中文摘要：在田间，表型性状通常用于诊断赤霉病(FHB) 的发展情况，而麦粒中霉菌毒素积累情况的准确评估只能运用高成本的方法，如高效液相色谱法(HPLC)。本研究旨在确定：（i）现有的现有商业决策支持工具所提供的结果能否用表型测量，包括一种新型的计算机辅助麦穗图像分析技术来预测；（ii）这些测量能否避免使用HPLC。研究表明，这种新型计算机辅助图像分析技术对脱氧雪腐镰刀菌烯醇的积累有更好的预测能力，比传统视觉症状评估更加客观省时。该评估法适合补充现有的预测工具，避免在可能感染的地块中系统和昂贵地测量霉菌毒素.
外文摘要：Phenotypic traits are regularly used to diagnose the development of Fusarium head blight (FHB) in the field, whereas mycotoxin accumulation in wheat grains can only be accurately evaluated through costly methods, such as high–performance liquid chromatography (HPLC). The aim of this study was to determine whether: (i) the results provided by existing commercial decision support tools could be anticipated using phenotypic measurements, including a novel technique of computer–assisted image analysis of spikes; and (ii) these measurements could avoid using HPLC. We monitored the FHB development during two consecutive years in highly contaminated plots in the Burgundy region (France). Contamination by crop residues was simulated through a field inoculation with barley grains artificially colonized by Fusarium graminearum. The development of the disease on spikes and harvested grains was assessed on one tolerant and two susceptible wheat varieties. The accumulated amounts of mycotoxins were measured in harvested grains using HPLC. As expected, the measured traits revealed that the inoculum responsible for infection on spikes mainly came from residues left on the soil surface, and the susceptible varieties were more diseased than the tolerant variety. Weather conditions had a strong effect on disease development. The novel computer–assisted image analysis technique had a better prediction power of deoxynivalenol accumulation, was more objective and time–saving than classical visual symptom assessments. This assessment method could be suitable to supplement the use of existing prediction tools and might avoid systematic and costly mycotoxin measurements in likely infected plots.
外文关键词：Fusarium graminearum；Preceding crops residues；Weather conditions；Computer-assisted image analysis；Decision support tools
作者：Leplat, J；Mangin, P；Falchetto, L；Heraud, C；Gautheron, E；Steinberg, C
作者单位：Univ Bourgogne
期刊名称：EUROPEAN JOURNAL OF PLANT PATHOLOGY
期刊影响因子：1.494
出版年份：2018
出版刊次：4
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