Utilization of Machine Vision to Monitor the Dynamic Responses of Rice Leaf Morphology and Colour to Nitrogen, Phosphorus, and Potassium Deficiencies
Joint Authors
Chen, Lisu
Sun, Yuanyuan
Gao, Jiali
Wang, Ke
Shen, Zhangquan
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-03
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Machine vision technology enables the continuous and nondestructive monitoring of leaf responses to different nutrient supplies and thereby contributes to the improvement of diagnostic effects.
In this study, we analysed the temporal dynamics of rice leaf morphology and colour under different nitrogen (N), phosphorus (P), and potassium (K) treatments by continuous imaging and further evaluated the effectiveness of dynamic characteristics for identification.
The top four leaves (the 1st incomplete leaf and the top three fully expanded leaves) were scanned every three days, and all images were processed in MATLAB to extract the morphological and colour characteristics for dynamic analysis.
Subsequently, the mean impact value was applied to evaluate the effectiveness of dynamic indices for identification.
According to the results, higher nutrient supply resulted in a faster leaf extension rate and a lower developing rate of chlorosis, and the influence of N deficiency on leaf growth was the greatest, followed by P deficiency and then K deficiency.
Furthermore, the optimal indices for identification were mainly calculated from morphological characteristics of the 1st incomplete leaf and colour characteristics of the 3rd fully expanded leaf.
Overall, dynamic analysis contributes not only to the exploration of the plant growth mechanism but also to the improvement of diagnostics.
American Psychological Association (APA)
Sun, Yuanyuan& Gao, Jiali& Wang, Ke& Shen, Zhangquan& Chen, Lisu. 2018. Utilization of Machine Vision to Monitor the Dynamic Responses of Rice Leaf Morphology and Colour to Nitrogen, Phosphorus, and Potassium Deficiencies. Journal of Spectroscopy،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1202416
Modern Language Association (MLA)
Sun, Yuanyuan…[et al.]. Utilization of Machine Vision to Monitor the Dynamic Responses of Rice Leaf Morphology and Colour to Nitrogen, Phosphorus, and Potassium Deficiencies. Journal of Spectroscopy No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1202416
American Medical Association (AMA)
Sun, Yuanyuan& Gao, Jiali& Wang, Ke& Shen, Zhangquan& Chen, Lisu. Utilization of Machine Vision to Monitor the Dynamic Responses of Rice Leaf Morphology and Colour to Nitrogen, Phosphorus, and Potassium Deficiencies. Journal of Spectroscopy. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1202416
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202416