185
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Estimating leaf nitrogen concentration from similarities in fresh and dry leaf spectral bands using a model population analysis framework

&
Pages 6841-6860 | Received 02 Apr 2018, Accepted 08 Nov 2018, Published online: 31 Mar 2019

References

  • Barnes, R., M. Dhanoa, and S. Lister. 1993. “Correction to the Description of Standard Normal Variate (SNV) and De-Trend (DT) Transformations in Practical Spectroscopy with Applications in Food and Beverage Analysis—2nd Edition.” Journal of near Infrared Spectroscopy 1: 185–186. doi:10.1255/jnirs.21.
  • Blackburn, G. A. 2007. “Hyperspectral Remote Sensing of Plant Pigments.” Journal of Experimental Botany 58: 855–867. doi:10.1093/jxb/erl123.
  • Cho, M. A., J. Van Aardt, R. Main, and B. Majeke. 2010. “Evaluating Variations of Physiology-Based Hyperspectral Features along with a Soil Water Gradient in a Eucalyptus Grandis Plantation.” International Journal of Remote Sensing 31: 3143–3159. doi:10.1080/01431160903154390.
  • Curran, P. J. 1989. “Remote Sensing of Foliar Chemistry.” Remote Sensing of Environment 30: 271–278. doi:10.1016/0034-4257(89)90069-2.
  • Deng, B., Y. Yun, P. Ma, C. Lin, D. Ren, and Y. Liang. 2015. “A New Method for Wavelength Interval Selection that Intelligently Optimises the Locations, Widths and Combinations of the Intervals.” Analyst 140: 1876–1885. doi:10.1039/c4an02123a.
  • Fan, W., Y. Shan, G. Li, H. Lv, H. Li, and Y. Liang. 2012. “Application of Competitive Adaptive Reweighted Sampling Method to Determine Useful Wavelengths for Prediction of Total Acid of Vinegar.” Food Analytical Methods 5: 585–590. doi:10.1007/s12161-011-9285-2.
  • Ferwerda, J. G., and S. D. Jones. 2006. “Continuous Wavelet Transformations for Hyperspectral Feature Detection.” In Progress in Spatial Data Handling . (pp. 167–178. Springer.
  • Fourty, T., F. Baret, S. Jacquemoud, G. Schmuck, and J. Verdebout. 1996. “Leaf Optical Properties with an Explicit Description of Its Biochemical Composition: Direct and Inverse Problems.” Remote Sensing of Environment 56: 104–117. doi:10.1016/0034-4257(95)00234-0.
  • Gökkaya, K., V. Thomas, T. Noland, H. McCaughey, I. Morrison, and P. Treitz. 2015. “Mapping Continuous Forest Type Variation by Means of Correlating Remotely Sensed Metrics to Canopy N: P Ratio in a Boreal Mixedwood Forest.” Applied Vegetation Science 18: 143–157. doi:10.1111/avsc.12122.
  • Horneck, D. A., and R. O. Miller. 1998. “Determination Of Total Nitrogen in Plant Tissue.” In ‘Handbook Of Reference Methods for Plant Analysis’. edited by Y Kalra, 75–83.
  • Huang, C., and G. P. Asner. 2009. “Applications of Remote Sensing to Alien Invasive Plant Studies.” Sensors 9: 4869–4889. doi:10.3390/s90604869.
  • Huang, Z., B. J. Turner, S. J. Dury, I. R. Wallis, and W. J. Foley. 2004. “Estimating Foliage N Concentration from HYMAP Data Using Continuum Removal Analysis.” Remote Sensing of Environment 93: 18–29. doi:10.1016/j.rse.2004.06.008.
  • Kokaly, R. F., and R. N. Clark. 1999. “Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression.” Remote Sensing of Environment 67: 267–287. doi:10.1016/S0034-4257(98)00084-4.
  • Li, H., Y. Liang, Q. Xu, and D. Cao. 2009. “Key Wavelengths Screening Using Competitive Adaptive Reweighted Sampling Method for Multivariate Calibration.” Analytica Chimica Acta 648: 77–84. doi:10.1016/j.aca.2009.06.046.
  • Li, J., W. Huang, L. Chen, S. Fan, B. Zhang, Z. Guo, and C. Zhao. 2014. “Variable Selection in Visible and Near-infrared Spectral Analysis for Noninvasive Determination Of Soluble Solids Content Of ‘Ya’pear.” Food Analytical Methods 7: 1891-1902. doi:10.1007/s12161-014-9832-8.
  • Mitchell, J.J., N.F. Glenn, T.T. Sankey, D.R. Derryberry, M.O. Anderson, and R.C. Hruska. 2012. “Spectroscopic Detection Of Nitrogen Concentrations in Sagebrush.” Remote Sensing Letters 3: 285-294. doi:10.1080/01431161.2011.580017.
  • Muñoz-Huerta, R. F., R. G. Guevara-Gonzalez, L. M. Contreras-Medina, I. Torres-Pacheco, J. Prado-Olivarez, and R. V. Ocampo-Velazquez. 2013. “A Review of Methods for Sensing the N Status in Plants: Advantages, Disadvantages and Recent Advances.” Sensors 13: 10823–10843. doi:10.3390/s130810823.
  • Mutanga, O., and A. K. Skidmore. 2004. “Hyperspectral Band Depth Analysis for a Better Estimation of Grass Biomass (Cenchrus Ciliaris) Measured under Controlled Laboratory Conditions.” International Journal of Applied Earth Observation and Geoinformation 5: 87–96. doi:10.1016/j.jag.2004.01.001.
  • Mutanga, O., A. K. Skidmore, and S. van Wieren. 2003. “Discriminating Tropical Grass (Cenchrus Ciliaris) Canopies Grown under Different N Treatments Using Spectroradiometry.” ISPRS Journal of Photogrammetry and Remote Sensing 57: 263–272. doi:10.1016/S0924-2716(02)00158-2.
  • Naes, T., T. Isaksson, and B. Kowalski. 1990. “Locally Weighted Regression and Scatter Correction for Near-Infrared Reflectance Data.” Analytical Chemistry 62: 664–673. doi:10.1021/ac00206a003.
  • Pereira, H. M., S. Ferrier, M. Walters, G. N. Geller, R. H. Jongman, R. J. Scholes, M. W. Bruford, et al. 2013. “Ecology. Essential Biodiversity Variables.” Science (New York, N.Y.) 339: 277–278. doi:10.1126/science.1229931.
  • Qu, F., D. Ren, J. Wang, Z. Zhang, N. Lu, and L. Meng. 2016. “An Ensemble Successive Project Algorithm for Liquor Detection Using near Infrared Sensor.” Sensors 16: 89. doi:10.3390/s16122100.
  • Ramoelo, A., A. K. Skidmore, M. Schlerf, R. Mathieu, and I. M. Heitkönig. 2011. “Water-Removed Spectra Increase the Retrieval Accuracy When Estimating Savanna Grass N and Phosphorus Concentrations.” ISPRS Journal of Photogrammetry and Remote Sensing 66: 408–417. doi:10.1016/j.isprsjprs.2011.01.008.
  • Ramoelo, A., A.K. Skidmore, M. Schlerf, R. Mathieu, and I.M. Heitkönig. 2011. “Water-removed Spectra Increase the Retrieval Accuracy when Estimating Savanna Grass Nitrogen and Phosphorus Concentrations.” ISPRS Journal Of Photogrammetry and Remote Sensing 66: 408-417. doi:10.1016/j.isprsjprs.2011.01.008.
  • Robinson, I., and A. MacArthur. 2011. The Field Spectroscopy Facility Post Processing Toolbox User Guide. Edinburgh, UK: University of Edinburgh.
  • Savitzky, A., and M.J. Golay. 1964. “Smoothing and Differentiation Of Data by Simplified Least Squares Procedures.” Analytical Chemistry 36: 1627-1639. doi:10.1021/ac60214a047.
  • Schlerf, M., C. Atzberger, J. Hill, H. Buddenbaum, W. Werner, and G. Schüler. 2010. “Retrieval ofChl and N in Norway Spruce (Picea Abies L. Karst.) Using Imaging Spectroscopy.” International Journal of Applied Earth Observation and Geoinformation 12: 17–26. doi:10.1016/j.jag.2009.08.006.
  • Serrano, L., J. Penuelas, and S. L. Ustin. 2002. “Remote Sensing of N and Lignin in Mediterranean Vegetation from AVIRIS Data: Decomposing Biochemical from Structural Signals.” Remote Sensing of Environment 81: 355–364. doi:10.1016/S0034-4257(02)00011-1.
  • Shao, J. 1993. “Linear Model Selection by Cross-validation.” Journal Of The American Statistical Association 88 (422): 486-494. doi:10.1080/01621459.1993.10476299.
  • Shi, B., L. Zhao, H. Wang, and D. Zhu. 2011. “Signal Optimisation Approaches on the Prediction of Apples Firmness by Near-Infrared Spectroscopy.” Sensor Letters 9: 1062–1068. doi:10.1166/sl.2011.1381.
  • Tran, T. N., N. L. Afanador, L. M. Buydens, and L. Blanchet. 2014. “Interpretation of Variable Importance in Partial Least Squares with Significance Multivariate Correlation (Smc).” Chemometrics and Intelligent Laboratory Systems 138: 153–160. doi:10.1016/j.chemolab.2014.08.005.
  • Vohland, M., M. Ludwig, M. Harbich, C. Emmerling, and S. Thiele-Bruhn. 2016. “Using Variable Selection and Wavelets to Exploit the Full Potential of Visible–Near-Infrared Spectra for Predicting Soil Properties.” Journal of near Infrared Spectroscopy 24: 255–269. doi:10.1255/jnirs.1233.
  • Vorovencii, I. 2009. “The Hyperspectral Sensors Used in Satellite and Aerial Remote Sensing.” Bulletin of the Transilvania University of Brasov 2: 51.
  • Wang, B. J., J. M. Chen, W. Ju, F. Qiu, Q. Zhang, M. Fang, and F. Chen. 2017. “Limited Effects of Water Absorption on Reducing the Accuracy of Leaf N Estimation.” Remote Sensing 9 (3): 291. doi:10.3390/rs9030291.
  • Wang, Z., T. Wang, R. Darvishzadeh, A. Skidmore, S. Jones, and L Suarez., ... & Hearne, J. (2016). Vegetation indices for mapping canopy foliar nitrogen in a mixed temperate forest. Remote sensing, 8(6), 491
  • Wold, S., M. Sjöström, and L. Eriksson. 2001. “PLS-regression: A Primary Tool of Chemometrics.” Chemometrics and Intelligent Laboratory Systems 58: 109–130. doi:10.1016/S0169-7439(01)00155-1.
  • Xu, Q., and Y. Liang. 2001. “Monte Carlo Cross Validation.” Chemometrics and Intelligent Laboratory Systems 56: 1-11. doi:10.1016/S0169-7439(00)00122-2.
  • Xu, Q., and Y. Liang. 2001. “Monte Carlo Cross-Validation.” Chemometrics and Intelligent Laboratory Systems 56: 1–11. doi:10.1016/S0169-7439(00)00122-2.
  • Yun, Y., W. Wang, M. Tan, Y. Liang, H. Li, D. Cao, H. Lu, and Q. Xu. 2014. “A Strategy that Iteratively Retains Informative Variables for Selecting an Optimal Variable Subset in Multivariate Calibration.” Analytica Chimica Acta 807: 36–43. doi:10.1016/j.aca.2013.11.032.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.