Spectral response of gram varieties under variable soil conditions

The spectral response of gram ( Cicer arietinum ) varieties was studied in a crop sequence experiment conducted on three soils in Gondkhairi watershed, Nagpur district of Maharashtra state. A poor relationship between leaf area and Normalized Difference Vegetation Index (NDVI) ( r =0.17) and IR/R ( r =0.11) was observed in ICCV-88202 and ICCC-37 varieties 66 days after sowing (DAS). The hypothesis that short-duration varieties should show a significant positive correlation (due to these crops attaining high biomass at an early growth stage) did not hold good. Contrary to this, in ICCV-10 (a medium maturing variety) the leaf area showed a poor relation with NDVI ( r =0.39) and IR/R ( r =0.45) at 84 DAS. As varieties ICCV-88202 (V 2 ) and ICCC-37 (V 3 ) in soil types S 1 and S 2 are high in biomass at 66 DAS (as is evident from the high values of leaf area) the possible reason for such a poor relationship is masking the effect due to profuse violet and pink flowers at the top of the plant canopy. Analysis of variance (ANOVA) results indicate that the influences due to soils and varieties yield a significant difference in IR/R ratio but a non-significant difference in NDVI both at 66 and 84 DAS. In gram with indeterminate growth habit, the biophysical parameters showed a more consistent relationship with IR/R ratio than with NDVI. The yield prediction is expected to be more valid for ICCV-10 at 66 DAS ( R 2 =0.90**), whereas ICCV-88202 and ICCC-37 are similar for such a prediction both at 66 DAS (V 2, R 2 =0.66*; V 3, R 2 =0.81**) and 84 DAS (V 2, R 2 =0.66*; V 3, R 2 =0.78**). Regression models encompassing varietal and soil influences at different growth stages were simulated to predict yields.

[1]  C. Sastri,et al.  Radiometric measurements for pearl millet crop , 1995 .

[2]  C. Tucker,et al.  North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer , 1985, Vegetatio.

[3]  Marvin E. Bauer,et al.  Spectral estimates of solar radiation intercepted by corn canopies. , 1983 .

[4]  S. Running,et al.  Relationship of thematic mapper simulator data to leaf area index , 1987 .

[5]  A. Kuusk.  Monitoring of vegetation parameters on large areas by the inversion of a canopy reflectance model , 1998 .

[6]  María Amparo Gilabert,et al.  Environmental monitoring and crop forecasting in the Sahel through the use of NOAA NDVI data. A case study: Niger 1986–89 , 1993 .

[7]  R. M. Hoffer,et al.  Biomass estimation on grazed and ungrazed rangelands using spectral indices , 1998 .

[8]  P. J. Curran,et al.  The importance of measurement error for certain procedures in remote sensing at optical wavelengths , 1986 .

[9]  S. Goward,et al.  Evaluating North American net primary productivity with satellite observations , 1987 .

[10]  A new editorial team , 1998 .

[11]  Thomas F. Eck,et al.  Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance , 1991 .

[12]  Jai Singh Parihar,et al.  Wheat acreage estimation for Haryana using satellite digital data , 1991 .

[13]  Differentiation of oil seed crops by remote sensing based on their spectral reflectance pattern , 1994 .

[14]  R. Navalgund,et al.  Spectral signature studies in optical region , 1981 .

[15]  J. Franklin,et al.  Reflectance of vegetation and soil in Chihuahuan desert plant communities from ground radiometry using SPOT wavebands , 1993 .

[16]  Bas A. M. Bouman,et al.  Linking physical remote sensing models with crop growth simulation models, applied for sugar beet , 1992 .

[17]  C. Tucker,et al.  Satellite remote sensing of primary production , 1986 .

[18]  T. N. Hajare,et al.  Gram yield estimation through SVI under variable soil and management conditions , 1998 .

[19]  Douglas Stow,et al.  Assessing the relationship between spectral vegetation indices and shrub cover in the Jornada Basin, New Mexico , 1993 .

[20]  R. Jackson,et al.  Spectral response of a plant canopy with different soil backgrounds , 1985 .

[21]  N. Kalra,et al.  Assessing growth and yield of wheat using remotely-sensed canopy temperature and spectral indices , 1993 .