首页> 外文期刊>Phytopathologia Mediterranea >Unmanned Aerial Vehicle (UAV)-based remote sensing to monitor grapevine leaf stripe disease within a vineyard affected by esca complex
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Unmanned Aerial Vehicle (UAV)-based remote sensing to monitor grapevine leaf stripe disease within a vineyard affected by esca complex

机译:无人驾驶飞机(UAV)基于遥感,以监测受ESCA复合物影响的葡萄园内的葡萄叶片条纹病

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摘要

Foliar symptoms of grapevine leaf stripe disease (GLSD, a disease within the esca complex) are linked to drastic alteration of photosynthetic function and activation of defense responses in affected grapevines several days before the appearance of the first visible symptoms on leaves. The present study suggests a methodology to investigate the relationships between high-resolution multispectral images (0.05 m/ pixel) acquired using an Unmanned Aerial Vehicle (UAV), and GLSD foliar symptoms monitored by ground surveys. This approach showed high correlation between Normalized Differential Vegetation Index (NDVI) acquired by the UAV and GLSD symptoms, and discrimination between symptomatic from asymptomatic plants. High-resolution multispectral images were acquired during June and July of 2012 and 2013, in an experimental vineyard heavily affected by GLSD, located in Tuscany (Italy), where vines had been surveyed and mapped since 2003. Each vine was located with a global positioning system, and classified for appearance of foliar symptoms and disease severity at weekly intervals from the beginning of each season. Remote sensing and ground observation data were analyzed to promptly identify the early stages of disease, even before visual detection. This work suggests an innovative methodology for quantitative and qualitative analysis of spatial distribution of symptomatic plants. The system may also be used for exploring the physiological bases of GLSD, and predicting the onset of this disease.
机译:葡萄叶片条纹疾病(GLSD,ESCA复合物中的疾病)叶面症状(ESCA综合体内的疾病)与光合作用的急剧改变有关,并且在叶子上的第一个可见症状外观之前的几天内受影响的葡萄园的防御反应。本研究表明,研究使用无人驾驶飞行器(UAV)获取的高分辨率多光谱图像(0.05米/像素)与由地面调查监测的GLSD叶面症状的方法。这种方法在无人机和GLSD症状获得的归一化差分植被指数(NDVI)之间表现出高的相关性,以及从无症状植物症状之间的歧视。 2012年6月和2013年7月在2012年和2013年7月获得了高分辨率的多光谱图像,该实验葡萄园受到位于托斯卡纳(意大利)的GLSD影响,自2003年以来已被调查和映射葡萄园。每个藤都有全球定位系统,并在每季开始时每周间隔分类为叶面症状和疾病严重程度。分析遥感和地面观察数据以及时识别疾病的早期阶段,即使在目视检测之前也是如此。这项工作表明,对症状植物的空间分布的定量和定性分析进行了创新方法。该系统还可用于探索GLSD的生理基础,并预测该疾病的发作。

著录项

  • 来源
    《Phytopathologia Mediterranea》 |2016年第2期|共14页
  • 作者单位

    CNR Ist Biometeorol IBIMET Via G Caproni 8 I-50145 Florence Italy;

    Univ Florence Sez Patol Vegetale &

    Entomol Dipartimento Sci Prod Agroalimentari &

    Ambiente D Piazzale Cascine 28 I-50144 Florence Italy;

    CNR Ist Biometeorol IBIMET Via Gobetti 101 I-40129 Bologna Italy;

    CNR Ist Biometeorol IBIMET Via Gobetti 101 I-40129 Bologna Italy;

    CNR Ist Biometeorol IBIMET Via G Caproni 8 I-50145 Florence Italy;

    Univ Florence Sez Patol Vegetale &

    Entomol Dipartimento Sci Prod Agroalimentari &

    Ambiente D Piazzale Cascine 28 I-50144 Florence Italy;

    Univ Perugia Dipartimento Sci Agr &

    Ambientali Borgo XX Giugno 74 I-06128 Perugia Italy;

    Univ Florence Sez Patol Vegetale &

    Entomol Dipartimento Sci Prod Agroalimentari &

    Ambiente D Piazzale Cascine 28 I-50144 Florence Italy;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 植物学;
  • 关键词

    precision viticulture; disease detection; asymptomatic plant; trunk disease;

    机译:精确葡萄栽培;疾病检测;无症状植物;躯干疾病;
  • 入库时间 2022-08-20 06:15:03

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