High-throughput field phenotyping of soybean: Spotting an ideotype

Roth, Lukas; Barendregt, Christoph; Bétrix, Claude‐Alain; Hund, Andreas; Walter, Achim

doi:10.1016/j.rse.2021.112797

Cited by 36 publications

(28 citation statements)

References 46 publications

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“…Alternatively, one could also select for a delayed development of apparent leaf area (t dLA max ) to increase protein content (Figure 8b). Interestingly, a similar ideotype was proposed based on growth dynamics' HTFP traits in soybean (Roth et al, 2022a). Nevertheless, delaying canopy development in the late season requires special care:…”

Section: Formulating An Ideotypementioning

confidence: 90%

“…In a recent study, we demonstrated that monitoring soybean METs with high-throughput field phenotyping (HTFP) can reveal strong relations between secondary traits and target traits, allowing to formulate an ideotypes concept (Roth et al, 2022a). Now, this knowledge is transferred to winter wheat ( Triticum aestivum L.), while additionally including overall performance and stability considerations.…”

Section: Introductionmentioning

confidence: 99%

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Image-based phenomic prediction can provide valuable decision support in wheat breeding

Roth

Fossati

Krähenbühl³

et al. 2022

Preprint

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Traditionally, breeders' selection decisions in early generations are largely based on visual observations in the field. With the advent of affordable genome sequencing and high-throughput phenotyping technologies, enhancing breeders' ratings with such information became attractive. In this research, it is hypothesized that GxE interactions of secondary traits (i.e., growth dynamics' traits) are less complex than those of related target traits (e.g., yield). Thus, phenomic selection (PS) may allow selecting for genotypes with beneficial response-pattern in a defined population of environments. A set of 45 winter wheat varieties was grown at five year-sites and analyzed with linear and factor-analytic (FA) mixed models to estimate GxE interactions of secondary and target traits. The dynamic development of drone-derived plant height, leaf area and tiller density estimations was used to estimate the timing of key stages, quantities at defined time points, and temperature dose-response curve parameters. Most of these secondary traits and grain protein content showed little GxE interactions. In contrast, the modeling of GxE for yield required a FA model with two factors. A trained PS model predicted overall yield performance, yield stability and grain protein content with correlations of 0.41, 0.22 and 0.34. While these accuracies are modest and do not outperform well-trained GS models, PS additionally provided insights into the physiological basis of target traits. An ideotype was identified that potentially avoids the negative pleiotropic effects between yield and protein content.

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Section: Formulating An Ideotypementioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Image-based phenomic prediction can provide valuable decision support in wheat breeding

Roth

Fossati

Krähenbühl³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…These methods provide precise insight into the physiological state of plants under specific environmental conditions, excellently detect morphological and biochemical changes such as light utilization by the photosystem II (PSII) and the underlying biochemical processes, leaf pigment content, chemical composition of leaves, morphological and architectural features of leaves and shoots, etc., and enable rapid data collection and processing [90,91]. HTP enables objective, fast and precise quantification of morphological, anatomical, physiological and biochemical properties of plants and modeling of ideotypes of agricultural crops adapted to growing in specific agroecological conditions [92]. By growing plants in controlled conditions of growth chambers that enable the management and control of environmental factors such as temperature, duration, spectral composition and intensity of light, availability of nutrients and water, in combination with the latest available methods of spectral analysis (VIS, NIR, IR), chlorophyll fluorescence and measurements of gas exchange, the phenotypic properties of plants, i.e.…”

Section: Phenotypingmentioning

confidence: 99%

New Age of Common Bean

Vidak¹,

Lazarević²,

Gunjača³

et al. 2023

Production and Utilization of Legumes - Progress and Prospects

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Common bean (Phaseolus vulgaris L.) is a plant with high nutritional value that occupies an important place in human nutrition worldwide. Its yields vary widely and are often below the genetic potential of the species, given the diversity of cropping systems and climatic changes. Common bean landraces are a source of great genetic variability and provide excellent material for the selection and improvement of numerous agronomic traits and the creation of modern cultivars. It is also important to use high quality seed of high-yielding cultivars in production, because in common bean, in addition to yield and resistance to abiotic and biotic stress factors, traits such as nutritional value and digestibility are also the focus of interest. The success of common bean production depends to a large extent on the quality of the seed, the production approach and new breeding programs.

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“…Several high-throughput phenotyping approaches have been developed to bridge the genotyping and phenotyping gap for various quality traits, including protein content [ 237 , 238 , 239 ]. Advances in high-throughput non-destructive phenotyping approaches such as hyperspectral technologies, near-infrared reflectance spectroscopy, and nuclear magnetic resonance have enabled the phenotyping of various biochemical attributes in cereal and legume seeds, including protein content, with high accuracy and efficiency [ 237 , 238 , 239 , 240 , 241 ]. For example, Raman spectroscopy has been used to measure SPC in soybean [ 237 ].…”

Section: Non-destructive Phenomics Approach For Quantifying High Prot...mentioning

confidence: 99%

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools

Jha

Nayyar

Parida

et al. 2022

IJMS

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Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based ‘dietary protein’ biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.

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High-throughput field phenotyping of soybean: Spotting an ideotype

Cited by 36 publications

References 46 publications

Image-based phenomic prediction can provide valuable decision support in wheat breeding

Image-based phenomic prediction can provide valuable decision support in wheat breeding

New Age of Common Bean

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools

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