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Canopy Hyperspectral Reflectance of Redroot Pigweed versus Okra and Super Okra Leaf Cotton

DOI: 10.4236/as.2019.1011107, PP. 1465-1476

Keywords: Amaranthus retroflexus, Gossypium hirsutum, Visible, Red Edge, Shortwave Infrared

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Abstract:

Redroot pigweed (Amaranthus retroflexus L.) is a nuisance weed that affects cotton (Gossypium hirsutum L.) growth and yield worldwide. Being able to distinguish redroot pigweed from cotton would help producers and crop consultants better implement strategies used to suppress and control it. Hyperspectral reflectance properties of weed and crop canopies have been used to differentiate between them. Currently, no information is available on the application of hyperspectral data to distinguish redroot pigweed from cotton with different leaf shapes. Positive results will further support the exploration of remote sensing technology for distinguishing redroot pigweed from cotton. The objectives were to compare canopy hyperspectral reflectance of redroot pigweed to canopy hyperspectral reflectance of okra and super okra leaf cotton and to identify regions of the spectrum in which differences exist in their reflectance properties. Hyperspectral reflectance measurements of redroot pigweed and cotton were obtained with a spectroradimeter on May 6 and June 27, 2019. Plants grown in a greenhouse were used for this study. One-hundred and sixty-two 10-nm bands (400 - 2350 nm spectral range) were evaluated with analysis of variance (p ≤ 0.05) and Dunnett’s test (p ≤ 0.05) to determine the wavebands that were useful for separating redroot pigweed from okra leaf and super okra leaf cotton. The following bands were consistent in distinguishing redroot pigweed and okra leaf cotton on both dates: 420 nm, 510 - 650 nm, 690 - 740 nm, and 2000 - 2010 nm; whereas, 400 - 500 nm, 1480 - 1780 nm, and 1990 - 2350 nm were identified for both dates for separating redroot pigweed from super okra leaf cotton. Commercial imaging systems used on ground-based or airborne platforms can be easily tuned into the spectral bands listed in this study, thus providing managers with a tool to use for identifying redroot pigweed in cotton production systems.

References

[1]  Cotton Counts (2019) The Story of Cotton.
https://www.cotton.org/pubs/cottoncounts/story/upload/The-Story-of-Cotton-Hi-Res-642k-PDF.pdf
[2]  Horak, M.J. and Loughin, T.M. (2000) Growth Analysis of Four Amaranthus Species. Weed Science, 48, 347-355.
https://doi.org/10.1614/0043-1745(2000)048[0347:GAOFAS]2.0.CO;2
[3]  Aguyoh, J.N. and Masiunas, J.B. (2003) Interference of Redroot Pigweed (Amaranthus retroflexus) with snap beans. Weed Science, 51, 202-207.
https://doi.org/10.1614/0043-1745(2003)051[0202:IORPAR]2.0.CO;2
[4]  Amini, R., Alizadeh, H. and Yousefi, A. (2014) Interference between Red Kidney Bean (Phaseolus vulgaris L.) Cultivars and Redroot Pigweed (Amaranthus retroflexus L.). European Journal of Agronomy, 60, 13-21.
https://doi.org/10.1016/j.eja.2014.07.002
[5]  Mirshekari, B., Javanshir, A. and Arbat, H.K. (2010) Interference of Redroot Pigweed (Amaranthus retroflexus) in Green Bean (Phaseolus vulgaris). Weed Biology and Management, 10, 120-125.
https://doi.org/10.1111/j.1445-6664.2010.00371.x
[6]  Bensch, C.N., Horak, M.J. and Peterson, D. (2003) Interference of Redroot Pigweed (Amaranthus retroflexus), Palmer Amaranth (A. palmeri), and Common Waterhemp (A. rudis) in soybean. Weed Science, 51, 37-43.
https://doi.org/10.1614/0043-1745(2003)051[0037:IORPAR]2.0.CO;2
[7]  Knezevic, S.Z., Weise, S.E. and Swanton, C.J. (1994) Interference of Redroot Pigweed (Amaranthus retroflexus) in Corn (Zea mays). Weed Science, 42, 568-573.
https://doi.org/10.1017/S0043174500076967
[8]  Sheibany, K., Meybodi, M.A.B. and Atri, A. (2009) Competitive Effects of Redroot Pigweed (Amaranthus retroflexus) on the Growth Indices and Yield of Corn. Weed Biology and Management, 9, 152-159.
https://doi.org/10.1111/j.1445-6664.2009.00333.x
[9]  Ghanizadeh, H., Lorzadeh, S. and Aryannia, N. (2014) Effect of Weed Interference on Zea mays: Growth Analysis. Weed Biology and Management, 14, 133-137.
https://doi.org/10.1111/wbm.12041
[10]  Buchanan, G.A. and Burns, E.R. (1971) Weed Competition in Cotton. Ⅱ. Cocklebur and Redroot Pigweed. Weed Science, 19, 580-582.
https://doi.org/10.1017/S0043174500050736
[11]  Buchanan, G.A., Crowley, R.H., Street, J.E. and McGuire, J.A. (1980) Competition of Sicklepod (Cassia obtusifolia) and Redroot Pigweed (Amaranthus retroflexus) with Cotton (Gossypium hirsutum). Weed Science, 28, 258-262.
https://doi.org/10.1017/S0043174500055259
[12]  Ma, X., Wu, H., Jiang, W., Ma, Y. and Ma, Y. (2015) Interference between Redroot Pigweed (Amaranthus retroflexus L.) and Cotton (Gossypium hirsutum L.): Growth Analysis. PLoS ONE, 10, e0130475.
https://doi.org/10.1371/journal.pone.0130475
[13]  Knezevic, S.Z. and Horak, M.J. (1998) Influence of Emergence Time and Density on Redroot Pigweed (Amaranthus retrofexus). Weed Science, 46, 665-672.
https://doi.org/10.1017/S0043174500089694
[14]  Karimmojeni, H., Bazrafshan, A.H., Majidi, M.M., Torabian, S. and Rashidi, B. (2014) Effect of Maternal Nitrogen and Drought Stress on Seed Dormancy and Germinability of Amaranthus retroflexus. Plant Species Biology, 29, e1-e8.
https://doi.org/10.1111/1442-1984.12022
[15]  Burnside, O.C., Wilson, R.G., Weisberg, S. and Hubbard, K. (1996) Seed Longevity of 41 Weed Species Buried 17 Years in Eastern and Western Nebraska. Weed Science, 44, 74-86.
https://doi.org/10.1017/S0043174500093589
[16]  Telewski, F.W. and Zeevaart, J.A.D. (2002) The 12-Years Period for Dr. Beal’s Seed Viability Experiment. American Journal of Botany, 89, 264-270.
https://doi.org/10.3732/ajb.89.8.1285
[17]  Jalali, M., Motlagh, B.P. and Salari, K. (2012) Allelopathic Effects of Aqueous Extract of Shoot and Root of Licorice (Glycyrrhiza glabra L.) and Pigweed (Amaranthus retroflexus L.) on Germination Characteristic and Seedling Growth of Corn and Chickpea. International Journal of Agricultural Research and Reviews, 2, 357-363.
[18]  Knezevic, S.Z., Horak, M.J. and Vanderlip, R.L. (1997) Relative Time of Redroot Pigweed (Amaranthus retroflexus L.) Emergence Is Critical in Pigweed Sorghum [Sorghum bicolor (L.) Moench] Competition. Weed Science, 45, 502-508.
https://doi.org/10.1017/S0043174500088731
[19]  Rezaie, F. and Yarnia, M. (2009) Allelopathic Effects of Chenopodium album, Amaranthus retroflexus and Cynodon dactylon on Germination and Growth of Safflower. Journal of Food, Agriculture, and Environment, 7, 516-521.
[20]  Heap, I. (2019) International Survey of Herbicide Resistant Weeds.
http://www.weedscience.org
[21]  Chandler, J.M. (1977) Competition of Spurred Anoda, Velvetleaf, Prickly Sida, and Venice Mallow in Cotton. Weed Science, 25, 151-158.
https://doi.org/10.1017/S0043174500033154
[22]  Kaur, R., Mahey, R.K. and Mukherjee, J. (2010) Optimum Time Span for Distinguishing Little Canary Grass (Phalaris minor) from Wheat (Triticum aestivum) Crop Based on Their Spectral Reflectance Characteristics. Indian Journal of Agricultural Sciences, 80, 615-619.
[23]  Kaur, R. and Jaidka, M. (2014) Spectral Reflectance Characteristics to Distinguish Malva neglecta in Wheat (Triticum aestivum). Indian Journal of Agricultural Sciences, 84, 1243-1249.
[24]  Kaur, R., Jaidka, M. and Kingra, P.K. (2013) Study of Optimum Time Span for Distinguishing Rumex spinosus in Wheat Crop through Spectral Reflectance Characteristics. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 84, 625-633.
https://doi.org/10.1007/s40011-013-0255-x
[25]  Buttar, G.S. Kaur, T., Kaur, R. and Kalra, V.P. (2017) Effect of Different Densities of Rumex spinosus on Growth and Yield of Wheat (Triticum aestivum) and Spectral Characteristics of Rumex spinosus. Indian Journal of Agronomy, 62, 185-190.
[26]  Gómez-Casero, M.T., Castillejo-González, I.L., García-Ferrer, A., Peña-Barragán, J.M., Jurado-Expósito, M., García-Torres, L. and López-Granados, F. (2010) Spectral Discrimination of Wild Oat and Canary Grass in Wheat Fields for Less Herbicide Application. Agronomy for Sustainable Development, 30, 689-699.
https://doi.org/10.1051/agro/2009052
[27]  Fletcher, R.S. (2015) Testing Leaf Multispectral Reflectance Data as Input into Random Forest to Differentiate Velvetleaf from Soybean. American Journal of Plant Sciences, 6, 3193-3204.
https://doi.org/10.4236/ajps.2015.619311
[28]  Fletcher, R.S. and Turley, R.B. (2017) Employing Canopy Hyperspectral Narrowband Data and Random Forest Algorithm to Differentiate Palmer Amaranth from Colored Cotton. American Journal of Plant Sciences, 8, 3258-3271.
https://doi.org/10.4236/ajps.2017.812219
[29]  Deng, W., Huang, Y., Zhao, C., Chen, L. and Wang, X. (2015) Bayesian Discriminant Analysis of Plant Leaf Hyperspectral Reflectance for Identification of Weeds from Cabbages. African Journal of Agricultural Research, 1, 551-562.
https://doi.org/10.5897/AJAR2015.10395
[30]  Fletcher, R.S. and Turley, R.B. (2018) Comparing Canopy Hyperspectral Reflectance Properties of Palmer amaranth to Okra and Super-Okra Leaf Cotton. American Journal of Plant Sciences, 9, 2708-2718.
https://doi.org/10.4236/ajps.2018.913197
[31]  McCoy, R.M. (2005) Field Methods in Remote Sensing. The Guilford Press, New York.
[32]  Prasad, K.A., Gnanappazham, L., Selvam, V., Ramasubramanian, R. and Kar, C.S. (2015) Developing a Spectral Library of Mangrove Species of Indian East Coast using Field Spectroscopy. Geocarto International, 30, 580-599.
https://doi.org/10.1080/10106049.2014.985743
[33]  Savitzky, A. and Golay, M.J.E. (1964) Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry, 36, 1627-1639.
https://doi.org/10.1021/ac60214a047
[34]  R Core Team (2019) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
https://www.R-project.org/
[35]  Lehnert, L.W., Meyer, H, Obermeier, W.A., Silva, B., Regeling, B., Thies, B. and Bendix, J. (2019) Hyperspectral Data Analysis in R: The Hsdar Package. Journal of Statistical Software, 89, 1-23.
https://doi.org/10.18637/jss.v089.i12
[36]  Steele, R.G.D. and Torrie, J.H. (1960) Principles and Procedures of Statistics. McGraw-Hill, New York.
[37]  Clewer, A.G. and Scarisbrick, D.H. (2001) Practical Statistics and Experimental Design for Plant and Crop Science. John Wiley and Sons, New York.
[38]  McHugh, M.L. (2011) Multiple Comparison Analysis Testing in ANOVA. Biochemia Medica, 21, 203-209.
[39]  de Mendiburu, F. (2019) Agricolae: Statistical Procedures for Agricultural Research. R Package version 1.3-1.
https://CRAN.R-project.org/package=agricolae
[40]  Campbell, J.B. (2002) Introduction to Remote Sensing. Third Edition, The Guilford Press, New York.
[41]  Jones, H.G. and Vaughan, R.A. (2010) Remote Sensing of Vegetation. Oxford University Press, New York.
[42]  Horler, D.N.H., Dockray, M. and Barber, J. (1983) The Red Edge of Plant Leaf Reflectance. International Journal of Remote Sensing, 4, 273-288.
https://doi.org/10.1080/01431168308948546
[43]  Thenkabail, P.S., Glumma, M.K., Teluguntla, P. and Mohammed, I.A. (2014) Hyperspectral Remote Sensing of Vegetation and Agricultural Crops. Photogrammetric Engineering and Remote Sensing, 80, 697-709.

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