Following the introduction of mineral fertiliser, mechanisation and the industrialisation of the production process, digital agriculture brings the next major movement. It is part of the Fourth Industrial Revolution (4IR).
Digital agriculture refers to the use of agricultural technology (AgriTech) and data-driven innovations to predict outcomes and guide the producer through every phase of operations on the farm. There are many benefits:
Some of the tools for digital agriculture are outlined in the following headings.
Robots can automate tasks like planting, weeding and manufacturing.
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A shortened form of “application software”, an app is a computer programme designed to run on cell phones and tablets. There are now billions of apps available including several thousand agriculture-related ones.
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Digital technologies are fundamental to artificial intelligence. AI looks across a farmer’s operations, analyses data – soil composition, weather, moisture, temperature etc – and provides insight on how to optimise resources and equipment.
AI can advise on matters like early treatment to combat mastitis in dairy cattle (a result of interpreting data from thermal imaging cameras) or let the owner know on the best time to sell cattle after measuring the weight and muscle mass of cattle (through 3D cameras). It can watch the movement of thousands of chickens and analyse behaviour to identify possible problems, or use microphones above pig pens to monitor conditions.
This degree of monitoring makes agricultural operations are more profitable.
An example could be a pair of “smart” glasses used by feedlot producers to remotely attend livestock auction …
Tractors being driven from a laptop is not new, but some tractor models do not even have a seat for a driver now! The Autonomous Farm Equipment Market size was valued at US$72.3 Billion in 2022, and is projected to reach a revised size of US$192.1 Billion by 2032 (Spherical Insights, 2023).
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Data has become a valuable global commodity. But it is much more than simply information: in expert hands, it is intelligence.
Already, analysts are finding ways to turn big data — the immense stocks of information collected in computers worldwide — into an invaluable resource for planning and decision-making. It is helping accelerate the development of robust responses to some of the most pressing challenges of our time: climate change/variability, food insecurity and malnutrition, and environmental degradation. It is transforming the world of genomics and crop breeding and revolutionizing disciplines from climate modelling to agronomy.
Source: https://blog.ciat.cgiar.org/cgiar-platform-for-big-data-in-agriculture/
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Blockchain “has the potential to usher in an era of autonomous digital commerce” (Lemmer, 2019). According to the UN Food and Agriculture Organisation (FAO), blockchains have been applied to areas like (i) Overseeing farm inventory (ii) Managing land records (iii) Enhancing agricultural supply chains (iv) Fair pricing (v) Mobile remittance for small farmers (vi) AgTech IoT Optimisation (vii) Fair Pricing, and (viii) Managing and modernizing farm management software.
On its website, find FAO (and partners) documents which include:
Some articles:
See separate page.
See “Precision farming” page.
The Internet of Things (IoT) is tangible for today’s farmers. All the data, be it from sensor or satellite, feeds into cell phone apps or software and a communication between farm equipment (machines, implements, infrastructure etc) occurs. Every part knows where it stands in relation to the other parts. And so, for example, it is easier to prevent row overlap when running multiple machines at the same time.
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See precision farming page.
The use of satellites has changed the world and how information is passed on. Apart from the bird’s-eye advantage, there is no need to roll out infrastructure in rural (and urban) areas which requires maintenance and which can go missing. The always-on status offers confidence.
Data from satellites is used to estimate crop yields, but can also indicate crop health and maturity. This allows for early warnings for crop failure and famine.
Land is mapped digitally and in very helpful details, without the services of cartographer required. Satellite information can be combined with data obtained from drones/UAVs and sensors to sharpen the accuracy and usefulness of the information.
This makes smart irrigation and precision farming possible.
Sensors monitor and measure conditions and provide data, be it for soil or weather conditions, movement amongst livestock or even how full a distant water crib is. A crop may require more water or fertiliser in a particular part of the field, or a cow may spend less time sitting down because it is on heat and requires a bull, for example. A planter using AI from a sensor to understand the ground conditions and alter planting settings automatically is envisioned in the near future (Gagliordi, 2018).
Sensors are “the Digital Nervous System of the Internet of Things” (Purnell, 2016).
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Various software is available for the farmer, ranging from financial programmes to administration and management programmes. These cover the different types of livestock, crops and functions on the farm. The latter includes irrigation scheduling, fertilisation, tank control within a cellar (wine), packhouse control, payroll software. Programmes can monitor weather elements, soil moisture, pests and diseases, vehicles and fuel consumption etc.
The advantages of software include:
In addition to being an enhanced information and decision making tool for the farm, it also becomes an invaluable way of bridging the space between producer and market. Traceability – the requirement of being able to track the field or animal from where a product came – makes software crucial.
Many on-farm software programmes applicable to animal breeding are available for producers, combining the functionality of herd management with on-farm recording. Find details of livestock computer programme (Software) providers on the “Animal Improvement and breeders” page. Several companies offering inputs also supply accompanying software.
3D will be used to manufacture replacement parts for farm implements and vehicles, or, by utilising genetic research, to produce meat or other food products.
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This includes computer-simulated images or environments. This can be useful in the training of farmworkers, for example (Lemmer, 2019).
Some articles and points of interest:
Opportunity or threat? Digital agriculture is disruptive to the big industry manufacturers and their business model of the past 50-60 years (Blackmore, 2018). It is small start-up companies with no investment in the past that are driving the experimentation in new technology, specifically new machines.
Workers in all countries are likely to be negatively affected by the Fourth Industrial Revolution, and how countries and their workforces adapt to the changes in skills sets will increasingly influence national narratives (Hlatswayo, 2018; Ngcwangu, 2019).
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Source: Wessel Lemmer
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Associations
Training and research
Companies
See the earlier references on this page.
