Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Lyra, Danilo Hottis; Virlet, Nicolas; Sadeghi‐Tehran, Pouria; Hassall, Kirsty L.; Wingen, Luzie U.; Orford, Simon; Griffiths, Simon; Hawkesford, Malcolm J.; Slavov, Gancho

doi:10.1093/jxb/erz545

Cited by 31 publications

(27 citation statements)

References 98 publications

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“…Plant growth and health parameters are extracted from the collected images ( Sadeghi-Tehran et al., 2017 ; Virlet et al., 2017 ; Sadeghi-Tehran et al., 2019 ). Detailed datasets can reveal hitherto unrecognized information concerning the genetic control of performance revealed at different developmental stages ( Lyra et al., 2020 ). Similar datasets can be obtained from drone-based platforms which are able to cover larger trials at multiple sites, but require greater manual inputs for collection ( Holman et al., 2016 ; Holman et al., 2019 ).…”

Section: Prospects: Research Gaps and Using Automated Phenotyping Formentioning

confidence: 99%

Impacts of G x E x M on Nitrogen Use Efficiency in Wheat and Future Prospects

Hawkesford

Riche

2020

Front. Plant Sci.

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Globally it has been estimated that only one third of applied N is recovered in the harvested component of grain crops. This represents an incredible waste of resource and the overuse has detrimental environmental and economic consequences. There is substantial variation in nutrient use efficiency (NUE) from region to region, between crops and in different cropping systems. As a consequence, both local and crop specific solutions will be required for NUE improvement at local as well as at national and international levels. Strategies to improve NUE will involve improvements to germplasm and optimized agronomy adapted to climate and location. Essential to effective solutions will be an understanding of genetics (G), environment (E), and management (M) and their interactions (G x E x M). Implementing appropriate solutions will require agronomic management, attention to environmental factors and improved varieties, optimized for current and future climate scenarios. As NUE is a complex trait with many contributing processes, identifying the correct trait for improvement is not trivial. Key processes include nitrogen capture (uptake efficiency), utilization efficiency (closely related to yield), partitioning (harvest index: biochemical and organ-specific) and trade-offs between yield and quality aspects (grain nitrogen content), as well as interactions with capture and utilization of other nutrients. A long-term experiment, the Broadbalk experiment at Rothamsted, highlights many factors influencing yield and nitrogen utilization in wheat over the last 175 years, particularly management and yearly variation. A more recent series of trials conducted over the past 16 years has focused on separating the key physiological sub-traits of NUE, highlighting both genetic and seasonal variation. This perspective describes these two contrasting studies which indicate G x E x M interactions involved in nitrogen utilization and summarizes prospects for the future including the utilization of high throughput phenotyping technology.

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Section: Prospects: Research Gaps and Using Automated Phenotyping Formentioning

confidence: 99%

Impacts of G x E x M on Nitrogen Use Efficiency in Wheat and Future Prospects

Hawkesford

Riche

2020

Front. Plant Sci.

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“…Unfortunately, though it can sample continuously, 24 h per day, but no two sensors can collect images simultaneously. Then, Field Scanalyzer also was used to determine wheat canopy height and further validate the potential of functional mapping analysis for detecting persistent quantitative trait loci (QTLs) (Lyra et al, 2020 ).…”

Section: Ht3p For Field Phenotyping In Notoriously Heterogeneous Condmentioning

confidence: 99%

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Quan

Song

et al. 2021

Front. Bioeng. Biotechnol.

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Food scarcity, population growth, and global climate change have propelled crop yield growth driven by high-throughput phenotyping into the era of big data. However, access to large-scale phenotypic data has now become a critical barrier that phenomics urgently must overcome. Fortunately, the high-throughput plant phenotyping platform (HT3P), employing advanced sensors and data collection systems, can take full advantage of non-destructive and high-throughput methods to monitor, quantify, and evaluate specific phenotypes for large-scale agricultural experiments, and it can effectively perform phenotypic tasks that traditional phenotyping could not do. In this way, HT3Ps are novel and powerful tools, for which various commercial, customized, and even self-developed ones have been recently introduced in rising numbers. Here, we review these HT3Ps in nearly 7 years from greenhouses and growth chambers to the field, and from ground-based proximal phenotyping to aerial large-scale remote sensing. Platform configurations, novelties, operating modes, current developments, as well the strengths and weaknesses of diverse types of HT3Ps are thoroughly and clearly described. Then, miscellaneous combinations of HT3Ps for comparative validation and comprehensive analysis are systematically present, for the first time. Finally, we consider current phenotypic challenges and provide fresh perspectives on future development trends of HT3Ps. This review aims to provide ideas, thoughts, and insights for the optimal selection, exploitation, and utilization of HT3Ps, and thereby pave the way to break through current phenotyping bottlenecks in botany.

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“…Not only remote phenotyping but also other methods were used in GS of wheat. For example, a robotic field phenotyping platform measured plant height [100]. In another study, grain yield was assessed from spectral reflectance data collected with a handheld multiple spectral radiometer [101].…”

Section: High-throughput Phenotypingmentioning

confidence: 99%

Genomic Selection for Forest Tree Improvement: Methods, Achievements and Perspectives

Lebedev

Лебедева

Chernodubov

et al. 2020

Forests

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The breeding of forest trees is only a few decades old, and is a much more complicated, longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle for forest trees can take 20–30 years. Recent advances in genomics and molecular biology have revolutionized traditional plant breeding based on visual phenotype assessment: the development of different types of molecular markers has made genotype selection possible. Marker-assisted breeding can significantly accelerate the breeding process, but this method has not been shown to be effective for selection of complex traits on forest trees. This new method of genomic selection is based on the analysis of all effects of quantitative trait loci (QTLs) using a large number of molecular markers distributed throughout the genome, which makes it possible to assess the genomic estimated breeding value (GEBV) of an individual. This approach is expected to be much more efficient for forest tree improvement than traditional breeding. Here, we review the current state of the art in the application of genomic selection in forest tree breeding and discuss different methods of genotyping and phenotyping. We also compare the accuracies of genomic prediction models and highlight the importance of a prior cost-benefit analysis before implementing genomic selection. Perspectives for the further development of this approach in forest breeding are also discussed: expanding the range of species and the list of valuable traits, the application of high-throughput phenotyping methods, and the possibility of using epigenetic variance to improve of forest trees.

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Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Cited by 31 publications

References 98 publications

Impacts of G x E x M on Nitrogen Use Efficiency in Wheat and Future Prospects

Impacts of G x E x M on Nitrogen Use Efficiency in Wheat and Future Prospects

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Genomic Selection for Forest Tree Improvement: Methods, Achievements and Perspectives

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