The world’s population is growing at an unsustainable speed. According to a report by The Guardian, we will need to produce 50 percent more food by 2050 as the increase in population demands more food supply. However, with challenges such as climate change affecting crop yields and food supplies, a food crisis may not be too far off in the foreseeable future.
To make better use of existing farmlands, farmers are looking towards technology to boost yields and to operate as efficiently as possible, prompting the agricultural industry to rapidly adopt technology, birthing Agritech to tackle some of its most pressing challenges.
Agritech is reportedly a $7.8 billion industry and is projected to be worth 13.5 billion by 2023. While the production of food remains a constant source of concern, Agritech has been pivotal in tackling food production challenges through Precision Agriculture.
What is Precision Agriculture?
Precision Agriculture is a farming management concept that utilizes data retrieved from multiple sources to provide a rationale and effective management plan for agricultural endeavors. In essence, to minimize the use of resources while maximizing yields.
Firstly, Precision Agriculture comprises remote sensing techniques utilizing Internet of Things sensors that help to monitor crop states at various growth levels and measures chemicals and temperatures to soil fertility. It involves the acquisition and processing of a large amount of data related to crop health. However, Precision Agriculture doesn’t merely revolve around information technology; it includes a broad range of other technologies as well including satelites and agriculture drones.
Machine Learning — The secret sauce to Precision Agriculture
A core mechanism behind Precision Agriculture lies in Machine Learning.The success of farming is dependent on a plethora of factors which farmers have little or no control over, such as weather and soil conditions, and temperature. The key to efficiency lies in their ability to adjust to such factors and this in turn is impacted and dependent on the availability of accurate real-time info. In essence, Precision Agriculture relies on real-time and historical data, when the data is fed into Machine Learning algorithms, it allows farmers to make more precise and targeted decisions. So farmlands can get precisely the treatment they need, that’s determined with great accuracy.
The burning question is how does Precision Agriculture help solve Agriculture’s evergreen problems?
Precision Agriculture in Disease Control
Crop disease and pests remain a pressing issue in agriculture as it can severely impact global food production and food security. Constant monitoring of crop fields by farmers is extremely time and cost consuming, as covering large swathes of land by foot isn’t sustainable in the long run. This is an area of problem where agricultural drones can tackle.
Agri-Cultural Drones – Super Sight for Farmers
In the field of things, agricultural drones are among the most popular and widely available devices that are taking the agro-arena by storm. These aerial devices are an integral part that serves as an enabler for Machine Learning in Precision Agriculture. Generally, Machine Learning and agricultural drones work hand in hand, whereby Machine Learning takes in from the input of data from each of these sources. The computer then processes the information and sends the appropriate actions back to these devices.
Aerobotics in the Future of Farming
Case in point, aerial data analytics companies like Aerobotics are making waves in the Agritech scene. The South African firm uses imagery obtained from drones and satellites, coupled with its Machine Learning algorithms, to present early problem detection services to farmers.
For instance, in the area of disease control, Machine Learning remains a vital part of Precision Agriculture in utilizing a more targeted approach in the distribution of pesticides on affected crops. Rather than spraying chemicals on a large area of land, which often results in inefficiency and incurs a higher cost, farmers are now able to pinpoint affected areas and target them specifically. A more targeted approach results in better management and, in turn, higher accuracy of disease detection.
The rate of Agritech startups and their capabilities is only expected to increase, with established Agritech firms focused on improving the existing technologies. The future of farming lies in Agritech, as it will provide more solutions to issues plaguing the industry, enabling farmers with data-driven insights. The adoption of Agritech will head mainstream with a lot of opportunities for expansion in various areas of the industry as Precision Agriculture plays its role in feeding the future.