英国埃塞克斯大学-BBSRC全额奖学金（截止日期：2021年02月08日）

Background：

Apple fruit is usually stored for a minimum of six months in a controlled atmosphere before marketing in the UK. It is not unusual for the stored fruit to suffer from 10-15% post-storage losses due to various causes, including physiological disorders and fungal rotting. This leads to not only yield losses but also increased the cost of sorting fruit post-storage. Fruit storability (i.e. post-storage fruit quality) can be affected by many factors, including flowering time, fruit ripeness at picking, fruit surface microflora, and climatic factors. Furthermore, the relationships of fruit quality with these factors are usually non-linear and the precise causal-relationships have yet to be elucidated.
 

Objectives and approaches：

There are two specific research objectives: (1) predicting flowering time, and (2) predicting fruit ripeness for optimum picking. Predicting the degree of fruit ripeness is critically important since it has been well established that fruit ripeness at picking could significantly affect fruit storage potential.

WP1: Predicting flowering time. Historic data collected at NAB EMR over the last 80 years will be used to study the temporal flowering pattern of several specific cultivars in relation to winter and spring climatic data. Statistical modeling will be carried out to study whether the temporal flowering pattern could be predicted from the winter and spring climatic data alone.

WP2: Predicting fruit ripeness. One key research activity is to work with crop physiologist in order to define physiologically/biochemically what is “perfect fruit ripeness” for harvesting. Previous research on predicting fruit ripeness is based on batches of fruit. To understand the variability of fruit ripeness among individual fruit, we propose to follow the development of individual fruit on several popular cultivars via imaging to investigate whether ripeness can be predicted from the imaging information as well as post-blossom temperatures.

Training：

The successful candidate will gain a wide range of experience in fruit physiology, imaging technology, statistical data analysis/modeling, and machine learning.



2、导师信息

Prof. Xiangming Xu，英国皇家园艺学会终身成就奖获得者，美国植物病理学会会士，英国皇家生物学会会士，兼任英国肯特大学教授、西北农林科技大学后稷学者、中英草莓合作工作室副主任、植物与微生物互作杂志高级编辑、美国植物病理学报和欧洲植物病理学报编辑、frontiers in plant sciense编辑。在植物病害流行、病害防治、真菌生物学和微生物生态学等领域取得了显著成就。在annual review of phytopathology、methods in ecology and evolution、mpmi、phytopathology等杂志发表sci论文160余篇。

导师链接 https://www.emr.ac.uk/staff/prof-xiangming-xu/ 

苏金亚博士，1990年出生于山东，现任英国埃塞克斯大学计算机与电子工程助理教授(UK lecturer)，博士生/博士后导师。2016年博士毕业于英国拉夫堡大学航空与汽车工程系(导师为 EPSRC Established Fellow，IEEE/IET/FIMechE fellow，博士期间获得英国EPSRC 和BAE Systems 公司全额奖学金资助)，随后留校担任博士后研究员至2019年7月。目前承担STFC、Innovate UK资助的卫星、无人机项目2项，总经费约800K英镑。此外，作为主持人或主要参与人完成六项人工智能与智慧农业相关项目，包括英国EPSRC，BBSRC, 牛顿基金等，项目总经费约三百万英镑。在国际著名期刊发表期刊论文33篇(谷歌学术引用次数1200+，多篇高被引论文)，包括3篇Automatica (IFAC旗舰期刊, 中科院一区)和8篇IEEE Transactions(EEE领域旗舰期刊，中科院一区)，5篇Computer and Electronics in Agriculture (精准农业著名期刊，中科院一区)，一篇Transportation Research Part C: Emerging Technology (智能交通旗舰期刊)，一篇Control Engineering Practice等。曾获得2015届国家优秀自费留学生奖学金(全英30名，6000美元奖金)并受邀访问中科院，Essex大学杰出青年学者奖（2020）， Santander 旅行基金(2019)，IEEE-IES 学生论文奖(2016), ICI 最佳论文奖 (2016), ABTA Doctorial Researcher Award (2016), ICAC Best Student Paper Award (2013), EPSRC博士生全额奖学金(2012)。担任IEEE、SAGE、Frontier、Remote sensing 客座编辑，CRC press、40余个期刊、20余个会议审稿人。(辅助)指导3名博士生，毕业去向包括英国讲师、英国高级工程师等。

导师链接 https://www.essex.ac.uk/people/sujin68001/jinya-su



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