Emerging Food Technology Trends & Insights for 2022

June 27th 2022 new story

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In this post, I’ll share how I went from zero(ish) to a six-figure software engineering job offer in nine months. I hope that my story inspires others and acts as a valuable data point that can be added to your success story dataset. I took a Visual Basic for Applications (VBA) course in high school (nine years ago) and learned some C, Python, Matlab, and Labview. After college, I got a job as a Process Engineer at a refinery. I worked there until I changed careers into Software Engineering.

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The food industry is one industry that benefits from the use of technology, from data gathering, food quality, and supply chain, to combating food fraud, customer sentiment analysis, and food customization. Let’s explore some emerging food technology trends in 2022.

Artificial Intelligence

It is crucial for food producers to develop new methods to renew their product lines in order to remain current and gain access to new sources of income. Finding these new ways might be challenging, but it is necessary. In the past, this has meant collecting data manually through techniques like surveys, but AI now gives businesses the chance to foretell the preferences of their clients.

Manufacturers are now able to predict future trends and create new goods to capitalize on them faster by evaluating vast quantities of data on sales patterns and taste preferences for each demographic group. AI is also being utilized to provide customers with more customization options for the things they purchase. This innovation not only identifies the probable most popular taste combinations but also shortens and lowers the cost of the product development process, assisting businesses in bringing new goods to market in a more time-efficient manner.

One of the key goals for food producers is being able to manage supply networks properly. Modern businesses are increasingly using artificial neural network-based algorithms to track shipments at every point in the supply chain, raising the bar for food safety and providing complete transparency.

Accurate projections can be produced using AI in the food sector to control inventory and price. This sort of predictive research enables food firms to stay one step ahead, preventing waste and unneeded expenses. Despite the fact that modern food supply chains are more complicated and dispersed than ever, AI enables businesses to get a better overall picture, consequently enhancing their capacity to boost income.

Blockchain Compatible Supply Chain

Blockchain technology within the supply chain network is another emerging trend within the food industry. Nestle, for example, has tested blockchain technology for tracking milk through the dairy supply chain. Due to the immutable nature of the blockchain, it can also be used to reduce food fraud in the global food market. Olive oil is one of the most famous cases when it comes to food fraud. According to a study, 70% of extra virgin olive is fake and actually adulterated with other seed oils.

Food fraud can be combated by implementing blockchain technology into the supply chain systems of food vendors and suppliers. These supply chains consist of farmers, processors, manufacturers, certifying agencies, transporters, distributors, retailers, and more. One way blockchain tech can be implemented is by creating on-chain tokens or IDs that represent a supplier and linking the data to a barcode. 

This barcode can then be attached to the packaging of the ingredients, raw materials, and finished product. This will allow all parties in the supply chain as well as consumers to determine the origin of their food products. For example, with extra virgin olive oil, the farmer has their own blockchain ID on a barcode that is scanned when it reaches the processor, the processor has their own ID that is scanned when the cold-pressed oil reaches the bottler, and so on. By determining the true origin of a food product, food fraud can be reduced in the food industry thanks to blockchain technology.

Big Data/Data Science

Big data refers to data that changes or grows too quickly, is too complex, or is too large in volume to be processed by traditional data processing methods. However, these datasets also provide valuable information that can solve problems that an organization hasn't been able to tackle before.

Big data may aid in enhancing quality control for food producers and suppliers. Quality is a crucial component in the food sector, but maintaining consistency in a large and competitive market is challenging. Big data can improve food quality by providing food vendors and suppliers with information on the quality of ingredients used, the time it takes to go from the farm to the factory, etc. all of which are factors that can impact the quality of the food. For example, a long pipeline from the farm to the factory can cause degradation of certain ingredients, prompting vendors to choose a different variety of the same ingredient or a new one altogether.

Data science can also improve the efficiency of vendors and suppliers in the food industry. Data science can be used to help vendors scale their operations by identifying aspects that can be automated (for example, customer service, self-checkout, drive-through, etc.) and finding out which areas need improvement. To boost efficiency and be ready for that demand surge in advance, it might also be helpful to look for patterns in rising customer demand.

Another factor in the food technology industry that can benefit from big data is sentiment analysis. Sentiment refers to how people feel about a company or a product. Sentiment analysis can be used by food firms to monitor consumer feelings and attitudes. Food vendors and suppliers can also employ the concept of sentiment analysis to understand their consumers and their evolving attitudes about a brand. Big data assists in analyzing client sentiments shared on social media platforms and review sites (i.e TripAdvisor, Twitter, Google Reviews, etc.) The food and beverage business can use sentiment analysis to identify trends and top products or services. 

Conclusion

Data collection, blockchain-enabled tracking, food quality, and supply chain management, fraud prevention, consumer sentiment analysis, and food personalization are some of the processes that are being pursued in the food technology industry.

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