 15 Rural RDC’s. It is the first research project to have all RDC’s as partners.
The project will
- design a solution for the use of big data in agriculture.
- deliver legal guidance, consistent data systems, access to foundational datasets and recommendations for data communications to improve decision making for farm businesses.
There has been much commentary in recent times about the potential benefits that will be delivered by digital agriculture. In early 2017, the benefits remain potential rather than realised for a number of reasons. Digital agriculture encompasses a broad suite of technologies and procedures and as such can be hard to define succinctly. There are also constraints to adoption that range from technical (appropriate data) to physical (connectivity limitations) and cultural (trust in access to data).
A widely accepted definition of digital agriculture is that it involves data analytics at a scale that is generally understood as big data. Big data in turn can be defined as extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations. Beyond that simple definition there are many interpretations of digital agriculture, particularly as it is applied across the whole of agriculture and how it relates to existing precision agriculture technology.
The P2D project has concentrated on the potential for improved decision making that digital agriculture enables. The underlying assumption is that productivity and profitability improvements in agriculture can be achieved when practice change prompted by compelling data analytics provided through the collective technologies of decision agriculture is enacted.
Decision agriculture uses a more integrated and connected system of systems compared to precision agriculture which currently is more of a collection of individual technologies which may or may not be connected. By connecting multiple datasets in the cloud a level of interrogation and analysis that goes beyond a traditional precision agriculture approach will facilitate an improved decision making process that can be called decision agriculture.
The P2D project is made up of a series of sub projects that are focused on various enabling functions that will facilitate the transition from precision agriculture to decision agriculture. The framework of the project is described in Figure 1.
Figure 1. P2D Project Framework
As part of the P2D project the Australian Farm Institute has conducted three case studies into how big data is being used in agricultural supply chains in the USA. The three case studies were selected to represent different applications of the way that data can be used in a supply chain while at the same time having implications for on-farm decision making.
Case studies
HarvestMark
Background
HarvestMark provides traceability solutions from case level to individual product level for all participants along the supply chain, including large and small growers, wholesalers, and retailers. HarvestMark provides traceability information by putting a barcode on packaging, and collecting all data associated with the barcode as it travels to the consumer. HarvestMark collects and analyses four types of data: (1) traceability; (2) quality (e.g., age, appearance, freshness); (3) operational (e.g., delivery, dwell, handling, merchandising); and (4) consumer data (e.g., taste, experience, value).
With these products, HarvestMark makes the supply chain more efficient by helping all participants to manage recalls, monitor for quality, track everything associated with a product (e.g., quality, location), and ultimately collect insights from end consumers, who can scan, review, and provide feedback. Specifically, HarvestMark helps brands to make data-driven decisions and ultimately improve their top lines, and helps growers to prevent and manage recalls and adapt production to meet consumer demand.
Relevence of HarvestMark to the grains industry in Australia
HarvestMark started life as a traceability and brand protection platform for computer hardware and electronics and only moved into food and agriculture when the market opportunities were realised. Technology spill over from industries external to agriculture is going to be a significant factor in the development of new products and services.
While traceability using bar codes is not an immediately obvious solution for bulk grains logistics the principles behind the need for such a solution, being the growing desire from consumers to know where their food is coming from is equally applicable to all food crops. Digital platforms such as the HarvestMark solution go beyond simple traceability to the ability to provide feedback through the entire supply chain on quality.
Agrian
Background
Agrian Inc. is a database-backed software platform that supports compliance throughout the supply chain, from an agronomist’s recommendation to the farmer’s actual usage, ultimately helping assure safe application of crop protection materials. Agrian presents information such as: field maps, planting records, yield maps, satellite imagery, mobile scouting, crop planning and budgeting, laboratory analysis results, nutrient management and crop protection data, and variable-rate application data. The core feature of the Agrian platform is North America’s largest manufacturer product database: Agrian users can search the database by product type (e.g., fertilizer, herbicide, inoculant), manufacturer, active ingredient, registered crop or pest, and organic status, to find out detailed product and manufacturer information, as well as safety and compliance data, such as where the product is restricted.
Customers, including growers, retailers, agronomists, manufacturers and processors, and input providers, can access the Agrian platform for an annual subscription fee. Agrian helps customers optimize input usage, ensures compliance with regulatory requirements, and saves time. Agrian has also worked with several industry groups and cross-sector collaborations to promote data standards, sustainability, and efficiency in agriculture.
Relevance of Agrian to grains industry in Australia
Agrian originated from the need to have robust compliance systems for horticultural production in California; one of the most regulated states in the USA. Regulatory requirements for agriculture, particularly in relation to environmental sustainability measurements are only going to increase over time. Decision agriculture including platforms like Agrian provide the opportunity for farm equipment and record keeping software to interface and integrate with a variety of compliance and stewardship programs. The end result is that the compliance process becomes less of a burden and more integrated with standard practice. For example, at the moment statutory chemical application record keeping is a separate process that does not integrate automatically with spray monitors etc.
The Canadian field print initiative is an example of how this will work in practice. The CFPI is a Canadian government program which provides environmental best practice benchmarks for fertiliser application. Agrian have worked with the CFPI initiative to develop API’s so that the farm data collected on their platform feeds directly into the CFPI process eliminating the need to have duplicate systems for record keeping.
Farmers Business Network (FBN)
Background
The Farmers Business Network (FBN) is a software-as-a-service platform that enables farmers to access anonymous, aggregate analytics about all aspects of their farming operation, including agronomic data, pricing, and finance, as well as participate in a marketplace of services and products backed by a lowest price guarantee. FBN also includes the Seed Finder system, the world’s largest real-world seed performance database, which helps farmers save time and money on their planning while optimizing their performance.
Farmers pay $500/year to join the network, and can save up to 50% on input costs (20-30% on average). As farmers add more of their data, they unlock additional insights derived from the aggregate data from over 10 million acres supplied by a network of over 3,000 farmers. All data is anonymous and insights provided back to individuals are aggregated.
Relevance of FBN to the grains industry in Australia
FBN has been receiving a lot of attention due to its potential to disrupt the agricultural input supply chain.
The data that FBN acquires through its subscribers allows it to predict with a high level of certainty where there is likely to be need for crop inputs such as crop protection chemicals and fertilisers. Using this information FBN can target inventory in a much more precise way than traditional inventory models. Varietal information, planting rates, crop rotations etc can all be used to predict where and when crop inputs are likely to be needed.
Using this information to target specific crop inputs and production areas FBN have started their own procurement program offering crop inputs to data subscribers directly.
The FBN procurement model is a potential threat to ag input manufacturers and suppliers if they are competing on price of product alone. It is likely to lead to offerings which are based more on a package of products bundled into production systems along with significant after sales support and knowledge.
An example of packaged production systems is the Syngenta HYVIDO barley program in the UK (https://www.syngenta.co.uk/CBYG) which provides a cash back program if the HYVIDO barley does not out yield a conventional barley by at least 0.5 t/Ha in accredited comparison fields. The requirement to participate in the program however is that the HYVIDO barley has to be grown to a proscribed recipe which includes at least one application of a Syngenta PGR.
Summary
Farm data is increasingly being aggregated and provided back to farmers to help with farm decision making to improve productivity and profitability. The same data has the capacity to significantly change agribusiness models and supply chain systems. Environmental compliance systems and traceability of agricultural products will also be enhanced by farm level data collection platforms.
Acknowledgements
The Case Studies in this report were compiled under contract to the AFI by Sarah Nolet from Agthentic. (www.agthentic.com)
Contact details
Richard HeathAustralian Farm Institute
73/61 Marlborough St, Surry Hills, NSW 2010.
Ph: 02 9690 1388
Email: heathr@farminstitute.org.au
GRDC Project Code: CRD00004,
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