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Related Experiment Video

Updated: Jul 16, 2025

Fruit Volatile Analysis Using an Electronic Nose

Fruit Volatile Analysis Using an Electronic Nose

Published on: March 30, 2012

Real-Time Detection of Strawberry Ripeness Using Augmented Reality and Deep Learning.

Jackey J K Chai¹, Jun-Li Xu², Carol O'Sullivan¹

¹School of Computer Science and Statistics, Trinity College Dublin, D02 PN40 Dublin, Ireland.

Sensors (Basel, Switzerland)

|September 9, 2023

Summary

This summary is machine-generated.

This study introduces an automated system using YOLOv7 object detection and augmented reality to accurately assess strawberry ripeness in real-time, improving harvest quality and efficiency for farmers.

Keywords:

YOLOv7 augmented reality deep learning ripeness strawberry

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Area of Science:

Agricultural Technology
Computer Vision
Robotics

Background:

Strawberry harvesting relies on manual labor and subjective ripeness assessments, leading to variable post-harvest quality.
Automating ripeness detection is crucial for enhancing efficiency and consistency in strawberry production.

Purpose of the Study:

To develop an automated system for accurate and efficient strawberry ripeness assessment.
To integrate object detection and augmented reality for real-time visual ripeness feedback.

Main Methods:

Utilized YOLOv7 object detection with transfer learning, fine-tuning, and multi-scale training for strawberry ripeness identification.
Implemented augmented reality (Microsoft HoloLens 2) to overlay ripeness labels onto strawberries in real-world conditions.
Evaluated model performance using metrics such as mAP and F1 score, and measured detection speed.

Main Results:

The YOLOv7 model achieved high accuracy in detecting strawberry ripeness, with an mAP of 0.89 and an F1 score of 0.92.
Real-time detection was achieved with an average detection time of 18 ms per frame at 1280x720 resolution.
Demonstrated superior performance compared to other state-of-the-art methodologies.

Conclusions:

The developed system offers a significant advancement over traditional methods for strawberry ripeness assessment.
Augmented reality integration provides practical visual assistance for farmers during harvesting.
This technology holds substantial potential for transforming agricultural practices and improving crop management.