The role of future technologies in Agriculture

The Agribusiness Bulletin

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The role of future technologies in Agriculture

In the next 30 years, it is forecast that there will be an additional 2.2 billion people to feed, clothe and shelter than there are today. This is the equivalent of almost two of today’s Chinas, with global population forecast to rise from 7.55 billion (2017) to 9.77 billion (2050). At the same time, land and water resources are dwindling through urban encroachment, pollution and land degradation, and environmental sustainability and ethical production is in increasing demand from consumers. This means that there needs to be a fundamental shift in the way we produce food, as we seek to produce much more with much less¹.

There are many ways to do more with less. For example, through more capital-intensive (rather than land-intensive) production systems, such as protected cropping and vertical farms, through better breeding and genetics to increase yields, or through reducing our food waste. A further way is to improve the sophistication of farming techniques through artificial intelligence (AI). Although a lot of this is already happening, the next 10 years is set for an explosion.

Types of technology currently in use in agriculture

An increasingly common technology in agriculture today is the use of drones or Unmanned Aerial Vehicles (UAVs). With the advancement of UAV’s capabilities, integrating AI technology has made precision farming a reality. Surveys such as infrared mapping, gathering crucial information like crop condition, could cost farmers as little as $5 per acre. Once the survey data is received and automatically analysed, the farmer could use this information to boost crop yields by up to 20 percent. The time savings in undertaking these types of surveys could be reduced from a couple of days to a couple of hours. In agriculture, UAV’s are used for crop dusting, seed sowing, precision agriculture, weed and pest monitoring and farm management. All made possible by the integration of autonomous controls and crash avoidance systems.

More recently, hyperspectral, multispectral and thermal sensors that collect and process information from an electromagnetic spectrum are attached to UAVs to capture data relating to soil moisture levels, crop density and health of the plants. Farmers can then use this information to make decisions on pest management, irrigation planning, and to get better yields from crops. With a combination of GPS, Photogrammetry and Lidar Cameras mounted on small UAV’s, collection of large amounts of photos automatically get analysed by the AI software and get stitched together to give an accurate 3D rendering of the landscape. These applications are used for surveying and provide data to assist the farmer on decisions regarding productive placement of crops and water catchment areas. Covering large amounts of area and rugged terrain, this was previously done mostly by full sized aircraft with large amount of human hours spent collating and analysing the data – an expensive exercise.

What technologies can we expect in the future?

The farm intelligence collected through drones and UAV technology and the associated software applications is a game changer. The conversion of this data into usable information enables whole farm planning, monitoring, better precision of detailed problems, and individual treatment of plants and animals. For example, in the future, farmers will be able to see 100% of problem areas on a property within a matter of minutes, wherein walking a paddock visually you would see approximately 10%. UAV’s can save valuable time and cost while improving farm knowledge through collection and assimilation of millions of data points or ‘big data’.

Furthermore, in the future, AI software together with will be able to analyse this big data and then use it to direct robotic systems to undertake specific tasks, including spraying, mustering or harvesting. It will also be able to predict harvest periods, packing needs and logistics requirements. All of which assists in farmers being in a position to extend their bottom line.

Examples of emerging technologies are robots being used together with machine learning to enable visual data to make decisions on whether or not a plant is a weed or contains unwanted pests, the robot then blasts a measured amount of pesticides on the pests assisting in eradication. They can also identify ripe fruit and pick the fruit at the ultimate stage of its life.

These applications are all in development stages and, looking further afield, the possibilities seem endless. Imagine a farm with no farmer, where a seed automatically gets planted based on the optimum weather conditions, forecast and location, crops get irrigated with precision when required, cattle get herded and fed, pests are removed, fruit and vegetables are harvested, sorted, packaged and delivered by order. All the farm equipment work in sync, sharing data, making decisions and automatically applying optimal actions from seed to end product.

What impact will these technologies have on the sector?

Globally AI in Agriculture growth is expected at CAGR of 24% by 2024 and Asia Pacific is predicted to be the fastest growth region.2With such a diverse range of applications, the growth of AI is likely to impact across all agricultural sectors including aquaculture, viticulture, cropping, forestry and livestock farming. Josh Voelker of Precision Hawk, one of the top 30 companies in the world for drones, predicts 80% of all drone usage across the world will be in agriculture.3 AI will naturally mean less labour as farms become larger and more automated4 and it’s estimated that AI could replace $32.4b worth of human labour and services in the agricultural industry, and a total of $127 billion across several industries⁵.

Conclusion

With the advancement in these technologies and integration of AI into the future, the agribusiness sector is in a sound position to meet the needs of a rising population. While there are some world changing benefits with the implementation of Artificial Intelligence across all industries, applications and capabilities need to be regulated and managed with social responsibility as a priority.

Author

• Beau Thomson, Financial Advisory

Sources

1. https://pursuit.unimelb.edu.au/articles/editing-farming-the-future
2. https://globenewswire.com/news-release/2018/03/12/1420234/0/en/Global-Artificial-Intelligence-AI-in-Agriculture-Market-Providing-Precision-Farming-Techniques-to-Reduce-Production-Cost-and-Chemicals-is-expected-to-witness-CAGR-of-24-3-by-2024-E.html
3. https://www.thechronicle.com.au/news/farmfest-why-drones-are-future-agriculture/3186587/
4. https://pursuit.unimelb.edu.au/articles/editing-farming-the-future
5. https://www.businessinsider.com.au/drones-could-replace-127-billion-of-human-labor-2016-5?r=US&IR=T