Gitaitis Ronald, Walcott Ronald
Department of Plant Pathology, University of Georgia, Coastal Plain Experiment Station, Tifton, Georgia 31793, USA.
Annu Rev Phytopathol. 2007;45:371-97. doi: 10.1146/annurev.phyto.45.062806.094321.
Although seed production has been moved to semiarid regions to escape seedborne pathogens, seedborne bacterial diseases continue to be problematic and cause significant economic losses worldwide. Infested seeds are responsible for the re-emergence of diseases of the past, movement of pathogens across international borders, or the introduction of diseases into new areas. Considerable attention has been paid to improving the sensitivity and selectivity of seed health assays by using techniques such as flow cytometry and the polymerase chain reaction. There has also been progress in understanding infection thresholds and how they influence seed sample size determination and ultimately the reliability of seed health testing. Disease development and dissemination of pathogens from contaminated seedlots can be predicted using formulas that take into account inoculum density and environmental pressures. In general, seeds infested with bacterial pathogens are distributed within a Poisson distribution. In a subset of contaminated seeds, bacteria are distributed in non-Gaussian distributions, e.g., a lognormal distribution.
尽管种子生产已转移到半干旱地区以避免种子传播的病原体，但种子传播的细菌性疾病仍然是个问题，并在全球范围内造成重大经济损失。受侵染的种子会导致过去的疾病再次出现、病原体跨越国界传播，或将疾病引入新的地区。通过使用流式细胞术和聚合酶链反应等技术，人们已经相当关注提高种子健康检测的灵敏度和选择性。在理解感染阈值以及它们如何影响种子样本大小的确定以及最终种子健康检测的可靠性方面也取得了进展。可以使用考虑接种物密度和环境压力的公式来预测受污染种子批次中病原体的疾病发展和传播。一般来说，受细菌病原体侵染的种子呈泊松分布。在一部分受污染的种子中，细菌呈非高斯分布，例如对数正态分布。
