Remote sensing for assessing Rhizoctonia crown and root rot severity in sugar beet

Reynolds, G.; Windels, Carol E.; MacRae, Ian V; Laguette, Soizik

doi:10.5274/assbt.2011.113

Cited by 5 publications

(4 citation statements)

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“…The lack of data is often due to difficulty in experimentation, but has additional ethical constraints in the case human and animal diseases. For plant diseases, the development of new monitoring tools such as remote sensing or nuclear magnetic resonance [49], [50] show promise in improving the monitoring of diseases in perennial and non-perennial crop systems, and, therefore, in helping practitioners and epidemiologists to detect pathogen infections and measure incubation periods.…”

Section: Discussionmentioning

confidence: 99%

Estimating the Delay between Host Infection and Disease (Incubation Period) and Assessing Its Significance to the Epidemiology of Plant Diseases

et al. 2014

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Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.

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Section: Discussionmentioning

confidence: 99%

Estimating the Delay between Host Infection and Disease (Incubation Period) and Assessing Its Significance to the Epidemiology of Plant Diseases

et al. 2014

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“…Vegetation indices from spectral measurements were also calculated and analyzed using ANOVA in R. All indices assessed by Reynolds et al [20] were tested in this experiment, but wideband indices were adapted into narrowband indices using 554 nm for green reflectance, 670 nm for red reflectance, and 775 nm for near-infrared reflectance.…”

Section: Statistical Analysesmentioning

confidence: 99%

Quantifying the Impacts of Systemic Acquired Resistance to Pitch Canker on Monterey Pine Growth Rate and Hyperspectral Reflectance

Reynolds

Gordon

McRoberts

2016

Forests

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Pitch canker, caused by Fusarium circinatum, is a disease affecting Monterey pine (Pinus radiata) and many other pine species throughout the world. The impact of pitch canker on Pinus radiata may be limited by systemic acquired resistance (SAR), a phenomenon that elevates resistance to a pathogen after initial challenge by that pathogen or another microorganism. Allocation of resources to defense, as a consequence of SAR, is presumed to reduce resources available to support growth and reproduction, but specific fitness consequences associated with SAR in P. radiata have not been measured. To quantify impacts of SAR on growth rate, a 2ˆ2 factorial experiment was established in which trees were either primed for SAR or unprimed, with half the trees in each of those two groups being inoculated with the pitch canker pathogen and the other half not inoculated. Priming for SAR was accomplished by inoculating one branch with F. circinatum and removing inoculated branches prior to subsequent challenge inoculations (= disease treatments). Disease treatments included three inoculations that were removed for measurement of lesion length, and three additional inoculations that remained on the tree as a representation of persistent disease. Control trees were mock inoculated with water. Main effects of priming and disease did not result in significant effects on growth rate. Based on hyperspectral canopy reflectance data, diseased trees were associated with higher difference vegetation index values and biomass. The absence of a negative impact on growth rate associated with SAR suggests that induction of resistance may have utility as a tool for management of pitch canker in plantations.

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“…It is also difficult to map the spatial extent and severity of the disease spread with the traditional method of field scouting [122]. RS solves many of these problems if used to detect and monitor several diseases in different crops [183], showing itself capable of detecting diseases whose symptoms are well evident in the aerial part of the plant and those affecting the roots [184,185]. The research concerning the detection of olive disease symptoms by RS imagery has mainly focused, to our knowledge, on two diseases (Table 5): Verticillium Wilt (VW) caused by the soil-borne fungus Verticillium Dahliae Kleb.…”

Section: Olive Disease Detection and Pest Managementmentioning

confidence: 99%

The Role of Remote Sensing in Olive Growing Farm Management: A Research Outlook from 2000 to the Present in the Framework of Precision Agriculture Applications

Messina

Modica

2022

Remote Sensing

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Given the importance of olive growing, especially in Mediterranean countries, it is crucial that there is a constant process of modernization aimed at both environmental sustainability and the maintenance of high standards of production. The use of remote sensing (RS) allows intervention in a specific and differentiated way in olive groves, depending on their variability, in managing different agronomic aspects. The potentialities of the application of RS in olive growing are topics of great agronomic interest to olive growers. Using the tools provided by RS and the modernization of the olive sector can bring great future prospects by reducing costs, optimizing agronomic management, and improving production quantity and quality. This article is part of a review that aims to cover the past, from the 2000s onwards, and the most recent applications of aerial RS in olive growing in order to be able to include research and all topics related to the use of RS on olive trees. As far as the use of RS platforms such as satellites, aircraft, and unmanned aerial vehicles (UAVs) as olive growing is concerned, a literature review showed the presence of several works devoted to this topic. This article covers purely agronomic matters of interest to olive farms (and related research that includes the application of RS), such as yielding and managing diseases and pests, and detection and counting of olive trees. In addition to these topics, there are other relevant aspects concerning the characterization of the canopy structure of olive trees which is particularly interesting for mechanized pruning management and phenotyping.

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Remote sensing for assessing Rhizoctonia crown and root rot severity in sugar beet

Cited by 5 publications

References 0 publications

Estimating the Delay between Host Infection and Disease (Incubation Period) and Assessing Its Significance to the Epidemiology of Plant Diseases

Estimating the Delay between Host Infection and Disease (Incubation Period) and Assessing Its Significance to the Epidemiology of Plant Diseases

Quantifying the Impacts of Systemic Acquired Resistance to Pitch Canker on Monterey Pine Growth Rate and Hyperspectral Reflectance

The Role of Remote Sensing in Olive Growing Farm Management: A Research Outlook from 2000 to the Present in the Framework of Precision Agriculture Applications

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