Spectral signature of brown rust and orange rust in sugarcane





remote sensing, sugar cane, pests, vegetation, agriculture


Precision agriculture, making use of the spatial and temporal variability of cultivable land, allows farmers to refine fertilization, control field irrigation, estimate planting productivity, and detect pests and disease in crops. To that end, this paper identifies the spectral reflectance signature of brown rust (Puccinia melanocephala) and orange rust (Puccinia kuehnii), which contaminate sugar cane leaves (Saccharum spp.). By means of spectrometry, the mean values and standard deviations of the spectral reflectance signature are obtained for five levels of contamination of the leaves in each type of rust, observing the greatest differences between healthy and diseased leaves in the red (R) and near infrared (NIR) bands. With the results obtained, a multispectral camera was used to obtain images of the leaves and calculate the Normalized Difference Vegetation Index (NDVI). The results identified the presence of both plagues by differentiating healthy from contaminated leaves through the index value with an average difference of 11.9% for brown rust and 9.9% for orange rust.

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Author Biographies

Jorge Luís Soca-Muñoz, University of Cienfuegos Carlos Rafael Rodríguez

Center for Thermoenergetic Studies.

Eniel Rodríguez-Machado, University "Marta Abreu" of Las Villas

Automation, Robotics and Perception Group (GARP).

Osmany Aday-Díaz, Sugarcane Research Institute (INICA)

Territorial Research Station for Sugar Cane (ETICA - Villa Clara Center).

Luis Hernández-Santana, University "Marta Abreu" of Las Villas

Automation, Robotics and Perception Group (GARP).

Rubén Orozco-Morales, University "Marta Abreu" of Las Villas

Automation, Robotics and Perception Group (GARP).


R. Park and C. Wellings, “Somatic hybridization in the uredinales,” Annual Review of Phytopathology , vol. 50, september 2012. [Online]. Available: https://doi.org/10.1146/annurev-phyto-072910-095405

M. Saba and A. Khalid, “Species diversity of genus Puccinia (Basidiomycota, Uredinales) parasitizing poaceous hosts in Pakistan,” International Journal of Agriculture and Biology , vol. 15, no. 3, pp. 580–584, Jan. 2013.

J. Hoy and C. Hollier, “Effect of brown rust on yield of sugarcane in Louisiana,” Plant Disease , vol. 93, no. 11, November 2009. [Online]. Available: https://doi.org/10.1094/PDIS-93-11-1171

K. Muhammad, S. Afghan, Y. Ban, and J. Iqbal, “Genetic variability among the brown rust resistant and susceptible genotypes of sugarcane by rapd technique,” Pakistan Journal of Botany , vol. 45, no. 1, pp. 163–168, Feb. 2013.

R. Peixoto and et al , “Development and characterization of microsatellite markers for Puccinia melanocephala , causal agent of sugarcane brown rust,” Proc. Int. Soc. Sugar Cane Technol. , vol. 28, pp. 244–247, 2013.

R. Peixoto and et al , “Genetic diversity among Puccinia melanocephala isolate from Brazil assessed using simple sequence repeat markers,” Genetics and molecular research: GMR , vol. 13, no. 3, september 26 2014. [Online]. Available: https://doi.org/10.4238/2014.September.26.23

J. Comstock and et al , “Presence of BRU1 brown rust resistance in the CP sugarcane development programs,” presented at XI Pathology and IX Entomology Workshops Program, Guayaquil, Ec., 2015.

L. Pérez and et al , “Definitive identification of orange rust of sugarcane caused by Puccinia kuehnii in Cuba,” Plant Pathology , vol. 59, no. 4, june 2010. [Online]. Available: https://doi.org/10.1111/j.1365-3059.2009.02248.x

M. Cadavid, J. Ángel, , and J. Victoria, “First report of orange rust ofsugarcane caused by Puccinia kuehnii in Colombia,” Plant Disease , vol. 96, no. 1, january 2012. [Online]. Available: https://doi.org/10.1094/PDIS-05-11-0406

G.Briggsand et al , “Firstreportoforangerustsiseaseofsugarcane in the Dominican Republic,” Plant Disease , vol. 98, no. 7, july 2014. [Online]. Available: https://doi.org/10.1094/PDIS-01-14-0044-PDN

J. Comstock and et al , “La roya naranja de la caña de azúcar, una enfermedad emergente: su impacto y comparación con la roya marrón,” Ciencia y Tecnología de los Cultivos industriales , vol. 5, no. 7, pp. 12–21, 2015.

C. Funes and et al , “First report of orange rust of sugarcane caused by Puccinia kuehnii in Argentina,” Plant Disease , vol. 100, no. 4, november 2015. [Online]. Available: https://doi.org/10.1094/PDIS-09-15-1099-PDN

D. Zhao, N. Glynn, B. Glaz, J. Comstockn, and S. Sood, “Orange rust effects on leaf photosynthesis and related characters of sugarcane,” Plant Disease , vol. 95, no. 6, june 2011. [Online]. Available: https://doi.org/10.1094/PDIS-10-10-0762

R. Raid and S. Sullivan, “Common rust,” in A guide to sugarcane diseases , P. Rott and et al , Eds. CIRAD and ISSCT, 2000, pp. 85–89.

B. Croft, R. Magarey, and P. Whittle, “Disease management,” in Manual of Canegrowing , M. Hogarth and P. Allsopp, Eds. Bureau of Sugar Experiment Stations, 2000, pp. 263––289.

CENICAÑA. (2014, feb. 19) Enfermedades de la caña de azúcar en Colombia. [Online]. Available: https://www.cenicana.org/enfermedades-de-la-cana-de-azucar-en-colombia/

O.Aday and et al ,“Caracterización de los síntomas de la roya naranja ( Puccinia kuehnii (W. Krüger) E. J. Butler) en cuatro cultivares de caña de azúcar en Cuba,” Centro Agrícola , vol. 49, no. 2, pp. 61–67, Apr. 2017.

A. Koschan and M.Abidi, Digital Color Image Processing . New Yersey, EE.UU.: John Wiley & Sons, 2007.

M. Peres, Focal Encyclopedia of Photography: Digital Imaging, Theory and Applications, History, and Science , 4th ed. Elsevier Focal Press, 2007.

G. saw and H. Bruke,“Spectral imaging fo rremote sensing,” Lincoln Laboratory Journal , vol. 14, no. 1, pp. 3–28, 2003.

Y. Fan and et al , “Fast detection of striped stem-borer (chilo suppressalis walker) infested rice seedling based on visible/near-infrared hyperspectral imaging system,” Sensors (Basel) , vol. 17, no. 11, october 27 2017. [Online]. Available: http://doi.org/10.3390/s17112470

J. Müllerová and et al , “Timing is important: Unmanned aircraft vs. satellite imagery in plant invasion monitoring,” Front Plant Sci , vol. 8, may 31 2017. [Online]. Available: http://doi.org/10.3389/fpls.2017.00887

S. Thomas and et al , “Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective,” Journal of Plant Diseases and Protection -New Series- , vol. 125, no. 3, september 2017. [Online]. Available: http://doi.org/10.1007/s41348-017-0124-6

S. Aggarwal, “Principle of remote sensing,” in Satellite Remote Sensing and GIS Applications in Agricultural Meteorology, , Dehra Dun, India, 2005, pp. 23–38.

R. Kokaly, D. Despain, R. Clark, and K. Livo, “Spectral analysis of absorption features for mapping vegetation cover and microbial communities in yellowstone national park using aviris data,” in Integrated Geoscience Studies in the Greater Yellowstone Area—Volcanic, Tectonic, and Hydrothermal Processes in the Yellowstone Geoecosystem , L. Morgan, Ed. U.S. Geological Survey Professional Paper 1717, 2007, pp. 463–489.

S. Sankaran and et al , “Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review,” European Journal of Agronomy , vol. 70, october 2015. [Online]. Available: https://doi.org/10.1016/j.eja.2015.07.004

J. Gago and et al , “Uavs challenge to assess water stress for sustainable agriculture,” Agricultural Water Management , vol. 153, may 1 2015. [Online]. Available: https://doi.org/10.1016/j.agwat.2015.01.020

J. Zhou and et al , “Aerial multispectral imaging for crop hail damage assessment in potato,” Computers and Electronics in Agriculture , vol. 127, september 2016. [Online]. Available: https://doi.org/10.1016/j.compag.2016.06.019

J. Díaz, “Estudio de Índices de vegetación a partir de imágenes aéreas tomadas desde UAS/RPAS y aplicaciones de estos a la agricultura de precisión,” M.S. thesis, Universidad Complutense de Madrid, Madrid, España, 2015.

R. Sanderson, “Introduction to remote sensing,” presented at Anais do XVI Simpósio Brasileiro de Sensoriamento Remoto, Brasil, 2013.

E. Abdel, F. Ahmed, M. Berg, and M. Way, “Potential of spectroscopic data sets for sugarcane thrips (Fulmekiola serrata Kobus) damage detection,” International Journal of Remote Sensing , vol. 31, no. 15, september 2010. [Online]. Available: https://doi.org/10.1080/01431160903241981

E.AkemiandN.NobuhiroandA.Garcia,“Análisedocomportamento espectraldeamostrasdecana-de-açúcarinfectadascomferrugem alaranjada,” in Anais XVI Simpósio Brasileiro de Sensoriamento Remoto - SBSR , Foz do Iguaçu, Brazil, 2013, pp. 0258–0265.

A. Apan, A. Held, S. Phinn, and J. Markley, “Detecting sugarcane ‘Orange Rust’ disease using EO-1 hyperion hyperspectral imagery,” International Journal of Remote Sensing , vol. 25, no. 2, 2004. [Online]. Available: https://doi.org/10.1080/01431160310001618031

R.IslamandM.Rafiqul,“Animageprocessingtechniquetocalculate percentage of disease affected pixels of paddy leaf,” International Journal of Computer Applications , vol. 123, no. 12, august 2015. [Online]. Available: https://doi.org/10.5120/ijca2015905495

E. Virtudazo, H. Nojima, and M. Kakishima, “Taxonomy of Puccinia species causing rust diseases on sugarcane,” Mycoscience , vol. 42, no. 2, april 2001. [Online]. Available: https://doi.org/10.1007/BF02464133

C. Li, K. Sivasithamparam, and M. Barbetti, “Complete resistance to leaf and staghead disease in Australian Brassica junce a germplasm exposed to infection by Albugo candida (white rust),” Australasian Plant Pathology , vol. 38, no. 1, january 2009. [Online]. Available: https://doi.org/10.1071/AP08078

K. Neumenn, “Digital aereal cameras,” unpublished.

A. Kavvadias, E. Psomiadis, M. Chanioti, E. Gala, and S. Michas, “Precision agriculture – comparison and evaluation of innovative very high resolution (UAV) and landsat data,” presented at International Conference on Information and Communication Technologies in Agriculture Food and Environment-HAICTA, Kavala, GR, 2015.

J.Beltran,“Methoddevelopmenttoprocesshyper-temporalremote sensing (rs) images for change mapping,” M.S. thesis, International Institute for Geo-information Science and Earth Observation- ITC, Enschede, Netherlands, 2007.

M.Rahman,A.Islam,andM.Rahman,“NDVIderivedsugarcanearea identification and crop condition assessment,” Plan Plus , vol. 1, pp. 1–12, Jan. 2004.

N. Virlet, E. Costes, S. Martinez, J. Kelner, and J. Regnard, “Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit,” Journal of Experimental Botany , vol. 66, no. 18, september 2015. [Online]. Available: https://doi.org/10.1093/jxb/erv355

D. Zhao, V. Gordona, J. Comstocka, N. Glynnb, and R. Johnsonc, “Assessment of sugarcane yield potential across large numbers of genotypes using canopy reflectance measurements,” Crop Science , vol. 56, no. 4, july 2016. [Online]. Available: https://doi.org/10.2135/cropsci2015.12.0747

K. Johansen and et al , “Using GeoEye-1 imagery for multi-temporal object-based detection of canegrub damage in sugarcane fields in Queensland, Australia,” GIScience & Remote Sensing , vol. 55, no. 2, 2018. [Online]. Available: https://doi.org/10.1080/15481603.2017.1417691

L. Kunze and et al , “Classification analysis of NDVI time series in metric spaces for sugarcane identification,” presented at 20th International Conference on Enterprise Information Systems, Funchal-Madeira, PT, 2018.

I. Pinheiro and et al , “Prediction of sugarcane yield based on NDVI and concentration of leaf-tissue nutrients in fields managed with straw remova,” Agronomy , vol. 8, no. 9, september 2018. [Online]. Available: https://doi.org/10.3390/agronomy8090196

Q. Zheng and et al , “New spectral index for detecting wheat yellow rust using Sentinel-2 multispectral imagery,” Sensors , vol. 18, no. 3, march 15 2018. [Online]. Available: https://doi.org/10.3390/s18030868




How to Cite

Soca-Muñoz, J. L., Rodríguez-Machado, E., Aday-Díaz, O., Hernández-Santana, L., & Orozco-Morales, R. . (2020). Spectral signature of brown rust and orange rust in sugarcane. Revista Facultad De Ingeniería Universidad De Antioquia, (96), 9–20. https://doi.org/10.17533/udea.redin.20191042

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