Multispectral Reflectance of Cotton Related to Plant Growth, Soil Water and Texture, and Site Elevation

Radiometric data can be useful to determine the impact of field heterogeneity, irrigation, and fertilization on plant water and N use. A 2-yr (1998-1999) study was conducted on the South Texas High Plains to investigate cotton (Gossypium hirsutum L.) spectral and agronomic responses to irrigation and N fertilization and to determine the simple and cross correlation among cotton reflectance, plant growth, N uptake, lint yield, site elevation (SE), and soil water and texture. The treatments were irrigation at 50 and 75% of calculated cotton evapotranspiration (ET) and N rates of 0, 90, and 135 kg ha -1 arranged in an incomplete block of size-2 design. Plant and soil spectral properties were investigated within a wavelength of 447 to 1752 nm. Near-infrared (NIR) reflectance was positively correlated with plant biomass and N uptake. Reflectance in the red and midinfrared band increased with SE. The mixed-model analysis showed that cotton NIR reflectance, normalized difference vegetative index (NDVI), soil water, N uptake, and lint yield were significantly affected by irrigation (P < 0.0012). The N treatment had no effect on spectral parameters, and interaction between irrigation and N fertilizer was significant on NIR reflectance (P < 0.0027). All spectral and agronomic parameters measured were associated with SE. The red and NIR reflectance and NDVI were cross-correlated with soil water, sand, clay, and SE across a distance of 60 to 80 m. Characterization of plant and soil reflectance and their spatial structure can be the basis for variable N application on heterogeneous fields to increase N use efficiency.

[1]  Eric R. Ziegel,et al.  SAS® System for Mixed Models@@@SAS registered System for Mixed Models , 1997 .

[2]  H. R. Duke,et al.  Remote Sensing of Plant Nitrogen Status in Corn , 1996 .

[3]  G. Asner Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .

[4]  M. S. Moran,et al.  Bidirectional Calibration Results for 11 Spectralon and 16 BaSO4 Reference Reflectance Panels , 1992 .

[5]  D. K. Cassel,et al.  Assessing Spatial Variability in an Agricultural Experiment Station Field: Opportunities Arising from Spatial Dependence , 2000 .

[6]  K. Bronson,et al.  Cotton lint yield variability in a heterogeneous soil at a landscape scale , 2001 .

[7]  M. E. Bauer,et al.  Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies , 1983 .

[8]  M. S. Moran,et al.  Field calibration of reference reflectance panels , 1987 .

[9]  A. Bégué Leaf area index, intercepted photosynthetically active radiation, and spectral vegetation indices: A sensitivity analysis for regular-clumped canopies , 1993 .

[10]  Ray D. Jackson,et al.  Remote Sensing Of Vegetation Characteristics For Farm Management , 1984, Other Conferences.

[11]  José M. Paruelo,et al.  Interannual variability of NDVI and its relationship to climate for North American shrublands and grasslands , 1998 .

[12]  R. Lascano,et al.  Estimation of Leaf Area Index for Cotton Canopies Using the LI-COR LAI-2000 Plant Canopy Analyzer , 1995 .

[13]  C. L. van Es,et al.  Spatial Nature of Randomization and Its Effect on the Outcome of Field Experiments , 1993 .

[14]  D. K. Cassel,et al.  Application of Regionalized Variable Theory to Large‐Plot Field Experiments , 1989 .

[15]  William D. Bowman,et al.  The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves , 1989 .

[16]  R. W. Whitney,et al.  Use of Spectral Radiance for Correcting In-season Fertilizer Nitrogen Deficiencies in Winter Wheat , 1996 .

[17]  Robert J. Lascano,et al.  Spatial and temporal distribution of surface water content in a large agricultural field , 1999 .

[18]  John B. Solie,et al.  Detection of nitrogen and phosphorus nutrient status in winter wheat using spectral radiance , 1998 .

[19]  C. Daughtry,et al.  Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies , 1992 .

[20]  R. Jackson,et al.  Multisite Analyses of Spectral-Biophysical Data for Wheat , 1992 .

[21]  J. Schepers,et al.  Nitrogen Deficiency Detection Using Reflected Shortwave Radiation from Irrigated Corn Canopies , 1996 .

[22]  W. M. Lyle,et al.  Low Energy Precision Application (LEPA) Irrigation System , 1981 .

[23]  B. R. Roberts,et al.  RELATIONSHIPS BETWEEN REMOTELY SENSED REFLECTANCE DATA AND COTTON GROWTH AND YIELD , 2000 .

[24]  Y. Pachepsky,et al.  Seasonal changes in fractal landscape surface roughness estimated from airborne laser altimetry data , 1998 .

[25]  I C Edmundson,et al.  Particle size analysis , 2013 .

[26]  R. Littell SAS System for Mixed Models , 1996 .

[27]  J. Everitt,et al.  Photographic and videographic observations for determining and mapping the response of cotton to soil salinity , 1994 .

[28]  M. Bauer,et al.  Effects of Cultural Practices on Agronomic and Reflectance Characteristics of Soybean Canopies1 , 1982 .

[29]  Stephan J. Maas,et al.  Estimating cotton canopy ground cover from remotely sensed scene reflectance , 1998 .

[30]  M. Bauer,et al.  Effects of Nitrogen Nutrition on the Growth, Yield, and Reflectance Characteristics of Corn Canopies 1 , 1982 .

[31]  W. Bausch Soil background effects on reflectance-based crop coefficients for corn☆ , 1993 .