Advances in tech and communications are increasing our awareness of the food industry and the ways we find, eat, and dispose of our food. Here’s why it matters.

Gaining insight into how weather, seasonal sunlight, migratory patterns of animals, birds, insects, use of specialized fertilizers, insecticides by crop, planting cycles and irrigation cycles all affect yield is a perfect problem for machine learning.

The agricultural industry is trying to tackle these complex issues, but its innovation pipelines have stagnated. For example, it takes companies between 13-15 years to discover a new crop protection product and bring it to market, despite the urgent pest resistance issues farmers face.

A growing number of agri-tech start-ups are developing ways of applying digital technologies to the mucky business of farming. Many of these technologies improve yields, cut waste and resource use, and enhance the sustainability of farming. And most do so by collecting and analysing an increasingly valuable asset: data.

By 2050, the world’s population is expected to grow to 9.7 billion people, and feeding it will be a huge challenge. Due to industrial development and urbanization, we are losing arable lands every day. In 2015, scientists reported that the Earth had lost a third of its arable lands over the previous 40 years.