Field spectroscopy for weed detection in wheat and chickpea fields

International Journal of Remote Sensing

Volumn 34, Issue 17, 2013, Pages 6094-6108

  Shapira, Uri ^a   Herrmann, Ittai ^a   Karnieli, Arnon ^a   Bonfil, David J ^b  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^b VOLCANI CENTER   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; HERBICIDES; REFLECTION; REMOTE SENSING; VEGETATION;

ADVANCED LAND IMAGERS; CLASSIFICATION ACCURACY; CRITICAL PERIOD FOR WEED CONTROLS; ENVIRONMENTAL BENEFITS; ENVIRONMENTAL MONITORING; HERBICIDE APPLICATION; SPECTRAL CLASSIFICATION; SPECTRAL PROPERTIES;

WEED CONTROL;

DISCRIMINANT ANALYSIS; HERBICIDE; LEGUME; PESTICIDE APPLICATION; REMOTE SENSING; SPECTRAL REFLECTANCE; WEED CONTROL; WHEAT;

CICER ARIETINUM; POACEAE; TRITICUM AESTIVUM;

EID: 84879555070     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2013.793860     Document Type: Article

References (56)

1. Alchanatis, V., Ridel, L., Hetzroni, A. and Yaroslavsky, L. 2005. Weed Detection in Multi-Spectral Images of Cotton Fields. Computers and Electronics in Agriculture, 47: 243 - 260.
2. Baudat, G. and Anouar, F. E. 2000. Generalized Discriminant Analysis Using a Kernel Approach. Neural Computation, 12: 2385 - 2404.
3. Bennett, A. L. and Pannell, D. J. 1998. Economic Evaluation of a Weed-Activated Sprayer for Herbicide Application to Patchy Weed Populations. Australian Journal of Agricultural and Resource Economics, 42: 389 - 408.
4. Biewer, S., Erasmi, S., Fricke, T. and Wachendorf, M. 2009. Prediction of Yield and the Contribution of Legumes in Legume-Grass Mixtures Using Field Spectrometry. Precision Agriculture, 10: 128 - 144.
5. Biller, R. H. 1998. Reduced Input of Herbicides by Use of Optoelectronic Sensors. Journal of Agricultural Engineering Research, 71: 357 - 362.
6. Blackshaw, R. E., Molnar, L. J. and Lindwall, C. W. 1998. Merits of a Weed-Sensing Sprayer to Control Weeds in Conservation Fallow and Cropping Systems. Weed Science, 46: 120 - 126.
7. Brent, J. and Schaeffer, T. H. 2011. Systematic Review of Parkinsonian Syndromes in Short- and Long-Term Survivors of Paraquat Poisoning. Journal of Occupational and Environmental Medicine, 53: 1332 - 1336.
8. Brown, R. B. and Steckler, J. 1995. Prescription Maps for Spatially Variable Herbicide Application in No-Till Corn. Transactions of the American Society of Agricultural Engineers, 38: 1659 - 1666.
9. Brown, R. B., Steckler, J. and Anderson, G. W. 1994. Remote-Sensing for Identification of Weeds in No-Till Corn. Transactions of the American Society of Agricultural Engineers, 37: 297 - 302.
10. Chander, G., Markham, B. L. and Helder, D. L. 2009. Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors. Remote Sensing of Environment, 113: 893 - 903.
11. Cohen, J. 1960. A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20: 37 - 46.
12. Deardorff, J. W. 1978. Effcient Prediction of Ground Surface-Temperature and Moistere, Whitch Inclusion of a Layer of Vegetation. Journal of Geophysical Research-Oceans and Atmospheres, 83: 1889 - 1903.
13. Dhawan, A., Bajpayee, M. and Parmar, D. 2009. Comet Assay: A Reliable Tool for the Assessment of DNA Damage in Different Models. Cell Biology and Toxicology, 25: 5 - 32.
14. Eddy, P. R., Smith, A. M., Hill, B. D., Peddle, D. R., Coburn, C. A. and Blackshaw, R. E. 2006. Comparison of Neural Network and Maximum Likelihood High Resolution Image Classification for Weed Detection in Crops: Applications in Precision Agriculture. 2006 IEEE International Geoscience and Remote Sensing Symposium, 1-8: 116 - 119.
15. Feyaerts, F. and van Gool, L. 2001. Multi-spectral Vision System for Weed Detection. Pattern Recognition Letters, 22: 667 - 674.
16. Foody, G. M. 2008. Harshness in Image Classification Accuracy Assessment. International Journal of Remote Sensing, 29: 3137 - 3158.
17. Fraley, C. and Raftery, A. E. 2002. Model-based Clustering, Discriminant Analysis, and Density Estimation. Journal of the American Statistical Association, 97: 611 - 631.
18. Gausman, H. 1985. Plant Leaf Optical Properties in Visible and Near Infrared Light, 9 - 60. Lubbock, TX: Texas Tech Press.
19. Gerhards, R. and Christensen, S. 2003. Real-time Weed Detection, Decision Making and Patch Spraying in Maize, Sugarbeet, Winter Wheat and Winter Barley. Weed Research, 43: 385 - 392.
20. Gerhards, R., Sokefeld, M., Schulze-Lohne, K., Mortensen, D. A. and Kuhbauch, W. 1997. Site Specific Weed Control in Winter Wheat. Journal of Agronomy and Crop Science, 178: 219 - 225.
21. Gibson, K. D., Dirks, R., Medlin, C. R. and Johnston, L. 2004. Detection of Weed Species in Soybean Using Multispectral Digital Images. Weed Technology, 18: 742 - 749.
22. Gibson, L., Kingwell, R. and Doole, G. 2008. The Role and Value of Eastern Star Clover in Managing Herbicide-Resistant Crop Weeds: A Whole-Farm Analysis. Agricultural Systems, 98: 199 - 207.
23. Gray, C. J., Shaw, D. R. and Bruce, L. M. 2009. Utility of Hyperspectral Reflectance for Differentiating Soybean (Glycine max) and Six Weed Species. Weed Technology, 23: 108 - 119.
24. Hamouz, P., Novakova, K., Soukup, J. and Holec, J. 2008. Detection of Cirsium arvense L. in Winter Wheat Using a Multispectral Imaging System. Journal of Plant Diseases and Protection Special Issue XXI:,: 167 - 170.
25. Har Gil, D., Bonfil, D. J. and Svoray, T. 2011. Multi scale Analysis of the Factors Influencing Wheat Quality as Determined by Gluten Index. Field Crops Research, 123: 1 - 9.
26. Herrmann, I., Pimstein, A., Karnieli, A., Cohen, Y., Alchanatis, V. and Bonfil, D. J. 2011. LAI Assessment of Wheat and Potato Crops by VENμS and Sentinel-2 Bands. Remote Sensing of Environment, 115: 2141 - 2151.
27. Johnson, G. A., Mortensen, D. A., Young, L. J. and Martin, A. R. 1995. The Stability of Weed Seedling Population-Models and Parameters in Eastern Nebraska Corn (Zea-Mays) and Soybean (Glycine-Max) Fields. Weed Science, 43: 604 - 611.
28. Jones, R. E., Vere, D. T., Alemseged, Y. and Medd, R. W. 2005. Estimating the Economic Cost of Weeds in Australian Annual Winter Crops. Agricultural Economics, 32: 253 - 265.
29. Jurado-Exposito, M., Lopez-Granados, F., Atenciano, S., Garcia-Torres, L. and Gonzalez-Andujar, J. L. 2003. Discrimination of Weed Seedlings, Wheat (Triticum aestivum) Stubble and Sunflower (Helianthus annuus) by Near-Infrared Reflectance Spectroscopy (NIRS)". Crop Protection, 22: 1177 - 1180.
30. Kafkafi, U. and Bonfil, D. J. 2008. " Integrated Nutrient Management: Experience and Concepts from the Middle East ". In Integrated Nutrient Management for Sustainable Crop Production, Edited by: Aulakh, M. and Grant, C. A. 523 - 565. Binghamton, NY: The Haworth Press.
31. Lamb, D. W. and Brown, R. B. 2001. Remote-sensing and Mapping of Weeds in Crops. Journal of Agricultural Engineering Research, 78: 117 - 125.
32. Lindquist, J. L., Dieleman, J. A., Mortensen, D. A., Johnson, G. A. and Wyse-Pester, D. Y. 1998. Economic Importance of Managing Spatially Heterogeneous Weed Populations. Weed Technology, 12: 7 - 13.
33. Lopez-Granados, F., Pena-Barragan, J. M., Jurado-Exposito, M., Francisco-Fernandez, M., Cao, R., Alonso-Betanzos, A. and Fontenla-Romero, O. 2008. Multispectral Classification of Grass Weeds and Wheat (Triticum durum) Using Linear and Nonparametric Functional Discriminant Analysis and Neural Networks. Weed Research, 48: 28 - 37.
34. Mahalanobis, P. C., Bose, R. C. and Roy, S. N. 1937. Normalization of Statistical Varieties and the Use of Rectangular Coordinates in Theory of Sampling Distributions. Sankhya, 3: 1 - 34.
35. Mallory-Smith, C. A., Thill, D. C. and Dial, M. J. 1990. Identification of Sulfonylurea Herbicide-Resistant Prickly Lettuce (Lactuca-Serriola). Weed Technology, 4: 163 - 168.
36. Manh, A. G., Rabatel, G., Assemat, L. and Aldon, M. J. 2001. Weed Leaf Image Segmentation by Deformable Templates. Journal of Agricultural Engineering Research, 80: 139 - 146.
37. Marshall, R. and Moss, S. R. 2008. Characterisation and Molecular Basis of ALS Inhibitor Resistance in the Grass Weed Alopecurus Myosuroides. Weed Research, 48: 439 - 447.
38. Mendenhall, J. A., D. E. Lencioni, and J. B. Evans. 2000. "Earth Observing-1 Advanced Land Imager: Radiometric Response Calibration." http://eo1.gsfc.nasa.gov/new/validationReport/Technology/Documents/EO-1-3.pdf (http://eo1.gsfc.nasa.gov/new/validationReport/Technology/Documents/EO-1-3.pdf) (Accessed: 29 January 2012).
39. Monaco, T. J., Weller, S. C. and Ashton, F. M. 2002. Weed Science Principles and Practices, 3 - 126. New York: John Wiley & Sons.
40. Moran, M. S., Inoue, Y. and Barnes, E. M. 1997. Opportunities and Limitations for Image-Based Remote Sensing in Precision Crop Management. Remote Sensing of Environment, 61: 319 - 346.
41. Moran, M. S., Maas, S. J., Vanderbilt, V. C., Barnes, M., Miller, S. N. and Clarke, T. R. 2004. " Application of Image-Based Remote Sensing to Irrigated Agriculture ". In Remote Sensing for Natural Resource Management and Environmental Monitoring, Edited by: Ustin, S. L. 648 - 650. Hoboken, NJ: John Wiley & Sons.
42. Papayiannis, L. C., Kokkinos, C. D. and Alfaro-Fernandez, A. 2012. Detection, Characterization and Host Range Studies of Pepino Mosaic Virus in Cyprus. European Journal of Plant Pathology, 132: 1 - 7.
43. Pikart, T. G., Souza, G. K., Serrao, J. E. and Zanuncio, J. C. 2011. Leafcutter Ants: A Small Dispersal Agent of the Invasive Plant Murraya Paniculata. Weed Research, 51: 548 - 551.
44. Pinter, P., Hatfield, J., Schepers, J., Barnes, E., Moran, M., Daughtry, C. and Upchurch, D. 2003. Remote Sensing for Crop Management. Photogrametric Engineering & Remote Sensing, 69: 647 - 664.
45. Raven, P. H., Everet, R. F. and Eichhorn, S. E. 2005. Biology of Plants, 35 - 88. New-York: W. H. Freeman and Company.
46. Shen, L., Bai, L. and Fairhurst, M. 2007. Gabor Wavelets and General Discriminant Analysis for Face Identification and Verification. Image and Vision Computing, 25: 553 - 563.
47. Slaughter, D. C., Giles, D. K. and Downey, D. 2008. Autonomous Robotic Weed Control Systems: A Review. Computers and Electronics in Agriculture, 61: 63 - 78.
48. Smith, A. M. and Blackshaw, R. E. 2003. Weed-crop Discrimination Using Remote Sensing: A Detached Leaf Experiment. Weed Technology, 17: 811 - 820.
49. Thenkabail, P. S., Enclona, E. A., Ashton, M. S. and Van der Meer, B. 2004. Accuracy Assessments of Hyperspectral Waveband Performance for Vegetation Analysis Applications. Remote Sensing of Environment, 91: 354 - 376.
50. Thorp, K. R. and Tian, L. F. 2004. A Review on Remote Sensing of Weeds in Agriculture. Precision Agriculture, 5: 477 - 508.
51. Timmermann, C., Gerhards, R. and Kuehbauch, W. 2003. The Economic Impact of Site-Specific Weed Control. Precision Agriculture, 4: 249 - 260.
52. Vrindts, E., De Baerdemaeker, J. and Ramon, H. 2002. Weed Detection Using Canopy Reflection. Precision Agriculture, 3: 63 - 80.
53. Wastell, D. G. 1987. A Simple Randomization Procedure for Validating Discriminant Analysis: A Methodological Note. Biological Psychology, 24: 123 - 127.
54. Weis, M., Gutjahr, C., Rueda Ayala, V., Gerhards, R., Ritter, C. and Scholderle, F. 2008. Precision Farming for Weed Management: Techniques. Gesunde Pflanzen, 60: 171 - 181.
55. Zhao, G. and Maclean, A. L. 2000. A Comparison of Canonical Discriminant Analysis and Principal Component Analysis for Spectral Transformation. Photogrammetric Engineering and Remote Sensing, 66: 841 - 847.
56. Zwiggelaar, R. 1998. A Review of Spectral Properties of Plants and their Potential Use for Crop/Weed Discrimination in Row-Crops. Crop Protection, 17: 189 - 206.