Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time

S. Rai; R. Slichter; A. Dalal; A. Sharda

Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time

于Precision agriculture '25

著者：

S. Rai

S. Rai Biological and Agricultural Engineering, Kansas State University, Manhattan, Kansas 66506, USA

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R. Slichter

R. Slichter Biological and Agricultural Engineering, Kansas State University, Manhattan, Kansas 66506, USA

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A. Dalal

A. Dalal Biological and Agricultural Engineering, Kansas State University, Manhattan, Kansas 66506, USA

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A. Sharda

A. Sharda Biological and Agricultural Engineering, Kansas State University, Manhattan, Kansas 66506, USA

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类型:: 章节

Page Range:: 1038–1044

DOI:: https://doi.org/10.1163/9789004725232_136

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Dar Hadith al Hassania

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Effective seed sowing is hindered by challenges such as residue accumulation, low soil temperatures, and hair pinning (crop residue pushed in the trench by the furrow opener), which obstruct optimal trench formation. In this study, a novel computer vision-based method was developed to evaluate row cleaner performance. Multiple air seeders were equipped with a video acquisition system to capture trench conditions after row cleaner operation. The captured data were used to develop a segmentation model that analyzed key elements such as soil, straw, and machinery. Using the results from the segmentation model, an objective method was developed to quantify row cleaner performance. The results demonstrated the potential of this method to improve row cleaner selection and enhance seeding efficiency.

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Precision agriculture '25

ISBN:: 9789004725232

出版社:: Wageningen Academic

印刷出版日期:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time

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