Digital Agriculture: A Revolution in the Making
Agricultural production has been growing globally at an annual rate of 2-4 percent over the past 50 years, while the arable land has increased by only 1 percent per year. In addition, as emphasized by the Food and Agriculture Organization (FAO) of the United Nations, climate change poses a major challenge to the future of agriculture, as it must cope with rising temperatures, humidity, and scarcity of water—all in the context of a steady population growth. The global population has crossed 7 billion people in 2017 and is expected to grow close to 10 billion by 2050. What this means, according to the FAO is that we need to produce 70 percent more food compared to what we have produced in 2006.
The onset of digital technology has revolutionized many industries and occupations, and agriculture is no exception at all. Digital agriculture is the use of digital devices and technologies to analyze spatial or temporal data, and leveraging the resulting insights to improve agricultural productivity and sustainability. Big data and advanced analytics, AI, IoT, robotics, remote and proximal sensing, informatics and communication technologies, and a host of other technologies are enabling Digital agriculture to boost food productivity with optimal inputs.
Digital agriculture is a broad umbrella that covers the entire agriculture value chain. It includes, among other things, precision farming and smart farming, two concepts that are familiar to many. While precision farming uses some or all of the technologies mentioned above for analyzing and addressing the needs of individual crops or fields, smart farming is the application of data and information technologies for optimizing agricultural systems. We have witnessed significant progress in the genetic improvement of crops during the recent decades owing to the advancements in genomics, informatics, and analytics, combined with breeding and biotechnological approaches.
Digital agriculture with its existing, emerging, and anticipated tools has the potential to help us meet our future food supply needs
In addition to Genetic component (Genotype or G), current models for crop productivity also incorporate effects of Environment (E) and Management (M); productivity is the function of GxExM and Digital agriculture, with its tools and technologies, enabling the realization of gains from such a model. To provide a glimpse of the impact that Digital Agriculture is making, three concepts/ technologies and their utility are briefly outlined below.
Precision agriculture improves crop productivity and farm profitability through improved management of farm inputs using digital techniques. This involves better management of inputs such as seeds, fertilizers, irrigation, and herbicides/pesticides using right inputs at the right place, and at the right time. In conventional management, fields receive blanket application of fertilizers and irrigation, whether all locations in the fields need it or not, thereby contributing to increased production costs. With precision agriculture, these fields are divided into several management zones and each of these zones receives customized inputs based on variation in soil types, landscape position, and management history.
Remote sensing tools (sensors mounted on satellites, manned and unmanned aircrafts, drones etc) are used to evaluate crop health by measuring the radiation reflected from crops. By evaluating reflectance in multiple wavelength regions and calculating vegetation indices, we can assess the health status (healthy or stressed) of the plant and take measures to address the situation in a site-specific manner. When the sensors are near the objects such as those mounted on tractors or other farm equipment, or held by humans it is called proximal sensing. Remote sensing by itself, or in combination with proximal sensing, is being utilized for diverse applications such as management of nutrients, diseases and pests, weeds (through mapping of weed infestations), soils, and water (through direct sensing of soils or through assessment of crop canopy properties).
Internet of Things (IoT)—network of internet connected sensors and data collection devices—has been influencing many industries around the globe and its application in agriculture has a tremendous potential to improve farm productivity. IoT-based precision farming (precision agriculture) is where sensors, robotics, autonomous vehicles, and other devices are used for farm management through the implementation of site-specific and need-based application of fertilizers, water, and other inputs to improve productivity. Drones, in conjunction with IoT, are also increasingly being used for crop health assessment, site-specific application of agricultural chemicals, and for gathering key information about soil and other field characteristics. Other applications of IoT include controlled environment farming where the climate is monitored and managed, and monitoring of livestock location, movement, or health, which allows for timely intervention. Special mention needs to be made here of robotics where robots, operating in a fully or semi-autonomous manner, are being used for diverse operations such as sowing/planting, fertilizer/chemical applications, weeding, crop monitoring, harvesting, and a host of other activities beyond harvesting.
Humanity has gone through several famines and food supply crises over the centuries and we have survived them thanks to the technological innovations that boost food supply. Once again, we have a mammoth task ahead of us—of feeding nearly 10 billion people in 2050. Digital agriculture with its existing, emerging, and anticipated tools has the potential to help us meet our future food supply needs and what we are witnessing currently in this domain is nothing short of a revolution in Agriculture.