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草莓白粉病(瓜单囊壳白粉菌)的空间分布模式及气传接种体

Spatial Pattern of Strawberry Powdery Mildew (Podosphaera aphanis) and Airborne Inoculum.

作者信息

Van der Heyden H, Lefebvre M, Roberge L, Brodeur L, Carisse O

机构信息

Compagnie de Recherche Phytodata inc., 111 Rang Saint-Patrice, Sherrington, Quebec, J0L 2N0, Canada.

Agriculture and Agri-Food Canada, 430 Gouin Boulevard, St-Jean-sur-Richelieu, Quebec, Canada J3B 3E6, Canada.

出版信息

Plant Dis. 2014 Jan;98(1):43-54. doi: 10.1094/PDIS-10-12-0946-RE.

Abstract

The relationship between strawberry powdery mildew and airborne conidium concentration (ACC) of Podosphaera aphanis was studied using data collected from 2006 to 2009 in 15 fields, and spatial pattern was described using 2 years of airborne inoculum and disease incidence data collected in fields planted with the June-bearing strawberry (Fragaria × ananassa) cultivar Jewel. Disease incidence, expressed as the proportion of diseased leaflets, and ACC were monitored in fields divided into 3 × 8 grids containing 24 100 m quadrats. Variance-to-mean ratio, index of dispersion, negative binomial distribution, Poisson distribution, and binomial and beta-binomial distributions were used to characterize the level of spatial heterogeneity. The relationship between percent leaf area diseased and daily ACC was linear, while the relationship between ACC and disease incidence followed an exponential growth curve. The V/M ratios were significantly greater than 1 for 100 and 96% of the sampling dates for ACC sampled at 0.35 m from the ground (ACC) and for ACC sampled at 1.0 m from the ground (ACC), respectively. For disease incidence, the index of dispersion D was significantly greater than 1 for 79% of the sampling dates. The negative binomial distribution fitted 86% of the data sets for both ACC and ACC. For disease incidence data, the beta-binomial distribution provided a good fit of 75% of the data sets. Taylor's power law indicated that, for ACC at both sampling heights, heterogeneity increased with increasing mean ACC, whereas the binary form of the power law suggested that heterogeneity was not dependent on the mean for disease incidence. When the spatial location of each sampling location was taken into account, Spatial Analysis by Distance Indices showed low aggregation indices for both ACCs and disease incidence, and weak association between ACC and disease incidence. Based on these analyses, it was found that the distribution of strawberry powdery mildew was weakly aggregated. Although a higher level of heterogeneity was observed for airborne inoculum, the heterogeneity was low with no distinct foci, suggesting that epidemics are induced by well-distributed inoculum. This low level of heterogeneity allows mean airborne inoculum concentration to be estimated using only one sampler per field with an overall accuracy of at least 0.841. The results obtained in this study could be used to develop a sampling scheme that will improve strawberry powdery mildew risk estimation.

摘要

利用2006年至2009年在15个田块收集的数据,研究了草莓白粉病与瓜单囊壳白粉菌气传分生孢子浓度(ACC)之间的关系,并使用在种植四季草莓(凤梨草莓)品种“宝石”的田块中收集的2年气传接种体和发病率数据描述了空间格局。发病率以病叶比例表示,在划分为3×8网格、包含24个100平方米样方的田块中监测ACC。使用方差均值比、离散度指数、负二项分布、泊松分布以及二项分布和贝塔二项分布来表征空间异质性水平。病叶面积百分比与每日ACC之间的关系呈线性,而ACC与发病率之间的关系呈指数增长曲线。对于离地0.35米处采集的ACC(ACC)和离地1.0米处采集的ACC,在分别100%和96%的采样日期,V/M比显著大于1。对于发病率,在79%的采样日期,离散度指数D显著大于1。负二项分布对ACC和ACC的86%的数据集拟合良好。对于发病率数据,贝塔二项分布对75%的数据集拟合良好。泰勒幂定律表明,对于两个采样高度的ACC,异质性随平均ACC的增加而增加,而幂定律的二元形式表明异质性不依赖于发病率的均值。当考虑每个采样位置的空间位置时,距离指数空间分析显示ACC和发病率的聚集指数较低,且ACC与发病率之间的关联较弱。基于这些分析,发现草莓白粉病的分布呈弱聚集性。尽管气传接种体的异质性水平较高,但异质性较低且无明显病灶,这表明病害流行是由分布均匀的接种体引起的。这种低水平的异质性使得每个田块仅使用一个采样器就能估计气传接种体的平均浓度,总体准确率至少为0.841。本研究获得的结果可用于制定改进草莓白粉病风险评估 的采样方案。

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