The advantages of functional phenotyping in pre-field screening for drought-tolerant crops

Boaz Negin, Menachem Moshelion*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

58 Scopus citations


Increasing worldwide demand for food, feed and fuel presents a challenge in light of limited resources and climatic challenges. Breeding for stress tolerance and drought tolerance, in particular, is one the most challenging tasks facing breeders. The comparative screening of immense numbers of plant and gene candidates and their interactions with the environment represents a major bottleneck in this process. We suggest four key components to be considered in pre-field screens (phenotyping) for complex traits under drought conditions: (i) where, when and under which conditions to phenotype; (ii) which traits to phenotype; (iii) how to phenotype (which method); and (iv) how to translate collected data into knowledge that can be used to make practical decisions. We describe some common pitfalls, including inadequate phenotyping methods, incorrect terminology and the inappropriate use of non-relevant traits as markers for drought tolerance. We also suggest the use of more non-imaging, physiology-based, high-throughput phenotyping systems, which, used in combination with soil-plant-atmosphere continuum (SPAC) measurements and fitting models of plant responses to continuous and fluctuating environmental conditions, should be further investigated in order to serve as a phenotyping tool to better understand and characterise plant stress response. In the future, we assume that many of today's phenotyping challenges will be solved by technology and automation, leaving us with the main challenge of translating large amounts of accumulated data into meaningful knowledge and decision making tools.

Original languageAmerican English
Pages (from-to)107-118
Number of pages12
JournalFunctional Plant Biology
Issue number1
StatePublished - 2017

Bibliographical note

Publisher Copyright:
© CSIRO 2017.


  • drought stress
  • drought tolerance
  • modeling
  • modelling
  • screening
  • stress physiology


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