Farmers today have a monumental challenge. The United Nations World Population Prospects 2017 study found that the current world population of 7,6-billion is expected to reach 8.6-billion by 2030. This means that global agricultural production would need to double over the next few decades to meet this demand. Added to these pressures are challenges like climate change, droughts, floods and extreme temperature fluctuations. Within the framework of the Sustainable Development Goals, which aims to end hunger and all forms of malnutrition by 2030, food security has, therefore, become a global top priority.
As a solution, the agricultural sector is now looking towards data-driven solutions to proactively plan for the generations of tomorrow.
The cream of the technological crop
A preliminary step to addressing the challenges that farmers face today, is to implement a concept called precision farming. Precision farming is expected to contribute 30% of the growth needed in agricultural production to feed the world by 2050. This involves the use of GPS-enabled equipment to monitor and collect data on plants, soil and weather conditions. Equipped with the right data, farmers will have the ability to increase yields through intelligent information. This will also be combined with artificial intelligence and machine learning for added intelligent crop management.
Machine learning is a machine’s ability to automatically learn and improve its performance without being programmed. It is becoming vital for farmers for a number of reasons:
First, it is impossible for farmers to articulate all their knowledge, making it difficult to automate many tasks. This is something, machines do very well.
Second, machines are excellent learners. By turning data into assets, these systems promise to enable farmers to accelerate innovation, drive efficiencies and create insights around some of the above-mentioned challenges.
Within the context of farming, machine learning is being deployed to automatically calculate the amount of grass available in a field available for grazing; soil types, and even irregular weather patterns. Analytics is a central success factor when driving solutions based on these data sets.
The data-centric farmer of the future
Thriving with artificial intelligence and machine learning requires successful farmers to become data-centric. But cultivating data-centricity is no small undertaking. It requires the dynamic NetApp Data Fabric that simplifies and integrates data management across cloud and on-premises to ensure the success of an artificial intelligence initiative. A Data Fabric delivers consistent and integrated hybrid cloud data services for data visibility and insights, data access and control and data protection and security. Added to this philosophy, NetApp offers the industry’s first end-to-end NVMe unified all-flash system to deliver speed and agility.
The potential gain of technological innovations can turn some of the greatest farming challenges on its head. In the pursuit of driving yield efficiency, placing data at the heart of what has traditionally been a key driver of the South African economy will be vital.
By Morne Bekker, Country Manager at NetApp South Africa