Hyperspectral spectrometry as a means to differentiate uninfested and infested winter wheat by greenbug (Hemiptera: Aphididae).

Although spectral remote sensing techniques have been used to study many ecological variables and biotic and abiotic stresses to agricultural crops over decades, the potential use of these techniques for greenbug, Schizaphis graminum (Rondani) (Hemiptera: Aphididae) infestations and damage to wheat, Triticum aestivum L., under field conditions is unknown. Hence, this research was conducted to investigate: 1) the applicability and feasibility of using a portable narrow-banded (hyperspectral) remote sensing instrument to identify and discern differences in spectral reflection patterns (spectral signatures) of winter wheat canopies with and without greenbug damage; and 2) the relationship between miscellaneous spectral vegetation indices and greenbug density in wheat canopies growing in two fields and under greenhouse conditions. Both greenbug and reflectance data were collected from 0.25-, 0.37-, and 1-m2 plots in one of the fields, greenhouse, and the other field, respectively. Regardless of the growth conditions, greenbug-damaged wheat canopies had higher reflectance in the visible range and less in the near infrared regions of the spectrum when compared with undamaged canopies. In addition to percentage of reflectance comparison, a large number of spectral vegetation indices drawn from the literature were calculated and correlated with greenbug density. Linear regression analyses revealed high relationships (R2 ranged from 0.62 to 0.85) between greenbug density and spectral vegetation indices. These results indicate that hyperspectral remotely sensed data with an appropriate pixel size have the potential to portray greenbug density and discriminate its damage to wheat with repeated accuracy and precision.

[1]  H. Nilsson Hand-held radiometry and IR-thermography of plant diseases in field plot experiments† , 1991 .

[2]  R. Merton,et al.  MONITORING COMMUNITY HYSTERESIS USING SPECTRAL SHIFT ANALYSIS AND THE RED-EDGE VEGETATION STRESS INDEX , 1998 .

[3]  Walter E. Riedell,et al.  Leaf Reflectance Spectra of Cereal Aphid-Damaged Wheat , 1999 .

[4]  A. Huete,et al.  A Modified Soil Adjusted Vegetation Index , 1994 .

[5]  R. Campbell,et al.  Ultrastructural responses of resistant and susceptible wheat to infestation by greenbug biotype E (Homoptera: Aphididae) , 1994 .

[6]  A. Huete A soil-adjusted vegetation index (SAVI) , 1988 .

[7]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[8]  T. Malthus,et al.  High resolution spectroradiometry: Spectral reflectance of field bean leaves infected by Botrytis fabae , 1993 .

[9]  John A. Gamon,et al.  Assessing leaf pigment content and activity with a reflectometer , 1999 .

[10]  D. M. Gates,et al.  Spectral Properties of Plants , 1965 .

[11]  Christopher B. Field,et al.  Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves☆ , 1994 .

[12]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[13]  C. Raikes,et al.  Use of multispectral radiometry for assessment of rhizoctonia blight in creeping bentgrass. , 1998, Phytopathology.

[14]  C. Jordan Derivation of leaf-area index from quality of light on the forest floor , 1969 .

[15]  H. Poilvé,et al.  Hyperspectral Imaging and Stress Mapping in Agriculture , 1998 .

[16]  H. Nilsson Remote sensing and image analysis in plant pathology. , 1995, Annual review of phytopathology.

[17]  M. S. Moran,et al.  Remote Sensing for Crop Management , 2003 .

[18]  Z. Yanga,et al.  Using ground-based multispectral radiometry to detect stress in wheat caused by greenbug ( Homoptera : Aphididae ) infestation , 2005 .

[19]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[20]  G. Rondeaux,et al.  Optimization of soil-adjusted vegetation indices , 1996 .

[21]  Andrew D. Richardson,et al.  Drought Stress and Paper Birch (Betula Papyrifera) Seedlings: Effects of an Organic Biostimulant on Plant Health and Stress Tolerance, and Detection of Stress Effects With Instrument-Based, Noninvasive Methods , 2004, Arboriculture & Urban Forestry.

[22]  Zhihao Qin,et al.  Detection of rice sheath blight for in-season disease management using multispectral remote sensing , 2005 .

[23]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[24]  L. Johnsson,et al.  Hand-held radiometry of barley infected by barley stripe disease in a field experiment , 1996 .

[25]  S. Ustin,et al.  Detection of stress in tomatoes induced by late blight disease in California, USA, using hyperspectral remote sensing , 2003 .

[26]  A. Gitelson,et al.  Remote estimation of chlorophyll content in higher plant leaves , 1997 .