Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy,Agricultural Systems

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Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy
Agricultural Systems ( IF 6.1 ) Pub Date : 2021-07-14 , DOI: 10.1016/j.agsy.2021.103223
Hui Wang ₁ , Gabriele Mongiano ₂ , Davide Fanchini ₃ , Patrizia Titone ₂ , Luigi Tamborini ₂ , Simone Bregaglio ₃

Affiliation

CONTEXT

Rice blast manifests with different symptoms according to the affected plant organ, i.e., leaf and panicle blast, the latter being the primary determinant of yield losses in Italy. Forecasting models have been developed to drive fungicides application and perform scenario analyses to plan legislative measures on plant protection. An assessment of the blast pathogen pressure evolution in the Italian rice area under climate change realizations has not been done yet.

OBJECTIVE

We developed the ELLE process-based forecasting model (ricE bLast simuLation modEl) to reproduce the dynamics of leaf and panicle blast severity and incidence to release a tool to perform in-season monitoring and scenario assessment. The forecasting model is delivered as a RESTful API and is ready to be used by third parties for operational monitoring activities. Here we present its application to assess future rice blast impacts in Italy after an extended calibration and evaluation with ground-truth data.

METHODS

The reference dataset for model testing comprised (a) a multi-year (2013–2015) and multi-site (three locations) experimental trial, where leaf and panicle blast were assessed on four Italian rice varieties with different levels of susceptibility to blast disease, and (b) historical disease data collected at the municipality level. We then performed spatially distributed simulations at 2 × 2 km resolution on the Northern Italian rice district, considering a short- (2030) and long- (2070) term time horizon and rice varieties representative of the current variability in phenology and susceptibility to blast disease within the Italian varietal landscape. The factorial combinations of climatic projections from four General Circulation Models and two extreme CO₂ Representative Concentration Pathways were used as model inputs in the scenario analysis.

RESULTS AND CONCLUSIONS

Model calibration and evaluation at the field level denoted an overall accurate reproduction of leaf blast severity (RRMSE <13%) and panicle blast incidence (RRMSE <17%). The climate change scenario analysis highlighted the varietal susceptibility as the critical factor determining leaf and panicle blast variability in the future, with no significant changes in 2030 and a slight decline in 2070.

SIGNIFICANCE

Besides delivering a reusable methodology to analyze the severity and incidence of leaf and panicle blast, our modelling study confirms that varietal susceptibility is the main feature to be pursued in rice breeding programs to counteract blast disease.

中文翻译：

品种易感性克服了气候变化对意大利北部稻瘟病未来趋势的影响

语境

稻瘟病根据受影响的植物器官表现出不同的症状，即叶瘟和穗瘟，后者是意大利产量损失的主要决定因素。已经开发了预测模型来推动杀菌剂的应用并进行情景分析以规划植物保护的立法措施。尚未对意大利水稻区在气候变化实现下的稻瘟病病原体压力演变进行评估。

客观的

我们开发了基于 ELLE 过程的预测模型（ricE bLast simuLation modEl）来重现叶片和穗部稻瘟病严重程度和发生率的动态，以发布执行季节监测和情景评估的工具。预测模型作为 RESTful API 提供，可供第三方用于运营监控活动。在这里，我们展示了它在使用地面实况数据进行扩展校准和评估后评估意大利未来稻瘟病影响的应用。

方法

模型测试的参考数据集包括 (a) 多年（2013-2015 年）和多地点（三个地点）实验试验，其中评估了四种对稻瘟病易感性不同的意大利水稻品种的叶和穗稻瘟病，以及 (b) 在市级收集的历史疾病数据。然后，我们在意大利北部稻区以 2 × 2 公里分辨率进行空间分布模拟，考虑到短期（2030 年）和长期（2070 年）时间范围以及代表当前物候变化和对稻瘟病易感性的水稻品种在意大利品种景观中。四个大气环流模型和两个极端 CO ₂气候预测的因子组合代表性浓度途径用作情景分析中的模型输入。