Development of Seeding Rate Monitoring System Applicable to a Mechanical Pot-Seeding Machine

In this study, we developed a monitoring system to accurately track the seeding rate and to identify the locations where the mechanical pot-seeding machine failed to sow seeds correctly. The monitoring system employs diverse image processing techniques, including the Hough transform, hue–saturation–...

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Bibliographic Details
Published in:Agriculture (Basel) 2023-10, Vol.13 (10), p.2000
Main Authors: Kim, Seung-Jun, Lee, Hyeon-Seung, Hwang, Seok-Joon, Kim, Jeong-Hun, Jang, Moon-Kyeong, Nam, Ju-Seok
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Cameras
coated seed
Hough transformation
Image processing
Monitoring
monitoring system
Monitoring systems
pot-seeding machine
Saturation (color)
Seeding
Seeding rate
Seeds
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Summary:In this study, we developed a monitoring system to accurately track the seeding rate and to identify the locations where the mechanical pot-seeding machine failed to sow seeds correctly. The monitoring system employs diverse image processing techniques, including the Hough transform, hue–saturation–value color space conversion, image morphology techniques, and Gaussian blur, to accurately pinpoint the seeding rate and the locations where seeds are missing. To determine the optimal operating conditions for the seeding rate monitoring system, a factorial experiment was conducted by varying the brightness and saturation values of the image data. When the derived optimal operating conditions were applied, the system consistently achieved a 100% seed recognition rate across various seeding conditions. The monitoring system developed in this study has the potential to significantly reduce the labor required for supplementary planting by enabling the real-time identification of locations where seeds were not sown during pot-seeding operations.
ISSN:2077-0472
2077-0472
DOI:10.3390/agriculture13102000