A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves
Modern agriculture requires more accurate field management capability compared with traditional agriculture. The development of hyperspectral remote sensing technology embodies rapid and non-destructive features in agricultural information monitoring, providing a technical guarantee for the scientif...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10188855/ |
| _version_ | 1827893502494638080 |
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| author | Xu Li Ziyan Shi Tiecheng Bai Bailin Chen Xin Lv Ze Zhang Baoping Zhou |
| author_facet | Xu Li Ziyan Shi Tiecheng Bai Bailin Chen Xin Lv Ze Zhang Baoping Zhou |
| author_sort | Xu Li |
| collection | DOAJ |
| description | Modern agriculture requires more accurate field management capability compared with traditional agriculture. The development of hyperspectral remote sensing technology embodies rapid and non-destructive features in agricultural information monitoring, providing a technical guarantee for the scientific management of agricultural production. The mathematical model of inverse cotton leaf total nitrogen was established by decomposing and transforming the original cotton leaf spectrum using continuous wavelet analysis and traditional spectral transformation, taking the characteristic wavelet coefficients and spectral characteristic bands as independent variables, and using univariate, stepwise regression, and partial least squares methods. The correlation between the total nitrogen content of cotton leaves and the spectral reflectance, through different methods of spectral treatment, was improved to different degrees. For the conventional spectral transformation, the inverse logarithmic first-order differential lg<inline-formula> <tex-math notation="LaTeX">$^{\prime} $ </tex-math></inline-formula> (1/R) improved the correlation of cotton leaf total nitrogen by 0.26. The continuous wavelet analysis outperformed the conventional spectral model regarding information noise reduction and mining of feature information. The established model with RPD>2 had good stability and predictive power for all sample data. |
| first_indexed | 2024-03-12T21:54:41Z |
| format | Article |
| id | doaj.art-f83552427c434ca19af10be06b8bb435 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-12T21:54:41Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f83552427c434ca19af10be06b8bb4352023-07-25T23:00:24ZengIEEEIEEE Access2169-35362023-01-0111742287423810.1109/ACCESS.2023.329663510188855A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton LeavesXu Li0https://orcid.org/0000-0002-8154-1188Ziyan Shi1https://orcid.org/0000-0003-2596-9590Tiecheng Bai2Bailin Chen3Xin Lv4Ze Zhang5Baoping Zhou6https://orcid.org/0009-0002-8960-5163Key Laboratory of Tarim Oasis Agriculture/College of Information Engineering, Ministry of Education, Tarim University, Alar, ChinaKey Laboratory of Tarim Oasis Agriculture/College of Information Engineering, Ministry of Education, Tarim University, Alar, ChinaKey Laboratory of Tarim Oasis Agriculture/College of Information Engineering, Ministry of Education, Tarim University, Alar, ChinaKey Laboratory of Tarim Oasis Agriculture/College of Information Engineering, Ministry of Education, Tarim University, Alar, ChinaKey Laboratory of Oasis Ecological Agriculture Corps, Shihezi University, Shihezi, ChinaKey Laboratory of Oasis Ecological Agriculture Corps, Shihezi University, Shihezi, ChinaKey Laboratory of Tarim Oasis Agriculture/College of Information Engineering, Ministry of Education, Tarim University, Alar, ChinaModern agriculture requires more accurate field management capability compared with traditional agriculture. The development of hyperspectral remote sensing technology embodies rapid and non-destructive features in agricultural information monitoring, providing a technical guarantee for the scientific management of agricultural production. The mathematical model of inverse cotton leaf total nitrogen was established by decomposing and transforming the original cotton leaf spectrum using continuous wavelet analysis and traditional spectral transformation, taking the characteristic wavelet coefficients and spectral characteristic bands as independent variables, and using univariate, stepwise regression, and partial least squares methods. The correlation between the total nitrogen content of cotton leaves and the spectral reflectance, through different methods of spectral treatment, was improved to different degrees. For the conventional spectral transformation, the inverse logarithmic first-order differential lg<inline-formula> <tex-math notation="LaTeX">$^{\prime} $ </tex-math></inline-formula> (1/R) improved the correlation of cotton leaf total nitrogen by 0.26. The continuous wavelet analysis outperformed the conventional spectral model regarding information noise reduction and mining of feature information. The established model with RPD>2 had good stability and predictive power for all sample data.https://ieeexplore.ieee.org/document/10188855/Hyperspectralnon destructive testingcontinuous wavelet analysisspectral transformationtotal nitrogencotton |
| spellingShingle | Xu Li Ziyan Shi Tiecheng Bai Bailin Chen Xin Lv Ze Zhang Baoping Zhou A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves IEEE Access Hyperspectral non destructive testing continuous wavelet analysis spectral transformation total nitrogen cotton |
| title | A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves |
| title_full | A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves |
| title_fullStr | A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves |
| title_full_unstemmed | A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves |
| title_short | A Study on the Estimation Model of Hyperspectral Reflectivity and Leaf Nitrogen Content of Cotton Leaves |
| title_sort | study on the estimation model of hyperspectral reflectivity and leaf nitrogen content of cotton leaves |
| topic | Hyperspectral non destructive testing continuous wavelet analysis spectral transformation total nitrogen cotton |
| url | https://ieeexplore.ieee.org/document/10188855/ |
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