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高通量表型分析能否助力地中海地区的粮食安全?

Can High Throughput Phenotyping Help Food Security in the Mediterranean Area?

作者信息

Danzi Donatella, Briglia Nunzio, Petrozza Angelo, Summerer Stephan, Povero Giovanni, Stivaletta Alberto, Cellini Francesco, Pignone Domenico, De Paola Domenico, Janni Michela

机构信息

Institute of Biosciences and Bioresources, National Research Council, Bari, Italy.

Dipartimento delle Culture Europee e del Mediterraneo: Architettura, Ambiente, Patrimoni Culturali, Università degli Studi della Basilicata, Matera, Italy.

出版信息

Front Plant Sci. 2019 Jan 25;10:15. doi: 10.3389/fpls.2019.00015. eCollection 2019.

Abstract

According to the IPCC 2014 report the Mediterranean region will be affected by strong climatic changes, both in terms of average temperature and of precipitations regime. This area hosts some half a billion people and the impact on food production will be severe. To implement a climate smart agriculture paradigm and a sustainable increase of agricultural productivity different approaches can be deployed. Agriculture alone consumes 70% of the entire water available on the planet, thus the observed reduction of useful rainfall and growing costs for irrigation water may severely constrain food security. In our work we focused on two typical Mediterranean crops: durum wheat, a rainfed crop, and tomato, an irrigated one. In wheat we explored the possibility of identifying genotypes resilient to water stress for future breeding aims, while in tomato we explored the possibility of using biostimulants to increase the plant capacity of using water. In order to achieve these targets, we used high throughput phenotyping (HTP). Two traits were considered: digital biovolume, a measure based on imaging techniques in the RGB domain, and Water Use Efficiency index as calculated semi-automatically on the basis of evaporation measurements resulting in a high throughput, non-destructive, non-invasive approach, as opposed to destructive and time consuming traditional methods. Our results clearly indicate that HTP is able to discriminate genotypes and biostimulant treatments that allow plants to use soil water more efficiently. In addition, these methods based on RGB quality images can easily be scaled to field phenotyping structure USVs or UAVs.

摘要

根据政府间气候变化专门委员会(IPCC)2014年的报告,地中海地区将受到强烈气候变化的影响,无论是在平均温度方面还是在降水模式方面。该地区居住着约5亿人口,气候变化对粮食生产的影响将是严重的。为了实施气候智能型农业模式并可持续提高农业生产力,可以采用不同的方法。仅农业就消耗了地球上全部可用水资源的70%,因此,观测到的有效降雨量减少以及灌溉用水成本的不断增加可能会严重限制粮食安全。在我们的工作中,我们聚焦于两种典型的地中海作物:硬粒小麦,一种雨养作物;以及番茄,一种灌溉作物。在小麦方面,我们探索了为未来育种目标鉴定耐水分胁迫基因型的可能性,而在番茄方面,我们探索了使用生物刺激剂来提高植物水分利用能力的可能性。为了实现这些目标,我们采用了高通量表型分析(HTP)。我们考虑了两个性状:数字生物体积,一种基于RGB域成像技术的测量方法;以及水分利用效率指数,该指数基于蒸发测量结果半自动计算得出,从而形成一种高通量、非破坏性、非侵入性的方法,这与具有破坏性且耗时的传统方法形成对比。我们的结果清楚地表明,高通量表型分析能够区分那些使植物更有效地利用土壤水分的基因型和生物刺激剂处理。此外,这些基于RGB质量图像的方法可以很容易地扩展到田间表型分析结构,如无人地面车辆(USV)或无人机(UAV)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6698/6355677/5f774ba0f3a5/fpls-10-00015-g001.jpg

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