Visual rating and the use of image analysis for assessing different symptoms of citrus canker on grapefruit leaves
Visual rating and the use of image analysis for assessing different symptoms of citrus canker on grapefruit leaves
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DOI：
10.1094/pdis-92-4-0530
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发表时间：
2008-04-01
期刊：
影响因子：
4.5
通讯作者：
Gottwald, T. R.
中科院分区：
文献类型：
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作者：
Bock, C. H.;Parker, P. E.;Gottwald, T. R.
柑橘溃烂病是由黄单胞菌引起的一种柑橘溃烂病。在潮湿的热带和亚热带柑橘种植区，可以侵染几种柑橘。为了监测育种材料中的流行病和疾病反应，需要准确、精确和可重复的疾病评估。本研究的目的是评估图像分析(IA)测量溃烂症状严重程度的重复性，并将其与三个视觉评分器(VR1-3)对不同症状类型(病变数目、面积坏死百分比和面积坏死+黄斑百分比)进行的视觉评估进行比较，并评估VR间和VR内的可重复性。对具有不同症状严重程度的210片柑橘叶片的数字图像在两个不同的场合进行了评估。对于所有症状类型，IA均比VRS更准确(评估间相关系数r，IA=0.99，VRS=0.89~0.94；%，IA=0.97，VRS=0.86~0.89；%，IA=0.96，VRS=0.74~0.85)。基于林的协调系数的准确性也遵循类似的模式，与视觉评分器(C-b=0.85至1.00)相比，IA对所有症状类型(偏差校正系数，C-b=0.99至1.00)的准确性最一致。病变个数的重复性最好(林氏一致性相关系数，Rho(C)=0.76~0.99)，其次是面积坏死+黄斑的百分比(Rho(C)=0.85~0.97)，最后是面积坏死的百分比(Rho(C)=0.72~0.96)。根据IA提供的“真”值，VRS对每叶病斑数的精确度是合理的(r=0.88~0.94)，对面积坏死率+黄化病的精确度稍差(r=0.87~0.92)，对坏死叶面积的精确度最差(r=0.77~0.83)。准确性损失较小，但在病变数目(C-b=0.93至0.99)方面表现出类似的趋势，VRS比面积坏死百分比(C-b=0.85至0.99)或面积坏死+黄斑百分比(C-b=0.91至1.00)更准确地再现病变数目。因此，视觉评分器在精确度和准确度上都受到了损失，其中以精确度估计面积坏死率损失最大。事实上，只有面积坏死率对评分者有显著影响(双向随机效应模型方差分析在评估I和2中分别为评分者返回P 0.001和0.016)。VRS表现出明显的倾向于聚集百分比区域严重性估计，特别是在严重程度为20%的区域(例如，25、30、35、40等)，然而VRS准备估计疾病
Citrus canker is caused by the bacterial pathogen Xanthomonas axonopodis pv. citri and infects several citrus species in wet tropical and subtropical citrus growing regions. Accurate, precise, and reproducible disease assessment is needed for monitoring epidemics and disease response in breeding material. The objective of this study was to assess reproducibility of image analysis (IA) for measuring severity of canker symptoms and to compare this to visual assessments made by three visual raters (VR1-3) for various symptom types (lesion numbers, % area necrotic, and % area necrotic+chlorotic), and to assess inter- and intra-VR reproducibility. Digital images of 210 citrus leaves with a range of symptom severity were assessed on two separate occasions. IA was more precise than VRs for all symptom types (inter-assessment correlation coefficients, r, for lesion numbers by IA = 0.99, by VRs = 0.89 to 0.94; for %, r for % area necrotic+chlorotic for IA = 0.97 and for VRs 0.86 to 0.89; and r for % area necrotic for IA = 0.96 and for VRs = 0.74 to 0.85). Accuracy based on Lin's concordance coefficient also followed a similar pattern, with IA being most consistently accurate for all symptom types (bias correction factor, C-b = 0.99 to 1.00) compared to visual raters (C-b = 0.85 to 1.00). Lesion number was the most reproducible symptom assessment (Lin's concordance correlation coefficient, rho(c), = 0.76 to 0.99), followed by % area necrotic+chlorotic (rho(c) = 0.85 to 0.97), and finally % area necrotic (rho(c) = 0.72 to 0.96). Based on the "true" value provided by IA, precision among VRs was reasonable for number of lesions per leaf (r = 0.88 to 0.94), slightly less precision for % area necrotic+chlorotic (r = 0.87 to 0.92), and poorest precision for % area necrotic (r = 0.77 to 0.83). Loss in accuracy was less, but showed a similar trend with counts of lesion numbers (C-b = 0.93 to 0.99) which was more consistently accurately reproduced by VRs than either % area necrotic (C-b = 0.85 to 0.99) or % area necrotic+chlorotic (C-b = 0.91 to 1.00). Thus, visual raters suffered losses in both precision and accuracy, with loss in precision estimating % area necrotic being the greatest. Indeed, only for % area necrotic was there a significant effect of rater (a two-way random effects model ANOVA returned a P 0.001 and 0.016 for rater in assessments I and 2, respectively). VRs showed a marked preference for clustering of % area severity estimates, especially at severity >20% area (e.g., 25, 30, 35, 40, etc.), yet VRs were prepared to estimate disease of