The Experts below are selected from a list of 158142 Experts worldwide ranked by ideXlab platform
Tim R Gottwald - One of the best experts on this subject based on the ideXlab platform.
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Plant Disease severity estimated visually by digital photography and image analysis and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to v...
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Plant Disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to visual rating, and this review highlights ways that assessment errors can be reducedparticularly by training raters or using assessment aids. Lesion number in relation to area infected is known to influence accuracy and precision of visual estimatesthe greater the number of lesions for a given area infected results in more overestimation. Furthermore, there is a widespread tendency to overestimate Disease severity at low severities (10%). Both interrater and intrarater reliability can be variable, particularly if training or rating aids are not used. During the last eighty years acceptable accuracy and precision of visual Disease assessments have often been achieved using Disease scales, particularly because of the time they allegedly save, and the ease with which they can be learned, but recent work suggests there can be some disadvantages to their use. This review considers new technologies that offer opportunity to assess Disease with greater objectivity (reliability, precision, and accuracy). One of these, visible light photography and digital image analysis has been increasingly used over the last thirty years, as software has become more sophisticated and user-friendly. Indeed, some studies have produced very accurate estimates of Disease using image analysis. In contrast, hyperspectral imagery is relatively recent and has not been widely applied in Plant pathology. Nonetheless, it offers interesting and potentially discerning opportunities to assess Disease. As Plant Disease assessment becomes better understood, it is against the backdrop of concepts of reliability, precision and accuracy (and agreement) in Plant pathology and measurement science. This review briefly describes these concepts in relation to Plant Disease assessment. Various advantages and disadvantages of the different approaches to Disease assessment are described. For each assessment method some future research priorities are identified that would be of value in better understanding the theory of Disease assessment, as it applies to improving and fully realizing the potential of image analysis and hyperspectral imagery.
C H Bock - One of the best experts on this subject based on the ideXlab platform.
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Plant Disease severity estimated visually by digital photography and image analysis and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to v...
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Plant Disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to visual rating, and this review highlights ways that assessment errors can be reducedparticularly by training raters or using assessment aids. Lesion number in relation to area infected is known to influence accuracy and precision of visual estimatesthe greater the number of lesions for a given area infected results in more overestimation. Furthermore, there is a widespread tendency to overestimate Disease severity at low severities (10%). Both interrater and intrarater reliability can be variable, particularly if training or rating aids are not used. During the last eighty years acceptable accuracy and precision of visual Disease assessments have often been achieved using Disease scales, particularly because of the time they allegedly save, and the ease with which they can be learned, but recent work suggests there can be some disadvantages to their use. This review considers new technologies that offer opportunity to assess Disease with greater objectivity (reliability, precision, and accuracy). One of these, visible light photography and digital image analysis has been increasingly used over the last thirty years, as software has become more sophisticated and user-friendly. Indeed, some studies have produced very accurate estimates of Disease using image analysis. In contrast, hyperspectral imagery is relatively recent and has not been widely applied in Plant pathology. Nonetheless, it offers interesting and potentially discerning opportunities to assess Disease. As Plant Disease assessment becomes better understood, it is against the backdrop of concepts of reliability, precision and accuracy (and agreement) in Plant pathology and measurement science. This review briefly describes these concepts in relation to Plant Disease assessment. Various advantages and disadvantages of the different approaches to Disease assessment are described. For each assessment method some future research priorities are identified that would be of value in better understanding the theory of Disease assessment, as it applies to improving and fully realizing the potential of image analysis and hyperspectral imagery.
Xinzhu Meng - One of the best experts on this subject based on the ideXlab platform.
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the dynamics of Plant Disease models with continuous and impulsive cultural control strategies
Journal of Theoretical Biology, 2010Co-Authors: Xinzhu MengAbstract:Plant Disease mathematical models including continuous cultural control strategy and impulsive cultural control strategy are proposed and investigated. This novel theoretical framework could result in an objective criterion on how to control Plant Disease transmission by rePlanting of healthy Plants and removal of infected Plants. Firstly, continuous rePlanting of healthy Plants and removing of infected Plants is taken. The existence and stability of Disease-free equilibrium and positive equilibrium are studied and continuous cultural control strategy is given. Secondly, Plant Disease model with impulsive rePlanting of healthy Plants and removing of infected Plants is also considered. Using Floquet's theorem and small amplitude perturbation, the sufficient conditions under which the infected Plant free periodic solution is locally stable are obtained. Moreover, permanence of the system is investigated. Under certain parameter spaces, it is shown that a nontrivial periodic solution emerges via a supercritical bifurcation. Finally, our findings are confirmed by means of numerical simulations. The modeling methods and analytical analysis presented can serve as an integrating measure to identify and design appropriate Plant Disease control strategies.
A Meinel - One of the best experts on this subject based on the ideXlab platform.
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more precise map position and origin of a durable non specific adult Plant Disease resistance against stripe rust puccinia striiformis in wheat
Euphytica, 2006Co-Authors: E K Khlestkina, O Unger, M S Roder, A Meinel, A BornerAbstract:Recently a major gene determining non-specific adult Plant Disease resistance against stripe rust (Puccinia striiformis) designated Yrns-B1 was mapped in wheat Triticum aestivum L. by using a cross between ‘Lgst. 79-74’ (resistant) and ‘Winzi’ (susceptible). Linkage to five Gatersleben wheat microsatellite (GWM) markers was discovered, previously mapped on chromosome arm 3BS. In the present study this map was improved by the incorporation of four additional GWM markers. QTL-analysis revealed high LOD values for the resistance at all nine loci, whereas the largest LOD (20.76) was found for the newly mapped marker Xgwm1329.
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the detection and molecular mapping of a major gene for non specific adult Plant Disease resistance against stripe rust puccinia striiformis in wheat
Theoretical and Applied Genetics, 2000Co-Authors: A Borner, M S Roder, O Unger, A MeinelAbstract:A major gene determining non-specific adult-Plant Disease resistance against stripe rust (Puccinia striiformis) designated Yrns-B1 was mapped by using a cross between ’Lgst.79–74’ (resistant) and ’Winzi’ (susceptible). Analyzing F3 lines of two consecutive experimental years contrary modes of inheritance were observed due to the intermediate character of the gene and the difference in the Disease pressure during the seasons. Using the Disease scoring data of both experimental years independently two maps were constructed detecting Yrns-B1 20.5 and 21.7 cM, respectively, proximal to the wheat microsatellite (WMS) marker Xgwm493 on the short arm of chromosome 3BS. The genetic relationships to other major genes or to quantitative trait loci controlling adult Plant Disease resistance against rusts in wheat are discussed.
Gavin H. Poole - One of the best experts on this subject based on the ideXlab platform.
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Plant Disease severity estimated visually by digital photography and image analysis and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to v...
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Plant Disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging
Critical Reviews in Plant Sciences, 2010Co-Authors: C H Bock, Gavin H. Poole, P E Parker, Tim R GottwaldAbstract:Reliable, precise and accurate estimates of Disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for Disease resistance, and for understanding fundamental biological processes including co-evolution. Disease assessments that are inaccurate and/or imprecise might lead to faulty conclusions being drawn from the data, which in turn can lead to incorrect actions being taken in Disease management decisions. Plant Disease can be quantified in several different ways. This review considers Plant Disease severity assessment at the scale of individual Plant parts or Plants, and describes our current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted. The review also considers how these can be identified using various statistical tools. Indeed, great strides have been made in the last thirty years in identifying the sources of assessment error inherent to visual rating, and this review highlights ways that assessment errors can be reducedparticularly by training raters or using assessment aids. Lesion number in relation to area infected is known to influence accuracy and precision of visual estimatesthe greater the number of lesions for a given area infected results in more overestimation. Furthermore, there is a widespread tendency to overestimate Disease severity at low severities (10%). Both interrater and intrarater reliability can be variable, particularly if training or rating aids are not used. During the last eighty years acceptable accuracy and precision of visual Disease assessments have often been achieved using Disease scales, particularly because of the time they allegedly save, and the ease with which they can be learned, but recent work suggests there can be some disadvantages to their use. This review considers new technologies that offer opportunity to assess Disease with greater objectivity (reliability, precision, and accuracy). One of these, visible light photography and digital image analysis has been increasingly used over the last thirty years, as software has become more sophisticated and user-friendly. Indeed, some studies have produced very accurate estimates of Disease using image analysis. In contrast, hyperspectral imagery is relatively recent and has not been widely applied in Plant pathology. Nonetheless, it offers interesting and potentially discerning opportunities to assess Disease. As Plant Disease assessment becomes better understood, it is against the backdrop of concepts of reliability, precision and accuracy (and agreement) in Plant pathology and measurement science. This review briefly describes these concepts in relation to Plant Disease assessment. Various advantages and disadvantages of the different approaches to Disease assessment are described. For each assessment method some future research priorities are identified that would be of value in better understanding the theory of Disease assessment, as it applies to improving and fully realizing the potential of image analysis and hyperspectral imagery.
