April 18, 2020

How Big Data and Sensors Can Help Reduce Food Wastage

food wastageModern farming has completely evolved by adopting technical advances like machines for harvesting, plowing, crop breeding, pesticides, fertilizers, controlled irrigation, and genetics research. All these have helped farmers produce good quality crops in larger quantities and a predictable manner. However, progress is yet to be made in getting the best yields from different types of soils because massive losses are still occurring during and after the harvest, where handling and monitoring of the produce aren’t done properly.

The industry is crying out for smart and precise solutions, and they are becoming available thanks to new technology that promises to revolutionize the industry. Smart farming is aiming to use modern technology for improving product and yield quality. An example is precision agriculture, where the concept of site-specific crop management deploys a decision support system that is based on measuring, monitoring, and responding to inter and intra-field variability in the crops.

This has allowed farmers to preserve their resources and optimize their returns. These monitoring solutions can be achieved by integrating electronic sensing devices that will record data on the environment, soil, and crops. This data can then offer useful information for decision-making through data analytics. The goal here is to make the best possible use of soil in a field, control crop care, and make informed decisions on the handling of produce after it is harvested.

Technology is already being used for the development and deployment of sensors to establish the quality of an extensive range of horticultural products like fruits. Computer intelligence methods are also being used to predict the quality of fruits and detect any defects. We found out through research that data-driven solutions have several benefits. For example, they can reduce the loss of vegetables and fruits along the supply chain from the farm to the point of being consumed.

The Big Problem

Vegetables and fruits can be damaged easily before, during, and after they are harvested in storage. This is wasting valuable produce. Most of the spoilage and decay are caused by fungi, viruses, bacteria, or microbial pathogens. Even products that are packed tightly can get bruised, which causes them to become susceptible to infections, and they generally don’t last long.

The United Nations’ Food and Agriculture Organization has reported that 14% of the world’s food is lost after harvest before it even reaches the shops and markets. Nearly one-third of all the food produced in the world is either lost or wasted. Minimizing food waste and loss has reached a critical point for creating a Zero Hunger world, where more than 822 million people suffer from hunger.

One research that was reviewing the role data analytics can play in the detection of defects in fruits and vegetables found that machine learning can help. Machine learning involves the use of computers to find patterns in data to make predictions and propose decisions without being programmed explicitly. The research found that machine learning is way ahead of traditional methods when it comes to classifying produce. It has made detecting diseases in plants and fruits extremely easy.

This application can be extended to monitoring the quality of fruit, vegetables, and other foods. The use of sensors for detecting diseases and insects in fruits and vegetables can act as electronic tongues or noses and measure chemical composition. The technology can also be used to measure physical properties like the acidity and firmness of the produce for determining its quality.

The acceptability of the product will depend on its size, shape, color, sweetness, and not having any defects like insect infestations or bruises. It will play a vital role in customer satisfaction and for the returns that suppliers and producers are going to be making. Sensing devices can also supply data about these characteristics to computer algorithms for analysis, and these new developments in machine learning will allow for fast and effective quality determination and predictions in fresh produce.

Machine Learning Will Help Cut Down Losses

There’s a current global research trend that aims at integrating sensing devices from the food chain to control and monitor quality indicators continuously. We reviewed this research and found stages where the solutions used in the food chain included:

·       Post-Harvest Quality Monitoring

In packaging houses, the products must be sorted and graded according to quality standards to determine their suitability for various consumer destinations. Export products should be stored well during long-distance transportation and on the shelf.

For local markets with shorter travel times, the quality requirements must be of different standards to determine if the product is suitable for human consumption or animal feed. Specialized sensors will take measurements to generate data for classifying, grading, and sorting products into different categories.

·       Market Quality Monitoring

Sensors can also be integrated into packaging materials that will continuously report and monitor the status of the product in real-time. These sensors can be allowed to communicate and send data to a center of command. Detecting, monitoring, and segregating food products such as fresh fruit to classify and then remove unsafe products to meet market demand is vital for ensuring profitability and maintaining market share.

·       Crop Monitoring

Sensors can also be used to measure properties of vegetables and fruits when they are growing, like the shape, color, and size. This information will help control growing conditions like water supply and will accurately determine the harvest date, which will reduce harvest losses.


With the global population increasing at a remarkable rate (it is expected to exceed 9 billion by 2050), the food and nutrition security is going to become an even bigger challenge. The only proper solution available to us right now lies in data-driven automation.

by Bobby J Davidson

We love our company and we love what we do.  Check out the ‘Why Percento‘ page to learn more: Love of Technology and Business!  As the President of Percento Technologies International, I provide day-to-day leadership to the company’s senior management and I am personally involved in the strategy, business development and sales activities of the firm.

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