Applications of Geographic Information Systems and Geostatistics in Plant Disease Epidemiology and Management

Nelson, M. R.; Orum, T. V.; Jaime-Garcia, Ramon; Nadeem, Athar

doi:10.1094/pdis.1999.83.4.308

Cited by 94 publications

(46 citation statements)

References 20 publications

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“…Considering the level of stress, the results also explain measured amount of stress (indicated by SRVI values) increased as disease severity increase. Understanding spatial and temporal differences of the disease spreading would be very useful for disease management [40]. The derived PRR disease severity distribution map of Figure 9 illustrates the distribution of trees in severe decline at the eastern and western boundaries, which was subsequently attributed to water logging conditions in lower elevation areas.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

et al. 2018

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Phytophthora root rot (PRR) infects the roots of avocado trees, resulting in reduced uptake of water and nutrients, canopy decline, defoliation, and, eventually, tree mortality. Typically, the severity of PRR disease (proportion of canopy decline) is assessed by visually comparing the canopy health of infected trees to a standardised set of photographs and a corresponding disease rating. Although this visual method provides some indication of the spatial variability of PRR disease across orchards, the accuracy and repeatability of the ranking is influenced by the experience of the assessor, the visibility of tree canopies, and the timing of the assessment. This study evaluates two image analysis methods that may serve as surrogates to the visual assessment of canopy decline in large avocado orchards. A smartphone camera was used to collect red, green, and blue (RGB) colour images of individual trees with varying degrees of canopy decline, with the digital photographs then analysed to derive a canopy porosity percentage using a combination of 'Canny edge detection' and 'Otsu's' methods. Coinciding with the on-ground measure of canopy porosity, the canopy reflectance characteristics of the sampled trees measured by high resolution Worldview-3 (WV-3) satellite imagery was also correlated against the observed disease severity rankings. Canopy porosity values (ranging from 20-70%) derived from RGB images were found to be significantly different for most disease rankings (p < 0.05) and correlated well (R 2 = 0.89) with the differentiation of three disease severity levels identified to be optimal. From the WV-3 imagery, a multivariate stepwise regression of 18 structural and pigment-based vegetation indices found the simplified ratio vegetation index (SRVI) to be strongly correlated (R 2 = 0.96) with the disease rankings of PRR disease severity, with the differentiation of four levels of severity found to be optimal.

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Section: Discussionmentioning

confidence: 99%

Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

et al. 2018

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“…Analyzing the spatial pattern of plant diseases may be pivotal to elucidate the ecology, the 48 epidemiology and the infection biology of pathogens as well as the mechanisms underlying host-49 pathogen interactions and the spread of epidemics (Nelson et al 1999). A large body of literature 50 deals with the application of Geographic Information Systems (GIS) in conjunction with statistical 51 and geostatistical methods to investigate peculiar traits of plants diseases, to test biologically 52 relevant hypotheses and to build predictive and/or explicative models (Nelson et al 1999).…”

Section: Introduction 46 47mentioning

confidence: 99%

“…A large body of literature 50 deals with the application of Geographic Information Systems (GIS) in conjunction with statistical 51 and geostatistical methods to investigate peculiar traits of plants diseases, to test biologically 52 relevant hypotheses and to build predictive and/or explicative models (Nelson et al 1999). 53…”

Section: Introduction 46 47mentioning

confidence: 99%

A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases

Lione

Gonthier

2016

Phytopathology®

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The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error < 0.05). A biological validation on the spatial distribution of spores of two fungal pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.

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“…Because GIS and GPS technologies are more adaptable and easier to use than RS (Nelson, Orum & Jaime-Garcia, 1999), they have been chosen as the alternative approach for this study. Also, season and year to year, the crop in a parcel may change, but changes in a parcel boundary are rare.…”

Section: Geographical Information Systems and Toolsmentioning

confidence: 99%

Using geospatial technology to strengthen data systems in developing countries: The case of agricultural statistics in India

Naik¹,

Basavaraj²,

Hegde³

et al. 2013

Applied Geography

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ABSTRACT. Despite significant progress in the development of quantitative geography techniques and methods and a general recognition of the need to improve the quality of geographic data, few studies have exploited the potential of geospatial tools to augment the quality of available data methods in developing countries. This paper uses data from an extensive deployment of geospatial technology in India to compare crop areas estimated using geospatial technology to crop areas estimated by conventional methods and assess the differences between the methods. The results presented here show that crop area estimates based on geospatial technology generally exceed the estimates obtained using conventional methods. This suggests that conventional methods are unable to respond quickly to changes in cropping patterns and therefore do not accurately record the area under high-value cash crops. This finding has wider implications for commercializing agriculture and the delivery of farm credit and insurance services in developing countries. Significant data errors found in the conventional methods could affect critical policy interventions such as planning for food security. Some research and policy implications are discussed.

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Applications of Geographic Information Systems and Geostatistics in Plant Disease Epidemiology and Management

Cited by 94 publications

References 20 publications

Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases

Using geospatial technology to strengthen data systems in developing countries: The case of agricultural statistics in India

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