A rapid, controlled-environment seedling root screen for wheat correlates well with rooting depths at vegetative, but not reproductive, stages at two field sites

Watt, Michelle; Moosavi, Seyed Amir; Cunningham, Shaun Cameron; Kirkegaard, John A.; Rebetzke, G. J.; Richards, Richard A.

doi:10.1093/aob/mct122

Cited by 156 publications

(150 citation statements)

References 41 publications

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“…When the root growth of vigorous and non-vigorous wheat genotypes was compared in rhizoboxes by Liao, Palta and Fillery [12], visual differences in root length and proliferation from the one-leaf stage (10 DAS) were monitored, but it was not until the onset of stem elongation (30 DAS) that significant differences occurred. These findings not only reflect the plasticity of the wheat root system when different cultivars are grown under different conditions [2,15,[38][39][40][41][42][43], but uncover the perils of conducting early-stage root phenotyping in wheat [44,45]. Despite the high plasticity of the root system, wheat cultivars, when grown in the field or in rhizoboxes, maintained a similar ranking in root biomass and root length density under well-watered and moderate water deficit conditions [1,46].…”

Section: Characterising the Root Systems Of Cultivars With Contrastinmentioning

confidence: 80%

Characterization of Root and Shoot Traits in Wheat Cultivars with Putative Differences in Root System Size

et al. 2018

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Abstract:Root system size is a key trait for improving water and nitrogen uptake efficiency in wheat (Triticum aestivum L.). This study aimed (i) to characterize the root system and shoot traits of five wheat cultivars with apparent differences in root system size; (ii) to evaluate whether the apparent differences in root system size observed at early vegetative stages in a previous semi-hydroponic phenotyping experiment are reflected at later phenological stages in plants grown in soil using large rhizoboxes. The five wheat cultivars were grown in a glasshouse in rhizoboxes filled to 1.0 m with field soil. Phenology and shoot traits were measured and root growth and proliferation were mapped to quantify root length density (RLD), root length per plant, root biomass and specific root length (SRL). Wheat cultivars with large root systems had greater root length, more root biomass and thicker roots, particularly in the top 40 cm, than those with small root systems. Cultivars that reached anthesis later had larger root system sizes than those that reached anthesis earlier. Later anthesis allowed more time for root growth and proliferation. Cultivars with large root systems had 25% more leaf area and biomass than those with small root systems, which presumably reflects high canopy photosynthesis to supply the demand for carbon assimilates to roots. Wheat cultivars with contrasting root system sizes at the onset of tillering (Z2.1) in a semi-hydroponic phenotyping system maintained their size ranking at booting (Z4.5) when grown in soil. Phenology, particularly time to anthesis, was associated with root system size.

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Section: Characterising the Root Systems Of Cultivars With Contrastinmentioning

confidence: 80%

Characterization of Root and Shoot Traits in Wheat Cultivars with Putative Differences in Root System Size

et al. 2018

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“…Although there are examples in which the early stage root phenotype has predictive value for later developmental stages (Tuberosa et al, 2002), the seedling root phenotype may not always be representative of the mature plant (Watt et al, 2013). Because replicate numbers from manual phenotyping of mature root systems are limited but mature root systems often have a higher complexity, adapted statistical methods need to be developed to make full use of data sets.…”

Section: Discussionmentioning

confidence: 99%

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

2016

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Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding – especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5) – Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0–5 cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars.

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“…It is thus evident that each system has its advantages for certain specific applications. Previously, the cultivation of roots on germination paper was used in the form of paper-roll setup (Watt et al 2013) or growth pouches (Hund et al 2009). These studies showed a good correlation with the length of the roots under field conditions in the early stages of growth, but not in the reproductive stage (Watt et al 2013).…”

Section: Resultsmentioning

confidence: 99%

“…Previously, the cultivation of roots on germination paper was used in the form of paper-roll setup (Watt et al 2013) or growth pouches (Hund et al 2009). These studies showed a good correlation with the length of the roots under field conditions in the early stages of growth, but not in the reproductive stage (Watt et al 2013). The length of filter paper in our study was 60 cm, but in principle, an almost unlimited extension is possible as both black filter paper and PVC-P foil are available in rolls.…”

Section: Resultsmentioning

confidence: 99%

Two-dimensional root phenotyping system based on root growth on black filter paper and recirculation micro-irrigation

Rattanapichai¹,

Klem²

2016

Czech J. Genet. Plant Breed.

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Rattanapichai W., Klem K. (2016): Two-dimensional root phenotyping system based on root growth on black filter paper and recirculation micro-irrigation. Czech J. Genet. Plant Breed., 52: 64-70.Plant root system architecture (RSA) has an important role in crop production, particularly for water and nutrient uptake under limiting conditions. In the last few years, several root phenotyping methods have been developed. Here we present a new technique which has been developed for non-destructive, inexpensive and high-throughput root growth studies and RSA analyses. To illustrate the potential applications, this method was tested in an experiment with nitrogen and phosphorous deficiencies in a nutrient solution, affecting RSA parameters of two spring barley varieties (Bojos and Barke). This technique is based on root growth on vertically positioned black filter paper (30 × 60 cm) placed between two black plastic (PVC-P) foils and micro-irrigation systems providing the recirculation of nutrient solution. The pre-germinated seeds were placed in the slit between two plastic bars which carry the filter paper and plastic sheets and fix the plant in the vertical position. This system allows easy repeated non-invasive access to roots for their measuring and sampling. Eighteen days after transplanting the root imaging was done using an RGB digital camera. To evaluate the root architecture parameters the "SmartRoot" software was used. The results revealed that the system is able to detect changes in RSA which are caused mainly by P deficiency (particularly changes in lateral root length and total root area). It can be concluded that this technique has a great potential for non-destructive root growth studies, RSA measurement and root sampling.

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A rapid, controlled-environment seedling root screen for wheat correlates well with rooting depths at vegetative, but not reproductive, stages at two field sites

Cited by 156 publications

References 41 publications

Characterization of Root and Shoot Traits in Wheat Cultivars with Putative Differences in Root System Size

Characterization of Root and Shoot Traits in Wheat Cultivars with Putative Differences in Root System Size

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

Two-dimensional root phenotyping system based on root growth on black filter paper and recirculation micro-irrigation

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