Assessing Potato Yellow Vein Virus (PYVV) infection using remotely sensed data

International Journal of Pest Management

Volumn 55, Issue 3, 2009, Pages 251-256

  Chavez P ^a   Zorogastua P ^a   Chuquillanqui, C ^a   Salazar, L F ^b   Mares, V ^a   Quiroz, R ^a  

^a INTERNATIONAL POTATO CENTER   (Peru)

^b Agdia Inc   (United States)

Author keywords

Early diagnosis; Light reflectance; Potato; PYVV; Remote sensing; Virus

Indexed keywords

ASSESSMENT METHOD; CROP DAMAGE; CROP PRODUCTION; DETECTION METHOD; DISEASE SEVERITY; FIELD SURVEY; INFECTIOUS DISEASE; MONITORING SYSTEM; MULTISPECTRAL IMAGE; NDVI; POTATO; REMOTE SENSING; SATELLITE DATA; SPECTRAL REFLECTANCE; VIRAL DISEASE;

SOUTH AMERICA;

POTATO YELLOW VEIN VIRUS; SOLANUM TUBEROSUM;

EID: 74849093519     PISSN: 09670874     EISSN: 13665863     Source Type: Journal    
DOI: 10.1080/09670870902862685     Document Type: Article

References (32)

1. Agrios GN. 1997. Plant pathology, 4th ed. New York Academic Press. 633 p.
2. Alba V. 1952. El 'amarillamiento de venas' de papa, una enfermedad causada por virus. Tesis Ing. Agrónomo. Universidad Nacional de Colombia, Medelli{dotless}n.
3. Baker NR, Horton P. 1987. Chlorophyll fluorescence quenching during photo inhibition. In: Kyle DJ, Osmond CB, Arntzen CJ, editors. Photo inhibition. Amsterdam, Netherlands: Elsevier. p. 85-94.
4. Bravo C, Moshou D, Oberti R, West J, McCartney A, Bodria L, Ramon H. 2004. Foliar disease detection in the field using optical sensor fusion. Agricultural Engineering International: The CIGR Journal of Scientific Research and Development. Manuscript FP 04 008. Vol. VI. December 2004.
5. Brown RB, Steckler J-PGA, Anderson GW. 1994. Remote sensing for identification of weeds in no-till corn. Trans Am Soc Agri Eng. 37(1):297-302.
6. Choudhury BJ. 1988. Microwave vegetation index: a new long-term global data set for biospheric studies. Int J Remote Sens. 9(2):185-186.
7. Clover GRG, Azam-Ali SN, Jaggard KW, Smith HG. 1999. The effects of beet yellows virus on the growth and physiology of sugar beet (Beta vulgaris). Plant Pathol. 48(1):129-138.
8. Crippen RE. 1990. Calculating the vegetation index faster. Remote Sens Environ. 34(1):71-73.
9. Davies AMC. 2007. Back to basics: spectral pre-treatments - derivatives. Spectroscopy Europe (Tony Davies Column). 19(2):32-33.
10. Díaz MC, Pulgarín JM, Saldarriaga A. 1990. Relaciones insecto-patógeno en el problema del amarillamiento de las venas de la papa. Revista Colombiana de Entomología. 16(2):3-14.
11. Fitzgerald GJ. 2002. Detecting spider mite damage in cotton through spectral mixture analysis of aviris imagery. Proceedings of the 11th JPL Airborne Earth Science Workshop; 2002 March 5-8; Pasadena (CA). p. 75-81.
12. Gamon JA, Peñuelas J, Field CB. 1992. A narrow waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sens Environ. 41(1):35-44.
13. Garbulsky MF, Peñuelas J, Ourcival JM, Filella I. 2008. Estimación de la eficiencia del uso de la radiación en bosques mediterráneos a partir de datos MODIS. Uso del Índice de Reflectancia Fotoquímica (PRI). Ecosistemas 17(3). http://www.revistaecosistemas.net/articulo.asp?Id = 567
14. Gilabert MA, González-Piqueras J, García-Haro J. 1997. Acerca de los índices de vegetación. Revista de Teledetección. 8:1-10.
15. Hope A, Coulter L, Stow D, Peterson S, Service D. 1999. Root rot detection in sugar beet using digital multispectral video. Available from: www.gisdevelopment.net/ aars/acrs/1999/ts1/ts1065pf.htm
16. Huete A, Warrick AW. 1990. Assessment of vegetation and soil water regimes in partial canopies with optical remotely sensed data. Remote Sens Environ. 32(2,3):155-167.
17. Major DJ, Baret F, Guyot G. 1990. A ratio vegetation index adjusted for soil brightness. Int J Remote Sens. 11(5):727-740.
18. Martelli GP, Agranovsky AA, Bar-Joseph M, Boscia D, Candresse T, Coutts RHA, Dolja VV, Falk BW, Gonsalves D, Jelkmann W, et al. 2002. The family Closteroviridae revised. Arch Virol. 147(10):2039-2044.
19. Peñuelas J, Filella I, Lloret P, Muñoz F, Vilajeliu M. 1995. Reflectance assessment of mites effects on apple trees. Int J Remote Sens. 16(14):2727-2733.
20. Pérez OA, Estrada NR. 1987. Comportamiento de varios clones de papa al Amarillamiento de Venas. XIII Reunión ALAP. Panamá. Marzo. p. 9-13.
21. Prince SD. 1991. A model of regional primary production for use with coarse resolution satellite data. Int J Remote Sens. 12(6):1313-1330.
22. Ritchie GL. 2003. Use of ground-based canopy reflectance to determine radiation capture, nitrogen and water status, and final yield in wheat. Thesis for Magister in Science academic degree, Utah State University, USA.
23. Salazar L. 1998. La enfermedad del amarillamiento de las venas de la papa: Evidencia de la presencia de un virus inusual. Agroenfoque. Perú. 12(85):24-26.
24. Salazar LF, Muller G, Querci M, Zapata JL, Owens RA. 2000. Potato yellow vein virus: Its host range, distribution in South America and identification as a crinivirus transmitted by Trialeurodes vaporariorum. Ann Appl Biol. 137(1):7-19.
25. Saldarriaga A, Alvarez A, Jaramillo J. 1988. Efecto del amarillamiento de venas transmitido por Trialeurodes vaporariorum (Westwood) en papa. Revista Colombiana de Entomología. 14(2):3-8.
26. SENASA (Servicio Nacional de Seguridad Agraria). 2008. Virus del amarillamiento de las venas (PYVV). Available from: http://www.senasa.gob.pe/servicios/sanidad_vegetal/ programas_fitosanitarios/cip_papa/virus_amarillento_venas.htm
27. Smith KM. 1972. A textbook for plant virus diseases. 3rd ed. New York: Academic Press. p. 897.
28. Spikes JD, Stout M. 1955. Photochemical activity of chloroplasts isolated from sugar beets infected with virus yellows. Science. 122(3165):375-376.
29. Summy KR, Everitt JH, Escobar DE, Alaniz MA, Davis MR. 1997. Use of airborne digital video imagery to monitor damage caused by two honeydew-excreting insects on cotton. Proceedings of the 16th Biennial Workshop on Color Photography and Videography in Resource Assessment, 29 April-1 May. p. 238-244.
30. Tamayo P, Navarro R. 1984. Aumenta la incidencia del virus de amarillamiento de venas de la papa en Antioquia. ASCOLFI Informa (Bogotá). 10:40-42.
31. Ustin SL, Roberts DA, Gamon JA, Asner GP, Green RO. 2004. Using imaging spectroscopy to study ecosystem processes and properties. BioScience. 54(6):523-534.
32. Wolfinger RD, Chang M. 1995. Comparing the SAS GLM and MIXED Procedures for Repeated Measures. SUGI Proceedings. Cary (NC): SAS Institute Inc. Available from: http://www.ats.ucla.edu/STAT/SAS/library/mixedglm.pdf