Identification of Optical Spectral Signatures for Detecting Cheat and Ryegrass in Winter Wheat

Precision weed management technology has immense potential for treating weed species at a small scale. To this end, however, crop and weeds must be recognized. One approach to this involves identification of reflectance signatures of crops and weeds that differ in the visible and near-infrared (NIR) wavelength region. Reflectance spectra were used for the detection of cheat (Bromus secalinus L.), ryegrass (Lolium multiflorum Lam.), and winter wheat (Triticum aestivum L.) under greenhouse conditions. A total of three experiments (two in December 2002 and one in February 2003) were conducted at the Agronomy Research Station, Stillwater, OK. The three species and two N levels were arranged in a completely randomized design with three replications. Spectral readings were taken at Feekes 3 and 5 winter wheat growth stages with a spectrometer. Two spectral measurements were obtained from each pot. The spectral measurements from the three experiments were combined by the two growth stages because preliminary analysis revealed that date of measurement and N levels were not significant. The spectral readings were measured at 1-nm intervals and averaged into 10-nm bandwidths for the wavelengths from 400 to 865 nm. Data were analyzed using a discriminant analysis procedure. The discriminant function with the band combinations 515/675, 555/675, and 805/815 resulted in the best overall correct classification (94%) of observations at Feekes 3, while for spectral data at Feekes 5 the discriminant function with the band combinations 755 and 855/ 675 resulted in 66.7% overall correct classification of observations. In several instances, ryegrass was classified as either cheat or winter wheat, while cheat was classified as rye. Cheat was not classified as winter wheat in most instances. This suggests that it is possible to identify cheat in winter wheat using wavelength ratios developed from spectral readings in 10-nm bands between 500 and 860 nm.

[1]  A. Mallarino,et al.  Phosphorus and Potassium Fertilization and Placement Methods for Corn-Soybean Rotations Managed with No-Till and Chisel Plow Tillage , 2005 .

[2]  A. Smith,et al.  Weed–Crop Discrimination Using Remote Sensing: A Detached Leaf Experiment1 , 2003, Weed Technology.

[3]  M. Silberbush,et al.  RESPONSE OF MAIZE TO FOLIAR VS. SOIL APPLICATION OF NITROGEN–PHOSPHORUS–POTASSIUM FERTILIZERS , 2002 .

[4]  A. Eshel,et al.  Simulation of ion uptake from the soil. , 2002 .

[5]  T Eichert,et al.  Quantification of stomatal uptake of ionic solutes using a new model system. , 2001, Journal of experimental botany.

[6]  H. Kirnak,et al.  ENHANCEMENT OF GROWTH AND NORMAL GROWTH PARAMETERS BY FOLIAR APPLICATION OF POTASSIUM AND PHOSPHORUS IN TOMATO CULTIVARS GROWN AT HIGH (NaCl) SALINITY , 2001 .

[7]  Ning Wang,et al.  DESIGN OF AN OPTICAL WEED SENSOR USINGPLANT SPECTRAL CHARACTERISTICS , 2001 .

[8]  Developing New Remote Sensing Technology for More Economical Weed Control , 2001 .

[9]  D. Plénet,et al.  Phosphorus Deficiency Affects the Rate of Emergence and Number of Maize Adventitious Nodal Roots , 2000 .

[10]  T. Borregaard,et al.  Crop–weed Discrimination by Line Imaging Spectroscopy , 2000 .

[11]  S. Christensen,et al.  Colour and shape analysis techniques for weed detection in cereal fields , 2000 .

[12]  J. V. Stafford,et al.  Weed detection using canopy reflectance. , 1999 .

[13]  H. Goldbach,et al.  Evidence for the Uptake of Large Anions through Stomatal Pores , 1998 .

[14]  Luc Van Gool,et al.  Sensor for Weed Detection Based on Spectral Measurements , 1998 .

[15]  Reyer Zwiggelaar,et al.  A review of spectral properties of plants and their potential use for crop/weed discrimination in row-crops , 1998 .

[16]  R. Lawrence,et al.  Comparisons among vegetation indices and bandwise regression in a highly disturbed, heterogeneous landscape : Mount St. Helens, Washington , 1998 .

[17]  J. Lamb,et al.  Agronomic and Environmental Management of Phosphorus , 1998 .

[18]  Mats Rudemo,et al.  Assessment of weed density at an early stage by use of image processing , 1997 .

[19]  N. Z. C. Chaisattapagon,et al.  Effective criteria for weed identification in wheat fields using machine vision , 1995 .

[20]  M. R. Gebhardt,et al.  Algorithms for Extracting Leaf Boundary Information from Digital Images of Plant Foliage , 1995 .

[21]  George E. Meyer,et al.  Shape features for identifying young weeds using image analysis , 1994 .

[22]  J. C. Price.  How unique are spectral signatures , 1994 .

[23]  T. C. Daniel,et al.  Managing Agricultural Phosphorus for Protection of Surface Waters: Issues and Options , 1994 .

[24]  J. Sawyer.  Concepts of Variable Rate Technology with Considerations for Fertilizer Application , 1994 .

[25]  R. B. Brown,et al.  Remote Sensing for Identification of Weeds in No-till Corn , 1994 .

[26]  J. V. Stafford,et al.  Spatially selective application of herbicide to cereal crops , 1993 .

[27]  P. J. Pinter,et al.  Remote sensing for crop protection , 1993 .

[28]  Gaines E. Miles,et al.  Application of machine vision to shape analysis in leaf and plant identification , 1993 .

[29]  W. Simonton,et al.  Identification of Plant Parts Using Color and Geometric Image Data , 1993 .

[30]  David G. Hopkins,et al.  Variable Fertilizer Application Based on Yield Goal, Soil Fertility, and Soil Map Unit , 1993 .

[31]  S. A. Barber,et al.  Maize Root Distribution between Phosphorus‐Fertilized and Unfertilized Soil , 1992 .

[32]  J. V. Stafford,et al.  Potential for automatic weed detection and selective herbicide application , 1991 .

[33]  Garik Gutman,et al.  Vegetation indices from AVHRR: An update and future prospects , 1991 .

[34]  D. H. Sander,et al.  Residual effects of various phosphorus application methods on winter wheat and grain sorghum. , 1990 .

[35]  S. A. Barber,et al.  Soil pH and Phosphorus and Potassium Uptake by Maize Evaluated with an Uptake Model , 1990 .

[36]  D. H. Sander,et al.  Diffusion, Adsorption, and Predicted Longevity of Banded Phosphorus Fertilizer in Three Soils , 1990 .

[37]  J. V. Stafford,et al.  Weed detection in cereal crops. , 1990 .

[38]  E. Franz,et al.  THE USE OF LOCAL SPECTRAL PROPERTIES OF LEAVES AS AN AID FOR IDENTIFYING WEED SEEDLINGS IN DIGITAL IMAGES , 1990 .

[39]  Brent Clothier,et al.  Effect of water stress on the canopy architecture and spectral indices of irrigated alfalfa , 1989 .

[40]  D. Barry,et al.  Phosphorus nutritional requirement of maize seedlings for maximum yield , 1989 .

[41]  J. C. Price.  Calibration of satellite radiometers and the comparison of vegetation indices , 1987 .

[42]  Gaines E. Miles,et al.  MACHINE VISION AND IMAGE PROCESSING FOR PLANT IDENTIFICATION. , 1986 .

[43]  R. Jackson,et al.  Spectral response of architecturally different wheat canopies , 1986 .

[44]  Foliar FERTILIZAnON.  Foliar Fertilization , 1986, Developments in Plant and Soil Sciences.

[45]  E. J. Kamprath,et al.  Soil Nutrient Bioavailability—A Mechanistic Approach , 1985 .

[46]  H. Gausman,et al.  Plant Leaf Optical Properties in Visible and Near-Infrared Light , 1985 .

[47]  A. Mehlich.  Mehlich 3 soil test extractant: A modification of Mehlich 2 extractant , 1984 .

[48]  John A. Richards,et al.  On the concept of spectral class , 1984 .

[49]  R. H. Shaw,et al.  Corn Grain Yield and Nutrient Response to Foliar Fertilizer Applied during Grain Fill1 , 1982 .

[50]  C. A. Black,et al.  Foliar Application of P. II. Yield Responses of Corn and Soybeans Sprayed with Various Condensed Phosphates and P‐N Compounds in Greenhouse and Field Experiments1 , 1979 .

[51]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[52]  R. Kniseley,et al.  Inductively Coupled Plasma-Optical Emission Spectroscopy , 1974 .

[53]  David G. Kleinbaum,et al.  Testing linear.hypotheses in generalized multivariate linear models , 1973 .

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

[55]  Wolfgang Franke,et al.  Mechanisms of Foliar Penetration of Solutions , 1967 .

[56]  J. Hanway.  How a corn plant develops , 1966 .

[57]  L. J. Middleton,et al.  The Uptake of Inorganic Ions by Plant Leaves , 1965 .

[58]  H. Linskens,et al.  Cuticula of leaves and the residue problem , 1965 .

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

[60]  J. P. Cooper.  Climatic Variation in Forage Grasses. I. Leaf Development in Climatic Races of Lolium and Dactylis , 1964 .

[61]  C. D. Dybing,et al.  Foliar penetration by chemicals. , 1961, Plant physiology.

[62]  J. Mitchell,et al.  Experiments with Radiophosphorus on the Uptake of Phosphorus by Wheat , 2016 .

[63]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[64]  P. Mahalanobis.  On the generalized distance in statistics , 1936 .