热点

本文重点介绍了未来高通量、无损、性价比高的植物性状测量策略。在植物表型组学领域使用低成本、DIY方法为快速原型开发以及传感器科研提供了机会；稳健规程、数据优化以及来源对表型数据再次应用以及交叉验证至关重要；地下部表型研究是一个主要瓶颈，需要对根部相关特征进行研究的新技术出现。

摘要

2016年，在墨西哥CIMMYT，IPPN主办的第四届植物表型会议上召开了工作组会议，探讨表型传感器进展。田间应用数量的不断增多提供了新挑战，需要专业化的解决方案。

很多性状对植物生长和发育非常关键，对表型研究方法提出苛刻要求，现有方法还在初始研究阶段或无法满足当前要求。另外，当前对低成本传感器解决方案有不断增长需求，要求移动平台可运输到实验场地，而非将实验设施搬运到平台进行。考虑到目标、精度、易于操作以及读取，需要采用多种传感器。将数据转换为知识并确保数据（适当的大数据）以此种方式存储：灵敏且当前可调用，可用于未来分析。此文中基于以前十年的学习、IPPN当前实践与讨论，推荐了新一代表型组学，鼓励植物科学家、物理学家以及工程专家深度思考以及合作。

北京博普特科技有限公司提供了植物表型组学较全面的设备、传感器以及解决方案。欢迎广大客户到2019 IPPS表型会议展位拜访我们。

Review: New sensors and data-driven approaches—A path to next generation phenomics

https://doi.org/10.1016/j.plantsci.2019.01.011Get rights and content

Under a Creative Commons license

open access

Highlights

Strategies for future high throughput, non-destructive and cost-efficient measurement of plant traits are highlighted.

Use of low-cost and DIY approaches in phenomics provides opportunities for rapid prototyping and sensor development.

Robust protocols, data harmonization and provenance are critical to allow data reuse and cross validation of phenotypes.

Below-ground phenotyping is a major bottleneck and new technologies allowing the measurement of root-related traits are needed.

Abstract

At the 4th International Plant Phenotyping Symposium meeting of the International Plant Phenotyping Network (IPPN) in 2016 at CIMMYT in Mexico, a workshop was convened to consider ways forward with sensors for phenotyping. The increasing number of field applications provides new challenges and requires specialised solutions. There are many traits vital to plant growth and development that demand phenotyping approaches that are still at early stages of development or elude current capabilities. Further, there is growing interest in low-cost sensor solutions, and mobile platforms that can be transported to the experiments, rather than the experiment coming to the platform. Various types of sensors are required to address diverse needs with respect to targets, precision and ease of operation and readout. Converting data into knowledge, and ensuring that those data (and the appropriate metadata) are stored in such a way that they will be sensible and available to others now and for future analysis is also vital. Here we are proposing mechanisms for “next generation phenomics” based on our learning in the past decade, current practice and discussions at the IPPN Symposium, to encourage further thinking and collaboration by plant scientists, physicists and engineering experts.