Void space inside the developing seed of <i><scp>B</scp>rassica napus</i> and the modelling of its function

Verboven, Pieter; Herremans, Els; Borisjuk, Ljudmilla; Helfen, Lukas; Ho, Quang Tri; Tschiersch, Henning; Fuchs, Johannes; Nicolaı̈, Bart; Rolletschek, Hardy

doi:10.1111/nph.12342

Cited by 50 publications

(57 citation statements)

References 59 publications

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“…Another prediction of the FBA model was that the outer cotyledon switches from net oxygen uptake to release at a light intensity above ;920 µmol quanta m 22 s 21 (while the inner cotyledon remains as a net oxygen consumer irrespective of the incident light level). Thus, the embryo's photosynthetic activity has a considerable effect on the seed's oxygen balance, in particular, helping it to avoid the onset of hypoxia, which is inimical to seed metabolism (Verboven et al, 2013).…”

Section: Metabolic Modeling Highlights the Tissue Specificity Of The mentioning

confidence: 99%

Seed Architecture Shapes Embryo Metabolism in Oilseed Rape

et al. 2013

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Constrained to develop within the seed, the plant embryo must adapt its shape and size to fit the space available. Here, we demonstrate how this adjustment shapes metabolism of photosynthetic embryo. Noninvasive NMR-based imaging of the developing oilseed rape (Brassica napus) seed illustrates that, following embryo bending, gradients in lipid concentration became established. These were correlated with the local photosynthetic electron transport rate and the accumulation of storage products. Experimentally induced changes in embryo morphology and/or light supply altered these gradients and were accompanied by alterations in both proteome and metabolome. Tissue-specific metabolic models predicted that the outer cotyledon and hypocotyl/radicle generate the bulk of plastidic reductant/ATP via photosynthesis, while the inner cotyledon, being enclosed by the outer cotyledon, is forced to grow essentially heterotrophically. Under field-relevant highlight conditions, major contribution of the ribulose-1,5-bisphosphate carboxylase/oxygenase-bypass to seed storage metabolism is predicted for the outer cotyledon and the hypocotyl/radicle only. Differences between in vitro-versus in planta-grown embryos suggest that metabolic heterogeneity of embryo is not observable by in vitro approaches. We conclude that in vivo metabolic fluxes are locally regulated and connected to seed architecture, driving the embryo toward an efficient use of available light and space.

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Section: Metabolic Modeling Highlights the Tissue Specificity Of The mentioning

confidence: 99%

Seed Architecture Shapes Embryo Metabolism in Oilseed Rape

et al. 2013

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“…Seed density is a rather complex trait because different seed parts, such as seed coat (Alonso-Blanco et al, 1999;Young et al, 2007), lipid content in the endosperm , or void space inside a seed (Verboven et al, 2013) may contribute differently. Air space in seeds may mask different oil contents, as reported for rapeseed by measuring the commonly applied seed buoyant density (Young et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

“…5, option 6), however, would need only pick and place, which is much faster. To monitor different traits of interest beyond morphological ones, additional sensors could be implemented: near-infrared spectroscopy to analyze the chemical content of seeds (Agelet and Hurburgh, 2014); chlorophyll fluorescence to score seed maturity and performance (Jalink et al, 1998); spectral imaging to classify common wheat (Triticum aestivum) and durum wheat (Triticum durum; Benoit et al, 2016); low-field NMR to measure both solid and liquid parts of a seed, as demonstrated for growing bean (Phaseolus vulgaris) pods (Windt and Blümler, 2015), or chemical components, such as lipids, carbohydrates, and proteins (Rolletschek et al, 2015); or x-ray CT to image internal seed structures, allowing, for example, the detection of internal defects of seeds (Stuppy et al, 2003;Belin et al, 2011;Yamauchi et al, 2012;Verboven et al, 2013). Further developments of phenoSeeder can be followed at www.phenoseeder.de.…”

Section: Discussionmentioning

confidence: 99%

phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds

et al. 2016

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The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently roundshaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality.

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“…As there are no noninvasive measurement techniques available for monitoring respiratory gas concentrations in fruit during CA storage, gas transport models have been used to evaluate gas transport and respiratory gaseous exchange of fruit. We have previously developed models operating at different spatial scales, from the macroscale (Ho et al, 2011Lammertyn et al, 2003;Mannapperuma et al, 1991;Verboven et al, 2013) to the microscale level (Ho et al, 2011(Ho et al, , 2009Verboven et al, 2013Verboven et al, , 2012 in a multiscale framework and validated them successfully for different apple and pear fruit cultivars (Ho et al, 2010b. Such modelling has shown that the local gas concentrations and the respiration rate inside fruit differs between cultivars, due to differences in diffusion and respiration properties, shape and size.…”

Section: Introductionmentioning

confidence: 97%

Stochastic modelling for virtual engineering of controlled atmosphere storage of fruit

Rogge

Verboven

et al. 2016

Journal of Food Engineering

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a b s t r a c tLong term storage of pear fruit requires low temperature and conventionally uses controlled atmosphere (CA) conditions to reduce respiration and consequent quality loss. Sub-optimal storage conditions may lead to physiological disorders and loss of product. Stochastic variability of the properties of fruit introduces uncertainty in storage design and operations and could result in severe quality loss. Taking such variability into account in simulation models for virtual engineering will allow to assess the uncertainty of the process and determine confidence limits for the operation. Gas exchange in pear fruit during controlled atmosphere storage was studied using a continuum diffusion-respiration model, taking into account stochastic variation of the 3D morphology, the diffusivity of oxygen and carbon dioxide and the maximal respiration rate. Different geometries were generated using a statistical shape generation algorithm for 3D morphology, that was automatically incorporated into the gas exchange model. Similarly, tissue diffusivity was computed using a 3D tissue microstructure database. Simulation results showed that internal O 2 and CO 2 gas profiles in fruit were highly affected by variation of diffusivities, maximal respiration rate and the 3D morphology of fruit. The model was further used to evaluate incidence to fermentation at different reduced O 2 levels of storage condition. The risk of fermentation inside the fruit predicted by the gas exchange model rapidly increased in response to decreasing external O 2 levels. The virtual simulation tool confirms that picking time and fruit size are important criteria for proper control of CA storage. While applied here to pear fruit, it can easily be extended to other commodities.

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Void space inside the developing seed of Brassica napus and the modelling of its function

Cited by 50 publications

References 59 publications

Seed Architecture Shapes Embryo Metabolism in Oilseed Rape

Seed Architecture Shapes Embryo Metabolism in Oilseed Rape

phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds

Stochastic modelling for virtual engineering of controlled atmosphere storage of fruit

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