Abstract
A field experiment was conducted on wheat crop during rabi seasons of 1995–96, 1996–97 and 1997–98 to study the spectral response of wheat crop (between 490 to 1080 nm) under water and nutrient stress condition. An indigenously developed ground truth radiometer having narrow band in visible and near infrared region (490 – 1080 nm) was used. Vegetation indices derived using different band combinations and related to crop growth parameters. The near infrared spectral region of 710 – 1025 nm was found most important for monitoring stress condition. Relationship has been developed between crop growth parameters and vegetation indices. Leaf Area Index (LAI) and chlorophyll could be predicted by knowing different reflectance ratios at milking stage of crop with R2 value of 0.78 and 0.89, respectively. Dry biomass (DBM), Plant Water Content (PWC) and grain yield are also significantly related with reflectance ratios at flowering stage of crop with R2 value of 0.90, 0.98 and 0.74, respectively.
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References
Aase, J.K., Miliard, J.P. and Brown, B.S. (1986). Spectral radiance estimates of leaf area and leaf phytomass of small grains and native vegetations. IEEE Trans. Geosciences and Remote Sensing24: 685–692.
Asrar, G., Kanemasu, E.T. and Yoshida, M. (1985). Estimates of leaf area index from spectral reflectance of wheat under different cultural practices and sun angle. Remote Sensing of Environment17: 1–11.
Baret, F. and Guyot, G. (1991). Potentials and limits of vegetation Indices for LAI and APAR assessment. Remote Sensing of Environment35: 161–173.
Buschmann, C. and Nagel, E. (1993). In vivo spectroscopy and internal optics of leaves as basic for remote sensing of vegetation. International Journal of Remote Sensing14: 711–722.
Crist, E.P. (1984). Effect of cultural and Environmental factors on corn and soybean spectral development patterns. Remote Sensing of Environment14: 3–13.
Das, D.K. (1998). Remote Sensing Applications in Management of Agricultural Resources- Research Highlights. 1ARI pp: 67–78.
Das, D.K., Mishra, K.K. and Kaira, N. (1993). Assessing growth and yield of wheat using remotely sensed canopy temperature and spectral indices. International Journal of Remote Sensing14: 3081–3092.
Fernandez, S., Vidal, D., Simon, E. and Sole-Sugranes, L. (1994). Radiometric characteristics of Triticum aestivum cv. Astral under water and nitrogen stress. International Journal of Remote Sensing15: 1421–1446.
Hiscox, J.D. and Israelrtam, G.F. (1979) A method for estimation of chlorophyll from leaf tissue without maceration. Canadian Journal of Botany57 (12): 1332–1334.
Lawrence, R.L. and Ripple, W.J. (1998). Comparisons among vegetation indices and band-wise regression in a highly disturbed, heterogeneous landscape: Mount St. Helens, Washington. Remote Sensing of Environment64: 91–102.
Major, D.G., Schaalje, Asrar, G. and Kanemasu, E.T. (1986). Estimation of whole plant biomass and grain yield from spectral reflectance of cereals, Canadian Journal of Remote Sensing12: 47–54.
Patel, N.K., Singh, T.P., Sahai, B. and Patel, M.S. (1985). Spectral response of rice crop and its relation to yield and yield attributes, International Journal of Remote Sensing6: 657–664.
Sellers, P.J. (1985). Canopy reflectance, Photosynthesis and transpiration, International Journal of Remote Sensing6: 1335–1372.
Singh, S.P., Bishnoi, O.P., Niwas, R. and Singh, M. (2001). Relationships of wheat grain yield with spectral indices, Journal of Indian Society of Remote Sensing29: 93–96.
Singh, T.P., Patel, N.K., Navalgund, R.R. and Sahai, B. (1982). Relationship of radiometric and biometric parameters in moisture-stressed wheat, Technical Report, ISRO-SAC-TR-22-82, Indian Space Research Organization, Bangalore, India.
Spanner, M.A., Pierce, L.L., Running, S.W. and Peterson, D.L. (1990). The seasonality of AVHRR data of temperate coniferous forests: Relationship with leaf area index. Remote Sensing of Environment33: 97–112.
Subbarao, Y.V. and Sastri, C.V.S. (1992). Simple remote-sensing technique for leaf-area index and absorbed photosynthetically active radiation in mustard(Brassica juncea) crop. Indian Journal of Agronomy,37: 71–75.
Townshend, J.R.G. and Justice, C.O. (1986). Analysis of the dynamics of African vegetation using the normalized difference vegetation index, International Journal of Remote Sensing,7: 1435–1445.
Tucker, C.J., Miller, L.D. and Pearson, R.L. (1975). Short grass prairie spectral measurements, Photogrammetric Engineering and Remote Sensing41: 1157–1162.
Vaesen, K., Gilliams, S., Nackaerts, K. and Coppin, P. (2001). Ground-measured spectral signatures as indicators of ground cover and leaf area index: the case of paddy rice, Field Crops Research69(1): 13–25.
Wiegand, C.L., Richardsons, A.J., Escobar, D.E. and Gerberman, A.H. (1991). Vegetation indices in crop assessments. Remote Sensing of Environment35: 105–119.
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Gajjar, R.B., Shekh, A.M., Dave, A.J. et al. Assessment of crop growth parameters of wheat under stress condition through ground based spectral data. J Indian Soc Remote Sens 33, 147–153 (2005). https://doi.org/10.1007/BF02990004
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DOI: https://doi.org/10.1007/BF02990004