权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

14TSB_ATC_IR Exploiting novel canopy sensors for improved disease management, variety selection and resilience in wheat

14TSB_ATC_IR 利用新型冠层传感器改善小麦的疾病管理、品种选择和恢复力

基本信息

批准号：
BB/M011550/1
负责人：
Rumiana Ray
金额：
$ 51.8万
依托单位：
University of Nottingham
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FM011550%2F1
关键词：
14TSB_ATC_IR Exploiting novel canopy sensors

项目摘要

Commercial production of wheat crops in the UK is currently highly dependent on timely applications of fungicides to optimise yield and the development of improved varieties by plant breeders with resilience to diseases and abiotic stresses. There is currently insufficient understanding and knowledge of how fungicide inputs can be optimised to grain yield and how plant health can be rapidly and precisely measured in the field to improve crop management decision-making and efficiency of selection in plant breeding. There is a continuous need to breed crops with improved performance, such as disease resistance and drought tolerance, to ensure food supplies are resilient in the face of a changing environment. The bottleneck is now in the ability to conduct field-based discovery and evaluation of traits (phenotyping), which are currently laborious, time-consuming and inefficient. The project will therefore develop canopy sensor phenomics platforms, based on chlorophyll fluorescence and hyperspectral imaging systems, which will allow a high throughput and detailed evaluation of crop performance. Chlorophyll fluorescence signatures (FP100 Fluorpen amd multiple detection probes Waltz) for estimating photosynthetic efficiency in the field will be developed to provide early signatures for biotic (Septoria) and abiotic (drought) stress on wheat. Firstly, this system will be developed in glasshouse conditions on 'stands' of wheat and secondly in-field (6 cultivars x 2 fungicide programmes) to relate these to crop management decisions and breeding selection. Ground-truthing measurements will include:(i) a molecular PCR assay developed for Septoria tritici DNA quantification, (ii) visual disease and (iii) crop growth by destructive harvesting.We will also develop hyperspectral canopy-sensor signatures to enable imaging across wider wavelength ranges (300 -2300 nm) and larger plot areas and with a higher throughput than is currently used for in-field crop monitoring: A high throughput, automated imaging system using a hyperspectral camera mounted on a tractor will be used to produce a spatial map of a complete field experiment (6 cultiars x 2 fungicide treatments). Data sets will be mined to identify a new metric from a subset of wavelengths predicting key traits, e.g. canopy green area, crop biomass and N content. Groundtruthing measurements will include: (i) crop growth by destructive harvesting, (ii) handheld hyperspectral measurements (FieldSpecHandHeld 2 Pro (350-1075 nm), Analytik Ltd) and (iii) visual disease. A key objective here will be to investigate the feasibility of replicating hand-collected and tractor mounted hyperspectral datasets using UAV (Oktocopter2) mounted sensors for aerial imaging.The phenotyping platforms will be validated by agronomists for optimised crop decision-making at three sites (high Septoria, high drought and control) in validation trials (6 cultivars x 2 fungicide programmes; 2 fungicide programmes x 6 fungicide treatments) and by breeders for varietal selections at one site in the project. The high-throughput canopy sensors (ground-based and aerial) will be tested as decision tools and provide a step change in the efficiency of wheat predictive agronomy and breeding and a basis for improving wheat for UK farmers, processors and consumers.

英国小麦作物的商业化生产目前高度依赖于及时施用杀菌剂以优化产量，以及植物育种者开发具有抗病和非生物胁迫能力的改良品种。目前对如何优化杀真菌剂投入以提高谷物产量以及如何在田间快速准确地测量植物健康以改善作物管理决策和植物育种选择效率的理解和知识不足。不断需要培育具有更好性能的作物，如抗病性和耐旱性，以确保粮食供应在不断变化的环境中具有弹性。目前的瓶颈是进行基于实地的特征发现和评价（表型分析）的能力，目前这是费力、耗时和低效的。因此，该项目将开发基于叶绿素荧光和高光谱成像系统的冠层传感器表型组学平台，这将实现对作物表现的高通量和详细评估。叶绿素荧光信号（FP 100荧光笔和多个检测探针华尔兹）估计光合效率在外地将被开发，以提供生物（壳针孢属）和非生物（干旱）对小麦的压力的早期信号。首先，该系统将在温室条件下开发的小麦“看台”，其次在外地（6个品种× 2杀真菌剂方案），这些作物管理决策和育种选择。地面实况测量将包括：（i）为三孢壳针孢DNA定量开发的分子PCR分析，（ii）视觉疾病和（iii）通过破坏性收获的作物生长。我们还将开发高光谱冠层传感器特征，以便在更宽的波长范围内成像（300 - 2300 nm）和更大的地块面积，并具有比目前用于田间作物监测的更高的吞吐量：高吞吐量，将使用安装在拖拉机上的高光谱照相机的自动成像系统来产生完整的野外实验的空间图（6个栽培物X 2个杀真菌剂处理）。数据集将被挖掘，以确定一个新的度量从一个子集的波长预测的关键性状，如冠层绿色面积，作物生物量和氮含量。地面实况测量将包括：（一）通过破坏性收获的作物生长，（二）手持高光谱测量（FieldSpecHandHeld 2 Pro（350-1075 nm），Analytik Ltd）和（三）视力疾病。这里的一个关键目标是调查使用无人机复制手工收集和拖拉机安装的高光谱数据集的可行性表型分析平台将由农学家进行验证，以优化三个地点的作物决策。（高壳针孢，高干旱和控制）在验证试验（6个品种x2个杀真菌剂方案; 2个杀真菌剂方案x6个杀真菌剂处理）和育种者在项目的一个地点进行品种选择。高通量冠层传感器（地面和空中）将作为决策工具进行测试，并为小麦预测农艺学和育种的效率提供一个步骤变化，并为英国农民，加工商和消费者改进小麦提供基础。