Exciting News: Clarifruit has Rebranded to Clarifresh!

September 26, 2024

The Importance of Real-Time Data in Fresh Produce Quality Control

  • Fresh Produce Software
  • Supply Chain
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If you work with fruits and vegetables, you already understand (better than most) what it’s like to work in an environment that’s always in flux. Unlike a production line, the fresh produce supply chain is not a simple input-output sequence: it’s a highly dynamic series of steps, each of which is influenced by factors beyond anyone’s control. Perishability, a complex supply chain, and the role of weather all make managing fresh produce quality control a daunting task, to say the least.

What these organizations need above all isn’t just data, but data that updates itself in real time. Knowing what is happening right now, in each consignment, warehouse or field, is crucial to maintaining quality standards.

Thankfully, fresh produce businesses can now make real headway by leveraging modern AI systems that provide that always-on (and always accurate) image of the supply chain. Here, we’re taking a look at why the “real time” in “real time data” is much more than a buzzword: it’s the lifeblood of the digitalized and sustainability-minded businesses of the future.

The Fresh Produce Supply Chain: Challenges and Opportunities

The fresh produce supply chain is a delicate, intricate network. Unlike many other industries, the industry has to contend with the rapid perishability of its products. What’s more – each type of fresh produce degrades at different rates, so a multi-product operation needs to track a variety of different quality parameters at once, in order to make informed decisions. 

On top of these biological challenges, fresh produce retailers have to address consumer demands for transparency. Consumers want to know where their food comes from, how it’s farmed and transported. At the same time, businesses need to be able to trace each step of the process to align with food safety regulations and quality standards.

Last, but not certainly not least, businesses across the supply chain need to keep a watchful eye on the amount of waste they produce. Every touchpoint poses a risk of loss or spoilage: harvesting, packaging, storage, and transport. 

Real-Time Data: The Skeleton Key to Unlocking Fresh Produce Supply Chain Efficiency

The “real-time” aspect is critical in fresh produce quality control because it allows for immediate action in a highly dynamic and perishable environment. Here are just some of the benefits of implementing an AI-powered system for quality control.

Immediate Response to Quality Issues

Fresh produce can deteriorate quickly, often within hours. Real-time data enables quick detection of issues such as temperature spikes, humidity changes, or early signs of decay. This allows teams to take instant corrective actions (like adjusting storage conditions or diverting shipments), preventing further deterioration.

Prevention of Spoilage

Non-real-time data would be retrospective, meaning by the time the data is analyzed, the produce may already be damaged or unsellable. Real-time insights help identify problems before spoilage occurs, reducing waste and maintaining product quality.

Dynamic Supply Chain Management

The supply chain for fresh produce is complex and time-sensitive. Real-time data allows suppliers and retailers to monitor conditions continuously, optimizing transit routes or adjusting storage environments instantly. This adaptability is crucial to maintaining freshness and minimizing losses during transport.

Eliminating Quality Mismatch

One of the most significant challenges in the fresh produce industry is the delicate task of managing many and varied sets of quality standards at once. For example, growers need to know the quality standards for each of the businesses they supply. When the produce delivered does not meet these standards, the resulting quality mismatch costs each organization financially, and more often than not leads to waste. 

Traditional quality assurance methods open the door to this kind of mismatch: when inspectors rely on color charts and manual inspections, human error is bound to occur. Even without this error, managing multiple sets of standards in complex Excel spreadsheets is anything but scalable.

Towards a Shared Language of Quality Through the Integration of AI

Once a business and its suppliers and customers use an AI system like Clarifresh, they gain a common language of quality that ensures everyone wins, from the farmer right through to the end customer:

  • Inspectors perform automated quality inspections using computer vision.
  • Once they evaluate a consignment, this data updates in real-time on the app, for everyone to see.
  • All parties can use this shared reservoir of real-time data to identify patterns and make rapid decisions without guesswork.

AI Implementation: Barriers and Solutions

Innovations in real-time data and AI technology are offering new opportunities to optimize quality control. But adopting these solutions has traditionally been out of the reach of smaller players in the industries, due to their cost and complexity. 

Strategies for Successful Integration

To successfully integrate new technologies, it’s important to start with incremental changes. Businesses can introduce technologies in phases, beginning with a pilot program that allows them to test the effectiveness and resolve any issues on a small scale before expanding. Employee training is another critical strategy. Investing time and resources into upskilling workers ensures that the team feels confident and prepared to work with new systems. Collaboration between tech providers and end-users is also key. These solutions should be designed with input from those who will be using them daily. Lastly, businesses should focus on interoperability, ensuring that new technologies can integrate smoothly with existing systems, reducing friction and maximizing efficiency.

Benefits for Growers, Wholesalers, and Retailers

For growers, real-time data makes it possible to predict yield with much more accuracy. They can also use this technology to enhance pest and disease monitoring, crucial for delivering healthier crops to their customers. 

Further downstream, the same technology empowers retailers to improve the way they manage inventory, reducing the chances of shrinkage. Across the supply chain, AI-supported quality control saves costs, improves produce quality and increases consumer satisfaction.

The Real-World Benefits of Real-Time Data: Clarifresh’s AI-Driven QCaaS Solution

Clarifresh’s AI-driven Quality Control as a Service (QCaaS) platform is the first of its kind, offering a fresh approach to quality control that uses advanced machine learning and computer vision to automate quality inspections. The platform provides real-time, objective data that ensures consistency and accuracy throughout.

By providing real-time data, Clarifresh enables supply chain stakeholders—growers, wholesalers, and retailers—to identify and address quality issues early, reducing waste, optimizing inventory management, and ensuring that only top-quality produce reaches consumers.

The real-world benefits of Clarifresh’s solution are significant. Businesses that have adopted the platform report improved operational efficiency, with inspection efficiency increased by up to 3 times when compared to traditional methods. Our team is ready to help you transform the way you do quality assurance for the better. 

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