期刊
CEREAL RESEARCH COMMUNICATIONS
卷 48, 期 2, 页码 203-210出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s42976-020-00035-y
关键词
Cereals; Multivariate analysis; Weather; Brown rust
类别
资金
- Iranian Agricultural Research, Education and Extension Organization [2-55-16-94165]
During four growing seasons (2013-2017), 282 leaf rust progress curves were characterized across experimental plots according to a number of climate-crop-disease variables in Kermanshah province, Iran. Leaf rust severity differed significantly between levels of cultivar, planting date, sampling time and year factors. Area under disease progress curve (AUDPC) based on disease severity was ranked using Kruskal-Wallis one-way ANOVA. H-test comparison between two disease-onset levels indicated lower mean AUDPC value for late disease onset than that for early disease onset. Highest and lowest AUDPC values were obtained in spring 2016 and 2015, respectively. According to principal component analysis, three principal components accounting for 73% of data variance verified dependence of leaf rust intensity on air temperature and wetness, cultivar resistance, date of disease onset, wheat maturity, and planting date. Based on principal component regression model, disease-onset and maturity date, mean 6-monthly temperature, number of days with minimum temperatures within the range of 5-25 degrees C and maximum RH > 60%, resistance index, and planting date justified 74% of variability in AUDPC dataset. These findings recommend involvement of cultivar resistance, dates of wheat maturity and planting along with weather predictors in wheat-leaf-rust studies to increase prediction value of future models, durability of host resistance to disease, and sustainability of disease control methods.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据