Remote detection of canopy leaf nitrogen concentration in winter wheat by using water resistance vegetation indices from in-situ hyperspectral data

Field Crops Research

Volumn 198, Issue , 2016, Pages 238-246

  Feng, Wei ^a   Zhang, Hai Yan ^a   Zhang, Yuan Shuai ^a   Qi, Shuang Li ^a   Heng, Ya Rong ^a   Guo, Bin Bin ^a   Ma, Dong Yun ^a   Guo, Tian Cai ^a  

^a HENAN AGRICULTURAL UNIVERSITY   (China)

Author keywords

Estimation model; Hyperspectral remote sensing; Leaf nitrogen concentration; Water resistance vegetation index; Winter wheat

Indexed keywords

AGRICULTURAL MODELING; CLIMATE CONDITIONS; CROP PRODUCTION; DATA ACQUISITION; DETECTION METHOD; GROWTH FORM; IN SITU MEASUREMENT; LEAF AREA; NITROGEN; REMOTE SENSING; VEGETATION INDEX; WHEAT;

CHINA;

TRITICUM AESTIVUM;

EID: 84987958845     PISSN: 03784290     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fcr.2016.08.023     Document Type: Article

References (64)

1. Bausch, W.C., Soil background effects on reflectance-based crop coefficients for corn. Remote Sens. Environ. 46 (1993), 213–222.
2. Bertheloot, J., Martre, P., Andrieu, B., Dynamics of light and nitrogen distribution during grain filling within wheat canopy. Plant Physiol. 148 (2008), 1707–1720.
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. 88 (1996), 1–5.
4. Boochs, F., Kupfer, G., Dockter, K., Kühbauch, W., Shape of the red edge as vitality indicator for plants. Remote Sens. 11 (1990), 1741–1753.
5. 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. For. Res. 26 (1996), 402–407.
6. 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. 101 (2006), 181–193.
7. Cohen, Y., Alchanatis, V., Zusman, Y., Dar, Z., Bonfil, D.J., Karnieli, A., Zilberman, A., Moulin, A., Ostrovsky, V., Levi, A., Brikman, R., Shenker, M., Leaf nitrogen estimation in potato based on spectral data and on simulated bands of the VEN(S satellite. Precis. Agric. 11 (2010), 520–537.
8. 2O emission in maize-crops fertilized with pig slurry, matured pig manure or ammonium nitrate in Brittany. Agr. Ecosyst. Environ. 123 (2008), 201–210.
9. Delegido, J., Alonso, L., González, G., Moreno, J., Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC). Int. J. Appl. Earth Observ. Geoinf. 12 (2010), 165–174.
10. Eitel, J., Long, D., Gessler, P., Smith, A., Using in‐situ measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status. Int. J. Remote Sens. 28 (2007), 4183–4190.
11. Elvidge, C.D., Lyon, R.J., Influence of rock-soil spectral variation on the assessment of green biomass. Remote Sens. Environ. 17 (1985), 265–279.
12. Feng, W., Guo, B.B., Wang, Z.J., He, L., Song, X., Wang, Y.H., Guo, T.C., Measuring leaf nitrogen concentration in winter wheat using double-peak spectral reflection remote sensing data. Field Crops Res. 159 (2014), 43–52.
13. Fitzgerald, G.J., Rodriguez, D., Christensen, L.K., Belford, R., Sadras, V.O., Clarke, T.R., Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments. Precis. Agric. 7 (2006), 233–248.
14. Gamon, J., Penuelas, J., Field, C., A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sens. Environ. 41 (1992), 35–44.
15. Gitelson, A., Merzlyak, M.N., Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation. J. Plant Physiol. 143 (1994), 286–292.
16. Gitelson, A.A., Merzlyak, M.N., Remote estimation of chlorophyll content in higher plant leaves. Int. J. Remote Sens. 18 (1997), 2691–2697.
17. Gitelson, A.A., Merzlyak, M.N., Remote sensing of chlorophyll concentration in higher plant leaves. ADV. Space Res. 22 (1998), 689–692.
18. Gitelson, A.A., Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. J. Plant Physiol. 161 (2004), 165–173.
19. Gupta, R.K., Vijayan, D., Prasad, T.S., Comparative analysis of red-edge hyperspectral indices. Adv. Space Res. 32 (2003), 2217–2222.
20. Haboudane, D., Miller, J.R., Tremblay, N., Zarco-Tejada, P.J., Dextraze, L., Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sens. Environ. 81 (2002), 416–426.
21. Haboudane, D., Miller, J.R., Pattey, E., Zarco-Tejada, P.J., Strachan, I.B., Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture. Remote Sens. Environ. 90 (2004), 337–352.
22. 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. 86 (2003), 542–553.
23. Hirose, T., Werger, M.J.A., Pons, T.L., Van Rheenen, J.W.A., Canopy structure and leaf nitrogen distribution in a stand of Lysimachia vulgaris L. as influenced by stand density. Oecologia 77 (1988), 145–150.
24. Huete, A.R., Jackson, R.D., Post, D.F., Spectral response of a plant canopy with different soil backgrounds. Remote Sen. Environ. 17 (1985), 37–53.
25. Huete, A.R., A soil-adjusted vegetation index (SAVI). Remote Sens. Environ. 25 (1988), 295–309.
26. Jin, X.L., Wang, K.R., Xiao, C.H., Diao, W.Y., Wang, F.Y., Chen, B., Li, S.K., Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat. Field Crops Res. 135 (2012), 24–29.
27. Jongschaap, R.E., Booij, R., Spectral measurements at different spatial scales in potato: relating leaf, plant and canopy nitrogen status. Int. J. Appl. Earth Obs. 5 (2004), 205–218.
28. Justes, E., Mary, B., Meynard, J.M., Machet, J.M., Thelier-Huché, L., Determination of a critical nitrogen dilution curve for winter wheat crops. Ann. Bot. London 74 (1994), 397–407.
29. Kamiji, Y., Pang, J., Milroy, S.P., Palta, J.A., Shoot biomass in wheat is the driver for nitrogen uptake under low nitrogen supply: but not under high nitrogen supply. Field Crops Res. 165 (2014), 92–98.
30. Kanke, Y., Raun, W., Solie, J., Stone, M., Taylor, R., Red edge as a potential index for detecting differences in plant nitrogen status in winter wheat. J. Plant Nutr. 35 (2012), 1526–1541.
31. Kaufman, Y.J., Tanre, D., Atmospherically resistant vegetation index(ARVI) for EOS-MODIS. IEEE Trans. Geosci. Remote 30 (1992), 261–270.
32. Lamb, D.W., Steyn-Ross, M., Schaare, P., Hanna, M.M., Silvester, W., Steyn-Ross, A., Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modelling and experimental observations. Int. J. Remote Sens. 23 (2002), 3619–3648.
33. Lee, Y.J., Yang, C.M., Chang, K.W., Shen, Y., A simple spectral index using reflectance of 735 nm to assess nitrogen status of rice canopy. Agron. J. 100 (2008), 205–212.
34. Maccioni, A., Agati, G., Mazzinghi, P., New vegetation indices for remote measurement of chlorophylls based on leaf directional reflectance spectra. J. Photochem. Photobiol. B 61 (2001), 52–61.
35. Madakadze, I.C., Stewart, K.A., Madakadze, R.M., Peterson, P.R., Coulman, B.E., Smith, D.L., Field evaluation of the chlorophyll meter to predict yield and nitrogen concentration of switchgrass. J. Plant Nutr. 22 (1999), 1001–1010.
36. Marshak, A., Knyazikhin, Y., Davis, A.B., Wiscombe, W.J., Pilewskie, P., Cloud-vegetation interaction: use of normalized difference cloud index for estimation of cloud optical thickness. Geophys. Res. Lett. 27 (2000), 1695–1698.
37. Miller, J.R., Hare, E.W., Wu, J., Quantitative characterization of the vegetation red edge reflectance 1. An inverted-Gaussian reflectance model. Remote Sens. 11 (1990), 1755–1773.
38. Nguy-Robertson, A., Gitelson, A., Peng, Y., Viña, A., Arkebauer, T., Rundquist, D., Green leaf area index estimation in maize and soybean: combining vegetation indices to achieve maximal sensitivity. Agron. J. 104 (2012), 1336–1347.
39. Peñuelas, J., Gamon, J.A., Fredeen, A.L., Merino, J., Field, C.B., Reflectance indices associated with physiological changes in nitrogen-and water-limited sunflower leaves. Remote Sens. Environ. 48 (1994), 135–146.
40. Peñuelas, J., Pinol, J., Ogaya, R., Filella, I., Estimation of plant water concentration by the reflectance water index WI (R900/R970). Int. J. Remote Sens. 18 (1997), 2869–2875.
41. Raun, W.R., Johnson, G.V., Improving nitrogen use efficiency for cereal production. Agron. J. 91 (1999), 357–363.
42. Raun, W.R., Solie, J.B., Johnson, G.V., Stone, M.L., Mullen, R.W., Freeman, K.W., Thomason, W.E., Lukina, E.V., Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agron. J. 94 (2002), 815–820.
43. Reyniers, M., Vrindts, E., Measuring wheat nitrogen status from space and ground-based platform. Int. J. Remote Sens. 27 (2006), 549–567.
44. Rondeaux, G., Steven, M., Baret, F., Optimization of soil-adjusted vegetation indices. Remote Sens. Environ. 55 (1996), 95–107.
45. Rouse, J., Haas, R., Schell, J., Deering, D., Harlan, J., Monitoring the Vernal Advancements and Retrogradation of Natural Vegetation., 1974, NASA/GSFC, Final Report, Greenbelt, MD, USA, 1–137.
46. 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. 6 (2005), 143–156.
47. Schepers, J., Francis, D., Thompson, M., Simultaneous determination of total C, total N, and 15N on soil and plant material. Commun. Soil Sci. Plant 20 (1989), 949–959.
48. Sehy, U., Ruser, R., Munch, J.C., Nitrous oxide fluxes from maize fields: relationship to yield, site-specific fertilization, and soil conditions. Agric. Ecosyst. Environ. 99 (2003), 97–111.
49. 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 Sen. Environ. 81 (2002), 337–354.
50. Strachan, I.B., Pattey, E., Boisvert, J.B., Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance. Remote Sens. Environ. 80 (2002), 213–224.
51. Tarpley, L., Reddy, K.R., Sassenrath-Cole, G.F., Reflectance indices with precision and accuracy in predicting cotton leaf nitrogen concentration. Crop Sci. 40 (2000), 1814–1819.
52. Thenkabail, P.S., Smith, R.B., De Pauw, E., Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sens. Environ. 71 (2000), 158–182.
53. Tang, Y.L., Wang, R.C., Huang, J.F., Relations between red edge characteristics and agronomic parameters of crops. Pedosphere 14 (2004), 467–474.
54. Tian, Y., Yang, J., Yao, X., Zhu, Y., Cao, W., A newly developed blue nitrogen index for estimating canopy leaf nitrogen concentration of rice. J. Appl. Ecol. 21 (2010), 966–972.
55. Turner, F., Jund, M., Assessing the nitrogen requirements of rice crops with a chlorophyll meter. Anim. Prod. Sci. 34 (1994), 1001–1005.
56. Van Niel, T., McVicar, T., Current and potential uses of optical remote sensing in rice-based irrigation systems: a review. Crop Pasture Sci. 55 (2004), 155–185.
57. Vogelmann, J., Rock, B., Moss, D., Red edge spectral measurements from sugar maple leaves. Remote Sens. 14 (1993), 1563–1575.
58. Wang, W., Yao, X., Yao, X., Tian, Y., Liu, X., Ni, J., Cao, W., Zhu, Y., Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Res. 129 (2012), 90–98.
59. Yao, X., Ren, H., Cao, Z., Tian, Y., Cao, W., Zhu, Y., Cheng, T., Detecting leaf nitrogen content in wheat with canopy hyperspectrum under different soil backgrounds. Int. J. Appl. Earth Obs. 32 (2014), 114–124.
60. Zarco-Tejada, P.J., Miller, J.R., Noland, T.L., Mohammed, G.H., Sampson, P.H., Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Trans. Geosci. Remote 39 (2001), 1491–1507.
61. Zarco-Tejada, P.J., Pushnik, J., Dobrowski, S., Ustin, S.L., Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects. Remote Sen. Environ. 84 (2003), 283–294.
62. Zhang, F.s., Ma, W.q., The relationship between fertilizer input level and nutrient use efficiency. Soil Environ. Sci., 2, 2000, 018.
63. 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. 86 (2006), 1037–1046.
64. Zhu, Y., Yao, X., Tian, Y., Liu, X., Cao, W., Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. Int. J. Appl. Earth Obs. 10 (2008), 1–10.