Measuring leaf nitrogen concentration in winter wheat using double-peak spectral reflection remote sensing data

Field Crops Research

Volumn 159, Issue , 2014, Pages 43-52

  Feng, Wei ^a   Guo, Bin Bin ^a   Wang, Zhi Jie ^b   He, Li ^a   Song, Xiao ^a   Wang, Yong Hua ^a   Guo, Tian Cai ^a  

^a HENAN AGRICULTURAL UNIVERSITY   (China)

^b UNIVERSITY OF LETHBRIDGE   (Canada)

Author keywords

Double peak area; Leaf nitrogen concentration; Monitoring model; Remote sensing; Winter wheat

Indexed keywords

EID: 84894037546     PISSN: 03784290     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fcr.2014.01.010     Document Type: Article

References (54)

1. Asner G.P., Martin R.E., Knapp D.E., Tupayachi R., Anderson C., Carranza L., Martinez P., Houcheime M., Sinca F., Weiss P. Spectroscopy of canopy chemicals in humid tropical forests. Remote Sens. Environ. 2011, 115:3587-3598.
2. Baret F., Houlès V., Guérif M. Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management. J. Exp. Bot. 2007, 58:869-880.
3. Blackmer T.M., Schepers J.S., Varvel G.E., Walter-Shea E.A. Nitrogen deficiency detection using reflected shortwave radiation from irrigated corn canopies. Agron. J. 1996, 88:1-5.
4. Boochs F., Kupfer G., Docter K., Kühbauch W. Shape of the red edge as vitality indicator for plants. Int. J. Remote Sens. 1990, 11:1741-1753.
5. Broge N.H., Leblanc E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sens. Environ. 2000, 76:156-172.
6. Carter G.A., Cibula W.G., Dell T.R. Spectral reflectance characteristics and digital imagery of a pine needle blight in the southeastern United States. Can. J. Forest Res. 1996, 26:402-407.
7. Chen P.F., Haboudane D., Tremblay N., Wang J.H., Vigneault P., Li B.G. New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat. Remote Sens. Environ. 2010, 114:1987-1997.
8. Cho M.A., Skidmore A.K. A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method. Remote Sens. Environ. 2006, 101:181-193.
9. Clevers J.G.P.W., Kooistra L., Salas E.A.L. Study of heavy metal contamination in river floodplains using the red-edge position in spectroscopic data. Int. J. Remote Sens. 2004, 25:3883-3895.
10. Dash J., Curran P.J. The MERIS terrestrial chlorophyll index. Int. J. Remote Sens. 2004, 25:5403-5413.
11. Delegido J., Alonso L., Gonza'lez G., Moreno J. Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC). Int. J. Appl. Earth Observ. Geoinfor. 2010, 12:165-174.
12. Demetriades-Shah T.H., Steven M.D., Clark J.A. High resolution derivative spectra in remote sensing. Remote Sens. Environ. 1990, 33:55-64.
13. Ecarnot M., Compan F., Roumet P. Assessing leaf nitrogen content and leaf mass per unit area of wheat in the field throughout plant cycle with a portable spectrometer. Field Crop Res. 2013, 140:44-50.
14. Feng W., Yao X., Zhu Y., Tian Y.C., Cao W.X. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. Eur. J. Agron. 2008, 28:394-404.
15. Gaju O., Allard V., Martre P., Le Gouis J., Moreau D., Bogard M., Hubbart S., Foulkes M.J. Nitrogen partitioning and remobilization in relation to leaf senescence, grain yield and grain nitrogen concentration in wheat cultivars. Field Crop Res. 2014, 155:213-223.
16. Gitelson A.A., Kaufman Y.J., Stark R., Rundquist D. Novel algorithms for remote estimation of vegetation fraction. Remote Sens. Environ. 2002, 80:76-87.
17. Gitelson A.A., Merzlyak M.N. Spectral reflectance changes associate with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves spectral features and relation to chlorophyll estimation. J. Plant Physiol. 1994, 143:286-292.
18. Gitelson A.A., Merzlyak M.N. Remote estimation of chlorophyll content in higher plant leaves. Int. J. Remote Sens. 1997, 18:2691-2697.
19. Gong P., Pu R.L., Heald R.C. Analysis of in situ hyperspectral data for nutrient estimation of giant sequoia. Int. J. Remote Sens. 2002, 23:1827-1850.
20. Gupta R.K., Vijayan D., Prasad T.S. Comparative analysis of red edge hyperspectral indices. Adv. Space Res. 2003, 32:2217-2222.
21. Hansen P.M., Schjoerring J.K. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sens. Environ. 2003, 86:542-553.
22. Hatfield J.L., Gitelson A.A., Schepers J.S., Walthall C.L. Application of spectral remote sensing for agronomic decisions. Agron. J. 2008, 100:117-131.
23. Horler D.N.H., Dockray M., Barber J. The red edge of plant leaf reflectance. Int. J. Remote Sens. 1983, 4:273-288.
24. Huang Z., Turner B.J., Dury S.J., Wallis I.R., Foley W.J. Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis. Remote Sens. Environ. 2004, 93:18-29.
25. Inoue Y., Sakaiya E., Zhu Y., Takahashi W. Diagnostic mapping of canopy nitrogen content in rice based on hyperspectral measurements. Remote Sens. Environ. 2012, 126:210-221.
26. Jamieson P.D., Porter J.R., Wilson D.R. A test of the computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Field Crop Res. 1991, 27:337-350.
27. Jongschaap R.E.E., Booij R. Spectral measurements at different spatial scales in potato: relating leaf, plant and canopy nitrogen status. Int. J. Appl. Earth Obser. Geoinfor. 2004, 5:205-218.
28. Ju X.T., Xing G.X., Chen X.P., Zhang S.L., Zhang L.J., Liu X.J., Cui Z.L., Yin B., Christie P., Zhu Z.L., Zhang F.S. Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:3041-3046.
29. Lacapra V.C., Melack J.M., Gastil M., Valerino D. Remote sensing of inundated rice with imaging spectrometry. Remote Sens. Environ. 1996, 55:50-58.
30. Lamb D.W., Steyn-Ross M., Schaare P., Hanna M.M., Silvester W., Steyn-Coss A. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modeling and experimental observations. Int. J. Remote Sens. 2002, 23:3619-3648.
31. Le Maire G., François C., Dufrêne E. Towards universal deciduous broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sens. Environ. 2004, 89:1-28.
32. Lee T., Reddy K.R., Sassenrath-Cole G.F. Reflectance indices with precision and accuracy in predicting cotton leaf nitrogen concentration. Crop Sci. 2000, 40:1814-1819.
33. Li F., Mistele B., Hu Y.C., Chen X.P., Schmidhalter U. Comparing hyperspectral index optimization algorithms to estimate aerial N uptake using multi-temporal winter wheat datasets from contrasting climatic and geographic zones in China and Germany. Agri. For. Meteorol. 2013, 180:44-57.
34. Martin M.E., Aber J.D. Estimation of forest canopy lignin and nitrogen concentration and ecosystem processes by high spectral resolution remote sensing. Ecol. Appl. 1997, 7:431-443.
35. Miller J.R., Hare E.W., Wu J. Quantitative characterization of the vegetation red edge reflectance 1. An inverted-Gaussian reflectance model. Int. J. Remote Sens. 1990, 11:1755-1773.
36. Mistele B., Schmidhalter U. Tractor-based quadrilateral spectral reflectance measurements to detect biomass and total aerial nitrogen in winter wheat. Agron. J. 2010, 102:499-506.
37. Oppelt N., Mauser W. Hyperspectral monitoring of physiological of wheat during a vegetation period using AVIS data. Int. J. Remote Sens. 2004, 25:145-159.
38. Raun W.R., Johnson G.V. Improving nitrogen use efficiency for cereal production. Agron. J. 1999, 91:357-363.
39. Ren H.R., Zhou G.S., Zhang X.S. Estimation of green aboveground biomass of desert steppe in Inner Mongolia based on red-edge reflectance curve area method. Biosyst. Eng. 2011, 109:385-395.
40. Schächtl J., Huber G., Maidl F.X., Sticksel E., Schulz J., Haschberger P. Laser-induced chlorophyll fluorescence measurements for detecting the nitrogen status of wheat (Triticum aestivum L.) canopies. Precis Agric. 2005, 6:143-156.
41. Sims D.A., Gamon J.A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sens. Environ. 2002, 81:331-354.
42. Smith K.L., Steven M.D., Colls J.J. Spectral responses of pot-grown. Plants to displacement of soil oxygen. Int. J. Remote Sens. 2004, 25:4395-4410.
43. Tang Y.L., Wang R.C., Huang J.F. Relations between red edge characteristics and agronomic parameters of crops. Pedosphere 2004, 14:467-474.
44. Thenkabail P.S., Smith R.B., Pauw E.D. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sens. Environ. 2000, 71:158-182.
45. Turner F.T., Jund M.F. Assessing the nitrogen requirements of rice crops with a chlorophyll meter. Aust. J. Exp. Agric. 1994, 34:1001-1005.
46. van Evert F.K., Booij R., Jukema J.N., ten Berge H.F.M., Uenk D., Meurs E.J.J., van Geel W.C.A., Wijnholds K.H., Slabbekoorn J.J. Using crop reflectance to determine sidedress N rate in potato saves N and maintains yield. Eur. J. Agron. 2012, 43:58-67.
47. Vogelmann J.E., Rock B.N., Moss D.M. Red-edge spectral measurements from Sugar Maple leaves. Int. J. Remote Sens. 1993, 14:1563-1575.
48. Wang W., Yao X., Yao X.F., Tian Y.C., Liu X.J., Ni J., Cao W.X., Zhu Y. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crop Res. 2012, 129:90-98.
49. Wang Z.J., Wang J.H., Liu L.Y., Huang W.J., Zhao C.J., Wang C.Z. Prediction of grain protein content in winter wheat (Triticum aestivum L.) using plant pigment ratio (PPR). Field Crop Res. 2004, 90. 331-321.
50. Xue L.H., Yang L.Z. Recommendations for nitrogen fertilizer topdressing rates in rice using canopy reflectance spectra. Biosys. Eng. 2008, 100:524-534.
51. Zarco-Tejada P.J., Miller J.R., Mohammed G.H., Noland T.L., Sampson P.H. Scaling-up and model inversion methods with narrow-band optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Trans. Geosci. Remote Sens. 2001, 39:1491-1507.
52. Zarco-Tejada P.J., Pushnik J.C., Dobrowski S., Ustin S.L. Steady state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects. Remote Sens. Environ. 2003, 84:283-294.
53. Zhang F.S., Ma W.Q. The relationship between fertilizer input level and nutrient use efficiency. Soil Environ. Sci. 2000, 9:154-157.
54. Zhu Y., Li Y.X., Feng W., Tian Y.C., Yao X., Cao W.X. Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Can. J. Plant Sci. 2006, 86:1037-1046.