AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Application of a spore detection system based on diffraction imaging to tomato gray mold

School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China
Jiangsu Changdian Technology Co. Ltd, Jiangyin 214400, Jiangsu, China
School of Science and Technology, Shanghai Open University, Shanghai 200433, China
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China
Department of Soil and Water Sciences, Faculty of Environmental Agricultural Sciences, Arish University, North Sinai, 45516, Egypt
Show Author Information

Abstract

This study addresses the challenge posed by the small spore size of tomato gray mold, which hinders its identification and enumeration by conventional techniques. This work presents a novel approach for quantifying spore counts of tomato gray mold using diffraction imaging technology and image processing techniques. To construct a device for acquiring diffraction images of tomato gray mold spores, initially, the hyperspectral data pertaining to the gray mold spores of tomatoes was obtained. The characteristic wavelength of the light source of the diffraction image acquisition device was obtained by smoothing, principal component analysis, and comprehensive coefficient weight calculation. Then, the key parameters of the system were simulated, and the diffraction image acquisition device was built. Finally, tomato gray mold spores were counted based on angular spectrum reconstruction and image processing. The findings indicated that the combined contribution rate of the initial and secondary principal components of the original spectral data obtained from tomato gray mold spore samples amounted to 92.271%. The visible range of 435 nm, 475 nm, and 720 nm can be selected as the light source for tomato gray mold’s spore diffraction imaging system. CMOS image sensor was installed 45 mm below the micropore with a diameter of 100 μm, and the diffraction image obtained by simulation has a clear diffraction fingerprint. The diffraction imaging system can collect diffraction images of disease spores, and the collected diffraction images have clear diffraction fingerprints. The experimental error range was 5.13%-8.57%, and the average error was 6.42%. The error was within a 95% consistency. Therefore, this study can provide a research basis for the classification and recognition of greenhouse disease spores.

References

【1】
【1】
 
 
International Journal of Agricultural and Biological Engineering
Pages 212-217

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Wang Y, Shi Q, Ren S, et al. Application of a spore detection system based on diffraction imaging to tomato gray mold. International Journal of Agricultural and Biological Engineering, 2024, 17(6): 212-217. https://doi.org/10.25165/j.ijabe.20241706.8537

601

Views

45

Downloads

0

Crossref

5

Web of Science

5

Scopus

Received: 15 September 2023
Accepted: 04 June 2024
Published: 31 December 2024
© The Author(s) 2024

We adopt the latest version of license CC BY 4.0, https://creativecommons.org/licenses/by/4.0/