Agriculture is the practice of cultivating soil, growing crops and raising livestock. And at its core is a bunch of maths and data.
“A number of concepts in statistics and maths are extensively used in various fields of agriculture, such as soil science, animal and crop production, agricultural engineering and agricultural economics,” says Kanika Singh, a research fellow at the University of Sydney, who is currently working on optimising soil management and health in Papua New Guinea.
Agriculture also relies on a range of data sources. Think weather and climate data for forecasting; sensor data for info on soil, temperature, humidity, rainfall, sunlight and farm equipment; animal and plant genomics research data; plus remotely sensed data through satellites and drones.
How do agriculturalists make sense of all that data? Statistical modelling combined with maths, according to Kanika.