Sustainability in Food Production: Reducing Waste and Environmental Impact
by Brandon Tillema
Producing enough food for an entire global population of nearly eight billion people is not a small task. Sure, in less centralized areas, food production is quite sustainable, as it relies on the individual’s responsibility to the whole production, starting from resource management to an end-product.
However, food production in high-income nations relies on cast financial and environmental resources, and the food production process is far from perfect.
Inadequate resource management is often prescribed to the cost of business of large industrial farms and agribusinesses that dominate the food production industry and often rely on methods that harm environmental health, exploit animals, and produce vast amounts of waste.
In this article, we’ll address the problem of sustainability in food production and how smart-enabled and innovative 3D imaging technologies can help minimize food waste and its subsequent environmental impact. But before we can do that, we have to understand the underlying problem.
The Food Waste Problem
Food waste is one of the major waste-related issues in the modern world, right behind the growing concerns surrounding e-waste. It’s estimated that approximately one-third of global food production is being wasted each year.
This implies that the resources used in said production are also wasted, which should sound worrying, considering the growing shortage of drinking water and other resources worldwide.
The truth is that the problem of food waste begins at the production level. Much of the food waste is attributed to inefficient production, harvesting, storage, and even overproduction. This includes food that was left in the field after harvest, food that spoiled during transport or due to inadequate storage, and food that wasn’t sold in retail stores.
When all is taken into account, we can safely say with a degree of certainty that maximizing food production efficiency, from farming to the end product, is one of the key steps to increasing the sustainability of the food production process.
Sustainability in Food Production
Among other things, sustainability in food production aims to address the negative environmental, social, and economic impacts of the current food production system. This includes efficient use of resources such as water and energy, as well as reduction of greenhouse gas emissions and overall waste reduction through more effective farming and processing.
And this is where Smart Food and Agricultural Systems come into play. The application of these technologies aims to optimize resource use and minimize waste, all while increasing yield without compromising the environment—or at least minimizing the effects of food production.
This can be achieved through precision farming, where technology monitors and manages crops down to the tiniest level. Drones, sensors, and automated machinery can be used to target specific areas of the field, ensuring the adequate use of resources. This precision both increases crop yield and decreases the harmful environmental effects of farming.
The Solution to the Waste Problem
The continuous development of 3D imaging technologies has profoundly impacted various industries, from machine, construction, and civil engineering to healthcare, medicine, and food production.
Admittedly, in the context of food production, 3D imaging technologies, such as laser scanners, aren’t a complete solution to food waste. However, they are working parts of the equation that lead us towards increased sustainability in food production.
Machine Learning and AI
On the production floor, 3D Imaging Systems and Laser Profilers can be used to reduce the waste of product as it is divided up into smaller portions. When cutting/slicing large pieces of meat or cheese, especially manually or with older machinery, it is common to cut off edges and ends to provide easier and more uniform cuts.
By utilizing a laser profiler to determine volume, these parts can be cut evenly and consistently without the excessive waste associated with the current technique.
Waste can also be reduced by identifying problems before they lead to defective items that need to be discarded. A large degree of variability can lead to creating defective food items, but increased monitoring reduces those risks.
For example, in bakeries, a common contributor to food waste is incorrectly positioned dough prior to the heating process. By alerting operators prior to the cooking process, improper dough positioning can be fixed and additional waste prevented.
While it admittedly sounds like something from science fiction, the application of these systems in agriculture allows farmers and other automated implementations to make certain adjustments and thus optimize the farming conditions further.
And it goes beyond just farming. Food processing has started relying on machine learning and other adjacent automation technologies, such as 3D scanning and imaging, to optimize food processing and thus minimize waste.
For example, starch production leaves behind massive amounts of steepwater, which is rich in proteins, vitamins, minerals, and soluble fibers. Historically, steepwater was dumped into rivers and bodies of water, leading to massive water pollution.
However, nowadays, the steepwater is concentrated into syrup and used for bran fortification, which enhances the latter’s nutrient profile. In most factories, the entire process is fully automated, and the result is more sustainable food production of starch and livestock feed, with reduced waste and maximized resource use.
The Future Holds Promise
Sustainability in food production is more than just a choice eco-friendly companies have to make—it’s a necessity. Therefore, the role of technology in creating sustainable food production, one that has a minimally adverse environmental impact, is crucial.
Admittedly, technology doesn’t offer a one-size-fits-all solution to the problem of inefficient production and waste, but implementing adequate smart solutions is a step in the right direction.
So, by harnessing the power of 3D imaging and scanning systems, paired with machine learning and artificial intelligence, the food production industry could produce our food more efficiently while minimizing waste of both resources and end-products, all of which can immensely benefit the environment.
Article by Brandon Tillema
Brandon is the Technical Marketing Manager of KEYENCE‘s High Precision Measurement & Inspection team. He and his team work hard to provide the best solutions for measurement and inspection applications throughout every industry utilizing factory automation.