Plant Phenotyping

Abstract

Every plant science experiment starts with a design that will be adapted to answer a specific biological question and involves evaluation of phenotypic traits. Plant phenotyping has advanced from manual measurements of physiologically relevant parameters to high‐throughput phenotyping platforms that use robotics and imaging sensors. Yet, this game‐changing technology has its own challenges, namely data analysis and interpretation. The improved quality of the sensors used in the phenotying experiment provides increased understanding, however the insight provided on the research question is limited by the experimental design. Aspects such as replication or spatial variability are important to consider when designing the experiment conducted in highly controlled environment as well as under field conditions. With wider availability of cameras and other sensors, we are able to record increasing number of plant traits. This results in the phenotypic bottleneck moving from data acquisition to data analysis. Throughout this article, we present practical considerations and potential shortcomings of phenotyping systems and suggest some solutions to the challenges of plant phenotyping through streamlined and reproducible data analysis pipelines. Key Concepts Plant phenotypes are complex, resulting from the interaction between genotype and environment. The phenotype can be divided into traits, for example, biomass can be dissected into leaf area, branches/tillers, fruits. The relationship between traits depends on the environment, genotype and treatment. Each phenotyping method is optimised to answer a specific research question. Exploring the relationships between phenotypes and their changes across genotypes/treatments increases our understanding of the underlying physiological processes. Experimental design should include an optimal number of replicates and sample randomisation to ensure a successful interpretation of phenotypic results. Phenotyping results require detailed statistical analysis to be adequately interpreted.

Genetic mapping of the early responses to salt stress inArabidopsis thaliana

“…More recently, salinity studies have begun investigating new traits that can potentially contribute to salinity tolerance (Morton et al ., 2019; Negrão et al ., 2017; Zelm et al ., 2020), including stress signalling pathways (Choi et al ., 2014; Evans et al ., 2016), cell wall remodelling (Feng et al ., 2018), transpiration‐use efficiency (Al‐Tamimi et al ., 2016) and root system architecture (Julkowska et al ., 2017), thus breaking down salinity tolerance into more genetically tractable components (Morton et al ., 2019). The non‐destructive methods developed in high‐throughput phenotyping allowed the recording of more sophisticated traits (Awlia et al ., 2016), providing the simultaneous and multifaceted understanding of plant size, architecture and photosynthetic efficiency during plant development and in response to environmental cues (Negrão and Julkowska, 2020). In this study, the focus was on exploring the natural variation in the early responses to salt stress by applying high‐throughput phenotyping protocols and GWAS on the Arabidopsis thaliana mapping population.…”

Genetic mapping of the early responses to salt stress inArabidopsis thaliana

“…More recently, salinity studies have begun investigating new traits that can potentially contribute to salinity tolerance (Negrao et al, 2017, Morton et al, 2019, van Zelm et al, 2020, including stress signaling pathways (Choi et al, 2014;Evans et al, 2016), cell wall remodeling (Feng et al, 2018), transpiration use efficiency (Al-Tamimi et al, 2016) and root system architecture (Julkowska et al, 2017), thus, breaking down salinity tolerance into more genetically tractable components (Morton et al, 2019). The non-destructive methods developed in highthroughput phenotyping allowed the recording of more sophisticated traits (Awlia et al, 2016), providing simultaneous and multifaceted understanding of plant size, architecture and photosynthetic efficiency during plant development and in response to environmental cues (Negrão and Julkowska, 2020). In this study, we used high-throughput phenotyping to enable indepth GWAS and have identified over 1,000 unique SNPs that were associated with the responses of Arabidopsis to salt stress ( Table S3, Table S4).…”

Capturing crop adaptation to abiotic stress using image-based technologies

“…royalsocietypublishing.org/journal/rsob Open Biol. 12: 210353 measurement of traits such as shoot and root length, fresh and dry mass as well as yield components such as number of productive tillers or branches, fruit or grain weight etc [7,18]. Destructive phenotyping entails no highly specialized nor expensive equipment.…”

“…Breeders heavily rely on phenotyping, using large number of genotypes and targeting the collective study of multiple traits simultaneously under a given condition. The challenge rests on breeding for yield and other traits, such as stress tolerance, using the most adequate phenotyping strategy for the trait of interest among a plethora of available phenotyping strategies (as reviewed by [18,71]). High-throughput phenotyping (HTP) aims to characterize the full set of phenotypes by non-destructively, capturing plant traits and integrating biology with computers and robotics (as reviewed by [15,72,73]).…”

“…This is the reason why many researchers are now using image-based technologies to improve the process of phenotyping. Image data paired with accurate high resolution environmental data provides information on the environment-genotype relationship in detail never before accessible [18]. Yet, the use of HTP in large-scale breeding programmes or to assist genomic selection is relatively new and full of challenges [71,86,87].…”