LandWISE 2015 Presenter, Tristan Perez

Since the 1960s, agriculture has seen significant advances in agrochemicals, crop and animal genetics, agricultural mechanisation and improved management practices. These technologies have been at the core of increased productivity and will continue to provide future incremental improvements. Data analytics, robotics, and autonomous systems are transforming industries such as mining, manufacturing, and health. We are starting to see automation of single agricultural processes such as animal and crop remote monitoring, robotic weed management, irrigation, nutrient decision support, etc. However, we envisage that the integration of these technologies together with a systems view of the farming enterprise and its place within the agri-food value chain will trigger the next wave of productive innovation in agriculture.

The challenge of the next agricultural revolution is to assist farming enterprises to make the management and business decisions that will optimise inputs such as labour, energy, water and agrochemicals and explicitly account for variability and uncertainty across the production system and along the agri-food value chain.

The opportunity for increased profitability, sustainability and competitiveness from finer-scale sensing and whole-farm decision-making and intervention requires farmers to have greater access to digital data and technologies to extract information from data. The agricultural landscape will rapidly change due to low-cost and portable ICT infrastructure.

Agri-intelligence is the integrated collection of tools and techniques – from robots, unmanned airborne vehicles (UAVs) and sensor networks to sophisticated mathematical models and algorithms – that can help farmers make sense of large amounts of data (agronomic, environmental and economic) to make risk-informed decisions and run their farms more profitably and sustainably.

The figure below shows the ubiquitous emerging vision of a farm in the second machine age, where computer systems are used to augment human perception and capacity for decision making in complex situations.

The farming enterprise is considered a system that interacts with the environment (through climate, markets, value chain, etc.) The key objective is to make sound decisions about management in order to optimise inputs, yield, quality, and at the same time make the system robust against yield and quality volatility due to climate, commodity market fluctuations, and incomplete information about the state of crop, soil, weeds and pests.