Determination of nitrogen concentration in fresh pear leaves by visible/near-infrared reflectance spectroscopy

Agronomy Journal

Volumn 106, Issue 5, 2014, Pages 1867-1872

  Jie, Wang ^a   Zhao, Hua Bing ^a   Shen, Chang Wei ^a   Chen, Qiao Wei ^a   Dong, Cai Xia ^a   Xu, Yang Chun ^a  

^a NANJING AGRICULTURAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84907044565     PISSN: 00021962     EISSN: 14350645     Source Type: Journal    
DOI: 10.2134/agronj13.0303     Document Type: Article

References (39)

1. Alchanatis, V., Z. Schmilovitch, M. Meron. 2005. In-field assessment of single leaf nitrogen status by spectral reflectance measurements. Precis. Agric. 6:25-39.
2. Atzberger, C., M. Guérifb, F. Baretb, and W. Wernerc. 2010. Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat. Comput. Electron. Agric. 73:165-173. doi:10.1016/j.compag.2010.05.006
3. Aucott, L.S., P.H. Garthwaite, and S.T. Buckland. 1988. Transformations to reduce the effect of particle size in near-infrared spectra. Analyst (Lond.) 113:1849-1854.
4. Baret, F., and S. Buis. 2008. Estimating canopy characteristics from remote sensing observations. Review of methods and associated problems. In: S. Liang, editor, Advances in land remote sensing: System, modeling, inversion and application. Springer, Dordrecht, the Netherlands. p. 172-301.
5. Cecilia, S., and R.S. Luis. 2009. Application of NIR and MIR spectroscopy in quality control of potato chips. J. Food Compost. Anal. 6:596-605.
6. Chen, M., B. Glaz, R.A. Gilbert, S.H. Daroub, F.E. Barton, and Y. Wan. 2002. Near-infrared reflectance spectroscopy analysis of phosphorus in sugarcane leaves. Agron. J. 94:1324-1331. doi:10.2134/ agronj2002.1324
7. Curran, P.J. 1989. Remote sensing of foliar chemistry. Remote Sens. Environ. 30:271-278. doi:10.1016/0034-4257(89)90069-2
8. Darvishzadeh, R., A. Skidmore, M. Schlerf, C. Atzberger, F. Corsi, and M. Cho. 2008. LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements. ISPRS J. Photogramm. 63:409-426.
9. Ecarnot, M., F. Compan, and P. Roumet. 2013. Assessing leaf nitrogen content and leaf mass per unit area of wheat in the field throughout plant cycle with a portable spectrometer. Field Crops Res. 140:44-50.
10. Eitel, J.U.H., D.S. Long, P.E. Gessler, and E.R. Hunt. 2008. Combined spectral index to improve ground-based estimates of nitrogen status in dryland wheat. Agron. J. 100:1694-1702.
11. Fernandez-Escobar, R., J.M. Garcia-Novelo, and H. Restrepo-Diaz. 2011. Mobilization of nitrogen in the olive bearing shoots after foliar application of urea. Sci. Hortic. (Amsterdam) 127:452-454. doi:10.1016/j. scienta.2010.10.006
12. Guiñón, J.L., E. Ortega, J. García-Antón, and V. Pérez-Herranz. 2007. Moving average and Savitzki-Golay smoothing filters using Mathcad. International Conference on Engineering Education. 9:3-7.
13. Houborg, R., and E. Boegh. 2008. Mapping leaf chlorophyll and leaf area index using inverseand forward canopy reflectance modeling and SPOT reflectance data. Remote Sens. Environ. 112:186-202. doi:10.1016/j. rse.2007.04.012
14. Hunt, E.R., C.S.T. Daughtry, J.U.H. Eitel, and D.S. Long. 2011. Remote sensing leaf chlorophyll content using a visible band index. Agron. J. 103:1090-1099.
15. Jin, C., M. Huang, and Y. He. 2009. Estimating nitrogen status of plant by Vis/NIR spectroscopy and mathematical model. Fifth International Conference on Natural Computation.3: 612-616.
16. Klein, I., and S.A. Weinbaum. 1984. Foliar application of urea to olive: Translocation of urea nitrogen as influenced by sink demand and nitrogen deficiency. J. Am. Soc. Hortic. Sci. 109:356-360.
17. Liu, F., P.C. Nie, M. Huang, W.W. Kong, and Y. He. 2011. Nondestructive determination of nutritional information in oilseed rape leaves using visible/near infrared spectroscopy and multivariate calibrations. Sci. China Inform Sci. 54:598-608. doi:10.1007/s11432-011-4198-7
18. Luo, C.S., L. Xue, and M.H. Liu. 2011. Nondestructive measurement of sugar content in navel orange based on Vis-NIR spectroscopy. Conference on Computer and Computing Technologies in Agriculture IV.347:467-473.
19. Martens, H., and T. Nas. 1989. Multivariate calibration. John Wiley & Sons, Chichester.
20. Menesatti, P., F. Antonuccia, F. Pallottinoa et al. 2010. [Citrus sinensis (L) Osbeck cv Tarocco] Estimation of plant nutritional status by Vis- NIR spectrophotometric analysis on orange leaves. Biosystems Eng. 105:448-454. doi:10.1016/j.biosystemseng.2010.01.003
21. Moore, K.J., C.A. Roberts, and J.O. Fritz. 1990. Indirect estimation of botanical composition of alfalfa-smooth bromegrass mixtures. Agron. J. 82:287-290. doi:10.2134/agronj1990.00021962008200020022x
22. Murray, I., and A.P. Hall. 1983. Animal feed evaluation by use of near infrared reflectance (NIR) spectrocomputer. Anal. Proc. 20:75-78.
23. Nguyen, H.T., and B.W. Lee. 2006. Assessment of rice leaf growth and nitrogen status by hyperspectral canopy reflectance and partial least square regression. Eur. J. Agron. 24:349-356. doi:10.1016/j.eja.2006.01.001
24. Rotbart, N., Z. Schmilovitch, Y. Cohen, V. Alchanatis, R. Erel, T. Ignat, C. Shenderey, A. Dag, and U. Yermiyahu. 2013. Estimating olive leaf nitrogen concentration using visible and near-infrared spectral reflectance. Biosystems Eng. 114: 426-434.
25. Sepulcre-Canto, G., P.J. Zarco-Tejadaa, J.C. Jiménez-Munoz, J.A. Sobrino, M.A. Soriano, E. Fereres et al. 2007. Monitoring yield and fruit quality parameters in open-canopy tree cropsunder water stress. Remote Sens. Environ. 107:455-470.
26. Serbin, S.P., D.N. Dillaway, E.L. Kruger, and P.A. Towsend. 2012. Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature. J. Exp. Bot. 63:489-499. doi:10.1093/jxb/err294
27. Shao, Y.N., C.J. Zhao, Y.D. Bao, and Y. He. 2012. Quantification of nitrogen status in rice by least squares support vector machines and reflectance spectroscopy. Food and Bioprocess. Tech. 5:100-107. doi:10.1007/ s11947-009-0267-y
28. Shepherd, K.D., C.A. Palm, C.N. Gachengo, and B. Vanlauwe. 2003. Rapid characterization of organic resource quality for soil and livestock management in tropical agroecosystems using near-infrared spectroscopy. Agron. J. 95:1314-1322. doi:10.2134/agronj2003.1314
29. Shi, J.Y., X.B. Zou, J.W. Zhao, K.L. Wang, Z.W. Chen, X.W. Huang et al. 2012. Nondestructive diagnostics of nitrogen deficiency by cucumber leaf chlorophyll distribution map based on near infrared hyperspectral imaging. Sci. Hortic. (Amsterdam) 138:190-197. doi:10.1016/j. scienta.2012.02.024
30. Sirisomboon, P., M. Tanaka, S. Fujita, and T. Kojima. 2007. Evaluation of pectin constituents of Japanese pear by near infrared spectroscopy. J. Food Eng. 78:701-707. doi:10.1016/j.jfoodeng.2005.11.009
31. Stenberg, B., A. Jonsson, and T. Borjesson. 2005. Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter. Plant Soil 269:251-258. doi:10.1007/s11104-004-0556-1
32. Ulissi, V., F. Antonucci, and P. Benincasa. 2011. Nitrogen content estimation in tomato leaves by VIS-NIR non-destructive spectroscopy. Sensors (Basel Switzerland) 11:6411-6424. doi:10.3390/s110606411
33. Verrelst, J., J.P. Rivera, J. Moreno, G. Camps-Valls. 2013. Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval. ISPRS J. Photogramm. 86:157-167. doi:10.1016/j.isprsjprs.2013.09.012
34. Wang, W., X. Yao, X.F. Yao, Y.C. Tian, X.J. Liu, J. Ni, W.X. Cao, and Y. Zhu. 2012. Estimating leaf nitrogen content with three-band vegetation indices in rice and wheat. Field Crops Res. 129:90-98.
35. Wold, S., M. Sjostrom, and L. Eriksson. 2001. PLS-regression: A basic tool of chemometrics. Chemometr. Intell. Lab. 58:109-130. doi:10.1016/ S0169-7439(01)00155-1
36. Xu, H.R., B. Qi, T. Sun, X.P. Fu, and Y.B. Ying. 2012. Variable selection in visible and near-infrared spectra: Application to on-line determination of sugar content in pears. J. Food Eng. 109:142-147. doi:10.1016/j. jfoodeng.2011.09.022
37. Yao, X., Y. Zhu, Y.C. Tian, W. Feng, and W.X. Cao. 2010. Exploring hyperspectral bands and estimation indices for leaf nitrogen accumulation in wheat. Int J. Appl. Earth Obs. 12:89-100. doi:10.1016/j. jag.2009.11.008
38. Ye, X., K. Sakai, A. Sasao, and S. Asada. 2008. Potential of airborne hyperspectral imagery to estimate fruit yield in citrus. Chemometr. Intell. Lab. 90:132-144. doi:10.1016/j.chemolab.2007.09.002
39. Zhao, K.G., D. Valle, S. Popescu, X.S. Zhang, and B. Mallick. 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sens. Environ. 132:102-119. doi:10.1016/j.rse.2012.12.026