Performance and Stability of Winter Wheat Cultivars to Stagonospora Nodorum Blotch Epidemics in Multi-Environment Trials.

IF 3.1 2区 农林科学 Q2 PLANT SCIENCES
Vinicius C Garnica, Mohammad Nasir Shalizi, Peter S Ojiambo
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引用次数: 0

Abstract

Field performance of winter wheat genotypes with quantitative resistance to Stagonospora nodorum blotch is influenced by genotype-by-environment interactions (GEI). This phenomenon explains why cultivars may perform inconsistently across environments, affecting decisions on locally adapted varieties. Further, GEI can also impact risk assessment when cultivar reaction is used as a model predictor under the assumption of stability of responses across environments. Thus, this study investigated GEI effects on four disease metrics; final disease severity (SEV), relative area under disease progress stairs (rAUDPS), time to 50% disease incidence (T50) and the apparent rate of disease increase (ω), describing SNB epidemics of 18 commercial soft red winter wheat cultivars planted in 18 environments in North Carolina from 2021 to 2024. Linear mixed models with various variance-covariance structures for random effects were used to analyze the disease data and a 3rd order factor analytic model provided the best fit to the data across the metrics examined. Type B genetic correlation (rg), broad-sense heritability (Hb^2), overall cultivar performance (OP), and global stability (RMSD), were estimated using model outputs and the factor analytic selection tool method. For SEV, rAUDPS and T50, values of rg ranged from -0.15 to 0.99 with most environment pairs exhibiting high rg values indicating an agreement in cultivar rankings. Cultivar 'USG 3230' was the top-performing and most stable, while 'TURBO' and 'SH7200' were more unstable cultivars. Cultivar reaction classes derived from OP exhibited consistent class-level means of marginal predictions supporting their utility as stable indicators of SNB susceptibility in risk assessment models.

冬小麦品种对斑病病多环境试验的表现及稳定性
具有数量抗性的冬小麦基因型田间表现受基因型-环境相互作用(GEI)的影响。这一现象解释了为什么品种在不同环境下的表现可能不一致,从而影响对适应当地环境的品种的决策。此外,当品种反应被用作模型预测因子时,假设不同环境下的反应是稳定的,GEI也可以影响风险评估。因此,本研究调查了GEI对四种疾病指标的影响;最终疾病严重程度(SEV)、疾病进展阶梯相对面积(rAUDPS)、到50%发病时间(T50)和表观疾病增长率(ω),描述了2021 - 2024年北卡罗来纳州18个环境中种植的18个软红冬小麦品种的SNB流行情况。采用随机效应的各种方差-协方差结构的线性混合模型对疾病数据进行分析,三阶因子分析模型为所检查指标的数据提供了最佳拟合。利用模型输出和因子分析选择工具方法估算了B型遗传相关(rg)、广义遗传力(Hb^2)、品种综合表现(OP)和整体稳定性(RMSD)。SEV、rAUDPS和T50的rg值在-0.15 ~ 0.99之间,大多数环境对的rg值较高,表明品种排名一致。品种‘USG 3230’表现最好、最稳定,而‘TURBO’和‘SH7200’表现较不稳定。来自OP的品种反应等级显示出一致的类别水平边际预测均值,支持它们作为风险评估模型中SNB敏感性的稳定指标的效用。
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来源期刊
Phytopathology
Phytopathology 生物-植物科学
CiteScore
5.90
自引率
9.40%
发文量
505
审稿时长
4-8 weeks
期刊介绍: Phytopathology publishes articles on fundamental research that advances understanding of the nature of plant diseases, the agents that cause them, their spread, the losses they cause, and measures that can be used to control them. Phytopathology considers manuscripts covering all aspects of plant diseases including bacteriology, host-parasite biochemistry and cell biology, biological control, disease control and pest management, description of new pathogen species description of new pathogen species, ecology and population biology, epidemiology, disease etiology, host genetics and resistance, mycology, nematology, plant stress and abiotic disorders, postharvest pathology and mycotoxins, and virology. Papers dealing mainly with taxonomy, such as descriptions of new plant pathogen taxa are acceptable if they include plant disease research results such as pathogenicity, host range, etc. Taxonomic papers that focus on classification, identification, and nomenclature below the subspecies level may also be submitted to Phytopathology.
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