New tools for predicting spread of Fusarium wilt in banana

预测香蕉枯萎病传播的新工具

• 批准号: 2271237
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2271237
• 关键词: New; tools; predicting; spread; Fusarium

Banana (Musa spp) is the 5th most important global food staple, but as a consequence of its clonal nature, banana production suffers significantly from pathogens. In the last banana apocalypse, Fusarium oxysporum var. cubense Race 1 (Foc1) destroyed global production of "Gros Michel". India, the biggest producer of bananas in the world (~25% global production), consumes nearly all its production. The highly virulent Fusarium Wilt Tropical Race 4 (Foc4) arrived in India in 2018 and in 2019 it was found in South America, threatening both food security (India is the world's largest banana producer) and the trade in banana commodities. This project has two key objectives. (i) Generating robust molecular markers that can be used in field for identification of TR4 and inform management strategies. (ii) Developing satellite-based remote sensing approaches will be developed for automatic demarcation of banana plantations, and identification of plant stress.Methods:Next generation sequencingBig data analysis - satellite radarHyperspectral imagingDevelopment of diagnostic molecular markers.Development of LAMP assays for in field detection of Fusarium.This will involve training in handling large datasets, both genomic (Fusarium; comparative genomics across different races and geographical/population structures) and geo-sattelite. to develop intra-specific genomic markers that can be used to track spread of individual pathogen genotypes across space and time. These TR4-specific sequences, will be used to develop PCR- and LAMP-based diagnostic assays, the latter of which could be deployed in the field using a battery-powered portable device.The remote sensing studies (from month 18) will use the European Space Agency's Sentinel Synthetic Aperature Radar (SAR) to develop radar signatures for banana plantations, using Google Earth imagery and plantation maps from partner organizations. In the first instance Costa Rica data will be used for training and statistical clustering algorithms such as Random Forest used for classification. Open-access, spectral data from LANDSAT will be used to develop vegetation indices for plantations, to understand spatial and temporal variation in plant health. Higher resolution imagery will be acquired using UAVs with multispectral scanners, both to validate satellite imagery and to avoid problems with image acquisition due to cloud cover. For ground truthing drone data collection, we aim to include some glasshouse experimentation to monitor effects of diseases on reflectance, due to changes in leaf chemistry or morphology.

香蕉（Musa spp）是全球第五大主要粮食作物，但由于其克隆性质，香蕉生产受到病原体的严重影响。在上一次香蕉灾难中，尖孢镰刀菌变种（Fusarium oxysporum var.）古巴1号种族（Foc 1）摧毁了“格罗斯·米歇尔”的全球生产。印度是世界上最大的香蕉生产国（约占全球产量的25%），几乎消耗了所有的产量。2018年，高度致命的枯萎病热带小种4（Foc 4）抵达印度，2019年在南美洲发现，威胁到粮食安全（印度是世界上最大的香蕉生产国）和香蕉商品贸易。该项目有两个主要目标。(i)产生可用于田间鉴定TR 4并告知管理策略的稳健分子标记。(ii)将开发基于卫星的遥感方法，用于香蕉种植园的自动划分和植物胁迫的识别。方法：下一代测序大数据分析-卫星雷达高光谱成像诊断分子标记的开发。开发用于现场检测镰刀菌的LAMP分析。这将涉及处理大型数据集的培训，包括基因组（镰刀菌;不同种族和地理/人口结构的比较基因组学）和地理卫星。开发可用于跟踪单个病原体基因型在空间和时间上的传播的特异性基因组标记。这些TR 4特异性序列将被用于开发基于PCR和LAMP的诊断分析，后者可以使用电池供电的便携式设备部署在实地。遥感研究（从第18个月开始）将使用欧洲航天局的哨兵合成孔径雷达（SAR），利用谷歌地球图像和伙伴组织的种植园地图，开发香蕉种植园的雷达特征。首先，哥斯达黎加的数据将用于训练和统计聚类算法，如用于分类的随机森林。将利用大地卫星提供的开放式光谱数据制定种植园的植被指数，以了解植物健康的空间和时间变化。将使用配备多光谱扫描仪的无人机获取更高分辨率的图像，以验证卫星图像并避免因云层覆盖而导致的图像获取问题。对于地面实况无人机数据收集，我们的目标是包括一些温室实验，以监测由于叶片化学或形态变化而引起的疾病对反射率的影响。