Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster, OH 44691.
Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907.
Plant Dis. 2021 Jan;105(1):96-107. doi: 10.1094/PDIS-04-20-0876-RE. Epub 2020 Nov 16.
Epidemics of wheat blast, caused the pathotype of , were studied in the Santa Cruz del la Sierra region of Bolivia to quantify and compare the temporal dynamics of the disease under different growing conditions. Six plots of a susceptible wheat cultivar were planted at Cuatro Cañadas (CC), Okinawa 1 (OK1), and Okinawa 2 (OK2) in 2015. Spike blast incidence (INC) and severity (SEV) and leaf blast severity (LEAF) were quantified in each plot at regular intervals on a 10 × 10 grid ( = 100 clusters of spikes), beginning at head emergence (Feekes growth stage 10.5), for a total of nine assessments at CC, six at OK1, and six at OK2. Spike blast increased over time for 20 to 30 days before approaching a mean INC of 100% and a mean SEV of 60 to 75%. The logistic model was the most appropriate for describing the temporal dynamics of spike blast. The highest absolute rates of disease increase occurred earliest at OK1 and latest at OK2, and in all cases it coincided with major rain events. Estimated values (initial blast intensity) were significantly ( < 0.05) higher at OK1 than at CC or OK2, whereas values (the logistic rate parameter) were significantly higher at OK2 than at CC or OK1. It took about 10 fewer days for SEV to reach 10, 15, or 20% at OK1 compared with OK2 and CC. Based on survival analyses, the survivor functions for time to 10, 15 and 20% SEV (s) were significantly different between OK1 and the other locations, with the probabilities of SEV reaching the thresholds being highest at OK1. LEAF at 21 days after Feekes 10.5 had a significant effect on s at OK1. For every 5% increase in LEAF, the chance of SEV reaching the thresholds by day 21 increased by 30 to 55%.
在玻利维亚圣克鲁斯德拉谢拉地区研究了由引起的小麦穗疫病流行，以量化和比较不同种植条件下疾病的时间动态。2015 年在 Cuatro Cañadas (CC)、Okinawa 1 (OK1) 和 Okinawa 2 (OK2) 种植了易感小麦品种的六个地块。在每个地块上，从穗出现（Feekes 生长阶段 10.5）开始，每隔一定时间在 10×10 网格（= 100 个穗簇）上量化穗疫病发生率（INC）和严重度（SEV）以及叶疫病严重度（LEAF），共进行了九次评估在 CC 进行了六次，在 OK1 进行了六次，在 OK2 进行了六次。穗疫病在头出现后 20 到 30 天内逐渐增加，然后接近 100%的平均 INC 和 60 到 75%的平均 SEV。逻辑模型最适合描述穗疫病的时间动态。在 OK1 最早，在 OK2 最晚，在所有情况下都与主要降雨事件同时发生，疾病增加的绝对速率最快。估计值（初始疫病强度）在 OK1 显著（<0.05）高于 CC 或 OK2，而值（逻辑率参数）在 OK2 显著高于 CC 或 OK1。SEV 达到 10%、15%或 20%的时间在 OK1 比在 OK2 和 CC 少了大约 10 天。基于生存分析，SEV 达到 10%、15%和 20%的生存函数（s）在 OK1 与其他地点之间存在显著差异，SEV 达到阈值的概率在 OK1 最高。在 Feekes 10.5 后 21 天的 LEAF 对 OK1 的 s 有显著影响。LEAF 每增加 5%，SEV 在第 21 天达到阈值的机会增加 30%至 55%。
