Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VENμS satellite

Y. Cohen; V. Alchanatis; Y. Zusman; Z. Dar; D. J. Bonfil; A. Karnieli; A. Zilberman; A. Moulin; V. Ostrovsky; A. Levi; R. Brikman; M. Shenker

doi:10.1007/s11119-009-9147-8

Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VENμS satellite

Y. Cohen^*, V. Alchanatis, Y. Zusman, Z. Dar, D. J. Bonfil, A. Karnieli, A. Zilberman, A. Moulin, V. Ostrovsky, A. Levi, R. Brikman, M. Shenker

^*Corresponding author for this work

Department of Soil and Water Sciences

Research output: Contribution to journal › Article › peer-review

72 Scopus citations

Abstract

Relationships between leaf spectral reflectance at 400-900 nm and nitrogen levels in potato petioles and leaves were studied. Five nitrogen (N) fertilizer treatments were applied to build up levels of nitrogen variation in potato fields in Israel in spring 2006 and 2007. Reflectance of leaves was measured in the field over a spectral range of 400-900 nm. The leaves were sampled and analyzed for petiole NO₃-N and leaf percentage N (leaf-%N). Prediction models of leaf nitrogen content were developed based on an optical index named transformed chlorophyll absorption reflectance index (TCARI) and on partial least squares regression (PLSR). Prediction models were also developed based on simulated bands of the future VENμS satellite (Vegetation and Environment monitoring on a New Micro-Satellite). Leaf spectral reflectance correlated better with leaf-%N than with petiole NO₃-N. The TCARI provided strong correlations with leaf-%N, but only at the tuber-bulking stage. The PLSR analysis resulted in a stronger correlation than TCARI with leaf-%N. An R² of 0.95 (p < 0.01) and overall accuracy of 80.5% (Kappa = 74%) were determined for both vegetative and tuber-bulking periods. The simulated VENμS bands gave a similar correlation with leaf-%N to that of the spectrometer spectra. The satellite has significant potential for spatial analysis of nitrogen levels with inexpensive images that cover large areas every 2 days.

Original language	English
Pages (from-to)	520-537
Number of pages	18
Journal	Precision Agriculture
Volume	11
Issue number	5
DOIs	https://doi.org/10.1007/s11119-009-9147-8
State	Published - 2010

Bibliographical note

Funding Information:
Acknowledgments This project was supported by the Israeli Space Agency, Israeli Ministry of Science and also by Research Grant Award No. CA-9102-06 from BARD-AAFC—The United States—Israel Binational Agricultural Research and Development Fund and Agriculture and Agri-Food, Canada. The authors wish to express their appreciation of the vital contributions of Gadi Hadar and Ran Ferdman, potato growers from Kibbutz Ruhama, who provided land, seed and pesticide, and managed the irrigation for the project at no cost. The field experiments could not have been performed without the collaboration of Yossi Sofer from Haifa Chemicals, Ltd. We are also grateful for the anonymous reviewers for their constructive remarks.

Keywords

Nitrogen
Partial least squares regression (PLSR)
Potato
Spectral reflectance
Transformed chlorophyll absorption in reflectance index (TCARI)
VENμS satellite

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10.1007/s11119-009-9147-8

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@article{e1465f08ba9a48debfae79a4e593d231,

title = "Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VENμS satellite",

abstract = "Relationships between leaf spectral reflectance at 400-900 nm and nitrogen levels in potato petioles and leaves were studied. Five nitrogen (N) fertilizer treatments were applied to build up levels of nitrogen variation in potato fields in Israel in spring 2006 and 2007. Reflectance of leaves was measured in the field over a spectral range of 400-900 nm. The leaves were sampled and analyzed for petiole NO3-N and leaf percentage N (leaf-%N). Prediction models of leaf nitrogen content were developed based on an optical index named transformed chlorophyll absorption reflectance index (TCARI) and on partial least squares regression (PLSR). Prediction models were also developed based on simulated bands of the future VENμS satellite (Vegetation and Environment monitoring on a New Micro-Satellite). Leaf spectral reflectance correlated better with leaf-%N than with petiole NO3-N. The TCARI provided strong correlations with leaf-%N, but only at the tuber-bulking stage. The PLSR analysis resulted in a stronger correlation than TCARI with leaf-%N. An R2 of 0.95 (p < 0.01) and overall accuracy of 80.5% (Kappa = 74%) were determined for both vegetative and tuber-bulking periods. The simulated VENμS bands gave a similar correlation with leaf-%N to that of the spectrometer spectra. The satellite has significant potential for spatial analysis of nitrogen levels with inexpensive images that cover large areas every 2 days.",

keywords = "Nitrogen, Partial least squares regression (PLSR), Potato, Spectral reflectance, Transformed chlorophyll absorption in reflectance index (TCARI), VENμS satellite",

author = "Y. Cohen and V. Alchanatis and Y. Zusman and Z. Dar and Bonfil, {D. J.} and A. Karnieli and A. Zilberman and A. Moulin and V. Ostrovsky and A. Levi and R. Brikman and M. Shenker",

note = "Funding Information: Acknowledgments This project was supported by the Israeli Space Agency, Israeli Ministry of Science and also by Research Grant Award No. CA-9102-06 from BARD-AAFC—The United States—Israel Binational Agricultural Research and Development Fund and Agriculture and Agri-Food, Canada. The authors wish to express their appreciation of the vital contributions of Gadi Hadar and Ran Ferdman, potato growers from Kibbutz Ruhama, who provided land, seed and pesticide, and managed the irrigation for the project at no cost. The field experiments could not have been performed without the collaboration of Yossi Sofer from Haifa Chemicals, Ltd. We are also grateful for the anonymous reviewers for their constructive remarks.",

year = "2010",

doi = "10.1007/s11119-009-9147-8",

language = "אנגלית",

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pages = "520--537",

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T1 - Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VENμS satellite

AU - Cohen, Y.

AU - Alchanatis, V.

AU - Zusman, Y.

AU - Dar, Z.

AU - Bonfil, D. J.

AU - Karnieli, A.

AU - Zilberman, A.

AU - Moulin, A.

AU - Ostrovsky, V.

AU - Levi, A.

AU - Brikman, R.

AU - Shenker, M.

N1 - Funding Information: Acknowledgments This project was supported by the Israeli Space Agency, Israeli Ministry of Science and also by Research Grant Award No. CA-9102-06 from BARD-AAFC—The United States—Israel Binational Agricultural Research and Development Fund and Agriculture and Agri-Food, Canada. The authors wish to express their appreciation of the vital contributions of Gadi Hadar and Ran Ferdman, potato growers from Kibbutz Ruhama, who provided land, seed and pesticide, and managed the irrigation for the project at no cost. The field experiments could not have been performed without the collaboration of Yossi Sofer from Haifa Chemicals, Ltd. We are also grateful for the anonymous reviewers for their constructive remarks.

PY - 2010

Y1 - 2010

N2 - Relationships between leaf spectral reflectance at 400-900 nm and nitrogen levels in potato petioles and leaves were studied. Five nitrogen (N) fertilizer treatments were applied to build up levels of nitrogen variation in potato fields in Israel in spring 2006 and 2007. Reflectance of leaves was measured in the field over a spectral range of 400-900 nm. The leaves were sampled and analyzed for petiole NO3-N and leaf percentage N (leaf-%N). Prediction models of leaf nitrogen content were developed based on an optical index named transformed chlorophyll absorption reflectance index (TCARI) and on partial least squares regression (PLSR). Prediction models were also developed based on simulated bands of the future VENμS satellite (Vegetation and Environment monitoring on a New Micro-Satellite). Leaf spectral reflectance correlated better with leaf-%N than with petiole NO3-N. The TCARI provided strong correlations with leaf-%N, but only at the tuber-bulking stage. The PLSR analysis resulted in a stronger correlation than TCARI with leaf-%N. An R2 of 0.95 (p < 0.01) and overall accuracy of 80.5% (Kappa = 74%) were determined for both vegetative and tuber-bulking periods. The simulated VENμS bands gave a similar correlation with leaf-%N to that of the spectrometer spectra. The satellite has significant potential for spatial analysis of nitrogen levels with inexpensive images that cover large areas every 2 days.

AB - Relationships between leaf spectral reflectance at 400-900 nm and nitrogen levels in potato petioles and leaves were studied. Five nitrogen (N) fertilizer treatments were applied to build up levels of nitrogen variation in potato fields in Israel in spring 2006 and 2007. Reflectance of leaves was measured in the field over a spectral range of 400-900 nm. The leaves were sampled and analyzed for petiole NO3-N and leaf percentage N (leaf-%N). Prediction models of leaf nitrogen content were developed based on an optical index named transformed chlorophyll absorption reflectance index (TCARI) and on partial least squares regression (PLSR). Prediction models were also developed based on simulated bands of the future VENμS satellite (Vegetation and Environment monitoring on a New Micro-Satellite). Leaf spectral reflectance correlated better with leaf-%N than with petiole NO3-N. The TCARI provided strong correlations with leaf-%N, but only at the tuber-bulking stage. The PLSR analysis resulted in a stronger correlation than TCARI with leaf-%N. An R2 of 0.95 (p < 0.01) and overall accuracy of 80.5% (Kappa = 74%) were determined for both vegetative and tuber-bulking periods. The simulated VENμS bands gave a similar correlation with leaf-%N to that of the spectrometer spectra. The satellite has significant potential for spatial analysis of nitrogen levels with inexpensive images that cover large areas every 2 days.

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KW - Spectral reflectance

KW - Transformed chlorophyll absorption in reflectance index (TCARI)

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Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VENμS satellite

Abstract

Bibliographical note

Keywords

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