Increasing the resilience of cereal and oilseed rape production to weather damage.

提高谷物和油菜生产对天气损害的抵御能力。

• 批准号: BB/P004555/1
• 负责人: George Blackburn
• 金额: $ 70.98万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP004555%2F1
• 关键词: Increasing; resilience; cereal; oilseed; rape

Severe weather can cause cereal and oilseed rape crops to become uprooted or their stems to break, a process called lodging. This means that the crops do not grow to their full potential, the quantity of seed they produce (the yield) is substantially reduced and the quality of the grain decreases meaning that it cannot be used for certain purposes such as bread making. Lodging makes crops more susceptible to infection by fungi which can produce toxic chemicals which render the grain unusable. These impacts of lodging can substantially reduce the value of a crop and there can be additional costs of drying the grain harvested from lodged crops. Hence, it is estimated that lodging can cost UK farmers £170M in a severe lodging year. High winds can also cause oilseed rape pods to shatter which releases the seeds and they cannot be harvested. This costs UK farmers in excess of £7M per year. By taking appropriate action (e.g. choice of crop variety and how it is managed) it is possible for farmers to reduce the likelihood of lodging and pod shatter. However, farmers need information to guide their decisions and currently this is largely absent.This project will develop a computerised system for predicting the risks of lodging and pod shatter. It will be based on a model of how crops behave under conditions of high wind speed and soil moisture that will be developed from field experiments. The system will calculate the distribution of lodging and pod shatter across a farm that is likely to occur under severe weather conditions. This information is useful to farmers for developing plans in advance of a growing season. It will show farmers how weather damage can be reduced by selecting particular crop varieties to plant in particular fields and by adjusting the timing and density of seed planting. The system will also support farmers to make decisions within a growing season. To do this it will use satellite images to monitor the growth of crops early in the growing season and use this information together with scenarios of different weather conditions during the season to predict which fields or parts of fields are likely to be damaged by weather. This will allow farmers to take action to avoid weather damage in vulnerable fields or parts of fields by controlling the growth of crops (by altering the timing or amount of fertiliser and chemical growth regulators) and by applying chemical pod sealants. Later in the growing season the computerised system will download short-range weather forecast information and use this to predict the risks of lodging in the forthcoming weather conditions. If certain fields are predicted to be vulnerable to lodging then the farmer can arrange to harvest those fields before lodging occurs.Overall, the decision-support tool produced by this project will enable farmers to reduce the risks of weather damage to crops. This will increase farmer's capacity to produce food and reduce unnecessary use of chemicals and energy on farms which will be beneficial for the environment.

恶劣的天气会导致谷物和油菜作物被连根拔起或茎杆断裂，这一过程称为倒伏。这意味着作物不能充分发挥其潜力，它们产生的种子数量（产量）大幅减少，谷物的质量下降，这意味着它不能用于某些目的，如制作面包。倒伏使作物更容易受到真菌的感染，真菌会产生有毒的化学物质，使谷物无法使用。倒伏的这些影响可以大大降低作物的价值，并且干燥从倒伏的作物收获的谷物可能会产生额外的成本。因此，据估计，在一个严重的住宿年，住宿可能会花费英国农民1.7亿英镑。大风也会导致油菜豆荚粉碎，释放出种子，无法收获。这使英国农民每年花费超过700万英镑。通过采取适当的行动（例如选择作物品种和如何管理），农民可以减少倒伏和豆荚破碎的可能性。然而，农民需要信息来指导他们的决定，而目前这一点在很大程度上是缺乏的。本项目将开发一个计算机化系统，用于预测倒伏和豆荚破碎的风险。它将基于一个在高风速和土壤湿度条件下作物如何表现的模型，该模型将通过实地实验开发。该系统将计算在恶劣天气条件下可能发生的整个农场的倒伏和荚果破碎的分布。这些信息对农民在生长季节之前制定计划很有用。它将向农民展示如何通过选择特定的作物品种在特定的田地种植以及调整播种的时间和密度来减少天气损害。该系统还将支持农民在生长季节内做出决定。为此，它将利用卫星图像监测作物生长季节初期的生长情况，并利用这一信息以及该季节不同天气条件的情景来预测哪些田地或田地的某些部分可能受到天气的损害。这将使农民能够采取行动，通过控制作物的生长（通过改变化肥和化学生长调节剂的时间或数量）和使用化学豆荚密封剂，避免在脆弱的田地或部分田地受到天气损害。在生长季节的后期，计算机化系统将下载短期天气预报信息，并利用这些信息来预测在即将到来的天气条件下住宿的风险。如果预测某些田地容易倒伏，那么农民可以在倒伏发生之前安排收割这些田地。总的来说，该项目产生的决策支持工具将使农民能够减少天气对作物造成损害的风险。这将提高农民生产粮食的能力，减少农场不必要的化学品和能源使用，这将有利于环境。

项目成果

Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China

• DOI: 10.3390/su11030706
• 发表时间: 2019-01
• 期刊: Sustainability
• 影响因子: 3.9
• 作者: Xinbing Wang;Y. Miao;R. Dong;Zhichao Chen;Y. Guan;Xuezhi Yue;Zheng Fang;D. Mulla

In-season prediction of maize stem lodging risk using an active canopy sensor

• DOI: 10.1016/j.eja.2023.126956
• 发表时间: 2023-11
• 期刊: European Journal of Agronomy
• 影响因子: 5.2
• 作者: R. Dong;Y. Miao;Pete Berry;Xinbing Wang;Fei Yuan;K. Kusnierek;Chris Baker;Mark Sterling

Canopy Fluorescence Sensing for In-Season Maize Nitrogen Status Diagnosis

• DOI: 10.3390/rs13245141
• 发表时间: 2021-12
• 期刊: Remote. Sens.
• 作者: R. Dong;Y. Miao;Xinbing Wang;Fei Yuan;K. Kusnierek

Combining leaf fluorescence and active canopy reflectance sensing technologies to diagnose maize nitrogen status across growth stages

• DOI: 10.1007/s11119-021-09869-w
• 发表时间: 2022-01
• 期刊: Precision Agriculture
• 影响因子: 6.2
• 作者: R. Dong;Y. Miao;Xinbing Wang;Fei Yuan;K. Kusnierek

Development and application of a model for calculating the risk of stem and root lodging in maize

• DOI: 10.1016/j.fcr.2020.108037
• 发表时间: 2021-03-01
• 期刊: FIELD CROPS RESEARCH
• 影响因子: 5.8
• 作者: Berry, P. M.;Baker, C. J.;Whyatt, J. D.
• 通讯作者: Whyatt, J. D.