---
title: "Patates Dolbec: 25% More Efficient Quality Control — Vooban"
url: https://vooban.com/en/case-studies/patates-dolbec
language: en
translation: https://vooban.com/etudes-de-cas/patates-dolbec
---

Case studies

# How to Be 25% More Efficient in Quality Control with AI?

- Client

Patates Dolbec

- Service

Artificial Intelligence

- Industry

Agrifood

Patates Dolbec is the largest potato producer in Eastern Canada. The company cultivates nearly 10,000 acres in the Portneuf region and has vertically integrated itself over the years. Today, Patates Dolbec cultivates, processes, and packages a wide variety of potatoes destined to the North American market.

Founded 50 years ago, the company based in St-Ubalde has consistently focused on innovation to improve its performance. Following the automation of its production line, Patates Dolbec decided to partner with Vooban in order to improve their quality assurance process using artificial intelligence.

## Statistics

- 15

Potato varieties

White, russet, red, etc.

- 21

Defects identified by the algorithm

## Challenges

The objective was to be able to detect all types of imperfections affecting the potatoes’ quality (more than 20) and to provide a solution that would give Patates Dolbec the flexibility of choosing the quality level of their product according to the varying needs of their customers (restaurants, grocery stores, etc.).

An additional challenge was to surpass the performance of the detection algorithm of their industrial sorting machine, the CELOX, which is the market benchmark for this sort of task. This would allow Patates Dolbec to reallocate its quality assurance team to higher value-added activities.

- > If AI is available in the potato industry, the rest of Quebec has to wake up!

Hugo d'Astous

General Director at Patates Dolbec

## Solution

Patates Dolbec was not satisfied with the performance of their older optical sorting machine, which had an error rate of 30%. This forced employees to manually sort part of the potatoes, resulting in the loss of a significant quantity of healthy potatoes and the associated revenue. In an industry with chronic labor shortage, a better solution was crucial. With the ever-changing nature of grown products, they needed an evolutive solution to be able to adapt to the changes in the base product.

We therefore retrofitted their optical sorting machine with high-definition cameras and a state-of-the-art deep neural network computer vision model, leveraging recent developments in AI and computer vision. To allow for periodic retraining of the model, a machine learning pipeline was developed in the AWS cloud. From data storage, labeling, and training to model registry and edge deployment, the AWS cloud serves as the foundational backbone of the upgraded sorting machine.

## Results

In the end, the implementation of AI in the quality control process had allowed Patates Dolbec to gain no less than 25% in efficiency as the error rate went from 30% to 5% in a matter of a few months.

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