• Abstract
• Full-Text PDF [577 KB]

• Article Statistics
• Google Scholar
• Order Reprints

• Cite this article
• Export to BibTeX
• Export to EndNote

• [+] on DOAJ
• Chávez, P
• Yarlequé, C
• Piro, O
• Posadas, A
• Mares, V
• Loayza, H
• Chuquillanqui, C
• Zorogastúa, P
• Flexas, J
• Quiroz, R
• [+] on Google Scholar
• Chávez, P
• Yarlequé, C
• Piro, O
• Posadas, A
• Mares, V
• Loayza, H
• Chuquillanqui, C
• Zorogastúa, P
• Flexas, J
• Quiroz, R
• [+] on PubMed
• Chávez, P
• Yarlequé, C
• Piro, O
• Posadas, A
• Mares, V
• Loayza, H
• Chuquillanqui, C
• Zorogastúa, P
• Flexas, J
• Quiroz, R

•  CiteULike
•  Facebook
•  Mendeley
•  Twitter

This article is

• freely available
• re-usable

Remote Sens. 2010, 2(5), 1197-1216; doi:10.3390/rs2051197

Article

Applying Multifractal Analysis to Remotely Sensed Data for Assessing PYVV Infection in Potato (Solanum tuberosum L.) Crops

Perla Chávez ^1,3 , Christian Yarlequé ¹ , Oreste Piro ⁴ , Adolfo Posadas ¹ , Víctor Mares ¹ , Hildo Loayza ¹ , Carlos Chuquillanqui ² , Percy Zorogastúa ¹ , Jaume Flexas ³  and Roberto Quiroz ^1,*

¹ Production Systems and the Environment Division, International Potato Center, Av. La Molina 1895, Lima 12, Peru ² Integrated Crop Management Division, International Potato Center, Av. La Molina 1895, Lima 12, Peru ³ Research Group in Biology of Plants under Mediterranean Conditions, University of Balearic Islands, Crtra. Valldemossa km.7.5, 07122 Palma de Mallorca, Spain ⁴ Physics Department, University of Balearic Islands, Crtra, Valldemossa km.7.5, 07122 Palma de Mallorca, Spain

* Author to whom correspondence should be addressed.

Received: 21 December 2009; in revised form: 12 April 2010 / Accepted: 14 April 2010 / Published: 27 April 2010

Download PDF Full-Text [577 KB, Updated Version, uploaded 28 April 2010 08:32 CEST]

The original version is still available [577 KB, uploaded 27 April 2010 11:30 CEST]

Abstract: Multispectral reflectance imagery and spectroradiometry can be used to detect stresses affecting crops. Previously, we have shown that changes in spectral reflectance and vegetation indices detected viral infection 14 days before visual symptoms were noticed by the trained eye. Herein we present evidence that shows that the application of multifractal analysis and wavelet transform to spectroradiometrical data improves the diagnostic power of the remote sensing-based methodology proposed in our previous work. The diagnosis of viral infection was effectively enhanced, providing the earliest detection ever reported, as anomalies were detected 29 and 33 days before appearance of visual symptoms in two experiments.

Keywords: remote sensing; PYVV; multifractal analysis; multispectral reflectance

Article Statistics

Cite This Article