How sensors and big data can help cut food wastage

Modern farming has evolved by adopting technical advances such as machines for ploughing and harvesting, controlled irrigation, fertilisers, pesticides, crop breeding and genetics research. These have helped farmers to produce large crops of a good quality in a fairly predictable way.

But there’s still progress to be made in getting the best possible yields from different kinds of soils. And big losses still occur – especially during and after harvest – where monitoring and handling of produce isn’t done well. The industry needs smart and precise solutions and these are becoming available through new technology.

Smart farming aims to use modern technology to improve yield and product quality. One example is precision agriculture, a site specific crop management concept that uses a decision support system based on monitoring, measuring and responding to inter and intra-field variability in crops. This allows farmers to optimise their returns and preserve resources. Such monitoring solutions can be achieved by integrating electronic sensing devices that record data in soil, the environment or crops. The data can then provide useful information for decision-making, through a process called data analytics.

The goal is to make the best possible use of soil in a particular field, control crop care and make informed decisions about handling produce after harvest.

We’ve been involved in the development and use of sensors to help establish the quality of a wide range of horticultural products, including fruits. We used computer intelligence methods to detect defects and predict the quality of fruit.

Our latest research found that data-driven solutions have a number of benefits. For instance, they can help reduce the loss of fruit and vegetables along the supply chain from farm to being consumed.

Fruits and vegetables can be damaged before, during and after harvest as well as in storage. This is wasteful. Some decay and spoilage is caused by viruses, fungi, bacteria or microbial pathogens. Products that are tightly packed or bruised are more vulnerable to infections and don’t last as long.

According to the United Nations Food and Agriculture Organisation, around 14% of the world’s food is lost after harvest and before reaching shops and markets. And about one-third of the world’s food is lost or wasted. Minimising food loss and waste is critical to creating a Zero Hunger world where more than 821 million people are already suffering from hunger.

Our research involved reviewing the role that data analytics can play in the detection of defects in fruit and vegetables. We found that machine learning – the ability of computers to find patterns in data, make predictions and propose decisions without being explicitly programmed – far surpasses traditional methods for classifying produce.

Machine learning has made great achievements in detecting plant diseases and fruit. These could be extended to monitoring the quality of fruit and other foods.