Soil carbon dioxide venting through rice roots

Kirk, G. J. D.; Boghi, Andrea; Affholder, Marie-Cécile; Keyes, Samuel D.; Heppell, James; Roose, Tiina

doi:10.1111/pce.13638

Cited by 22 publications

(23 citation statements)

References 49 publications

(70 reference statements)

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“…For roots in waterlogged soil, however, in which CO 2 concentrations can be several kPa (Ponnamperuma, 1984), CO 2 can diffuse into roots (e.g. rice; Kirk et al, 2019). The present data on tissue CO 2 concentrations within roots show, as expected owing to CO 2 production in respiration and ethanolic fermentation, that CO 2 is substantially higher within the roots than in the external medium.…”

Section: Discussionsupporting

confidence: 45%

“…For roots in waterlogged soil, however, in which CO 2 concentrations can be several kPa (Ponnamperuma, ), CO 2 can diffuse into roots (e.g. rice; Kirk et al , ).…”

Section: Discussionmentioning

confidence: 99%

“…As CO 2 is produced during respiration and also in ethanolic fermentation, roots are a source of CO 2 which will diffuse out radially when the external concentration is lower, although in waterlogged soils CO 2 can be high and it can diffuse into roots (e.g. Kirk et al , ). To date, data on presumed CO 2 gradients across roots and the DBL have not been available, as such measurements with high spatial resolution would require a CO 2 ‐specific microsensor.…”

Section: Introductionmentioning

confidence: 99%

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Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

et al. 2020

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Summary Roots in flooded soils experience hypoxia, with the least O2 in the vascular cylinder. Gradients in CO2 across roots had not previously been measured. The respiratory quotient (RQ; CO2 produced : O2 consumed) is expected to increase as O2 availability declines. A new CO2 microsensor and an O2 microsensor were used to measure profiles across roots of chickpea seedlings in aerated or hypoxic conditions. Simultaneous, nondestructive flux measurements of O2 consumption, CO2 production, and thus RQ, were taken for roots with declining O2. Radial profiling revealed severe hypoxia and c. 0.8 kPa CO2 within the root vascular cylinder. The distance penetrated by O2 into the roots was shorter at lower O2. The gradient in CO2 was in the opposite direction to that of O2, across the roots and diffusive boundary layer. RQ increased as external O2 was lowered. For chickpea roots in solution at air equilibrium, O2 was very low and CO2 was elevated within the vascular cylinder; the extent of the severely hypoxic core increased as external O2 was reduced. The increased RQ in roots in response to declining external O2 highlighted the shift from respiration to ethanolic fermentation as the severely hypoxic/anoxic core became a progressively greater proportion of the root tissues.

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Section: Discussionsupporting

confidence: 45%

“…For roots in waterlogged soil, however, in which CO 2 concentrations can be several kPa (Ponnamperuma, ), CO 2 can diffuse into roots (e.g. rice; Kirk et al , ).…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

et al. 2020

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“…To harden the X-ray beam, a 1.0 mm Cu filter was used. Recent studies on rice roots that involved X-ray CT have been listed in Table 2 [39][40][41][42][43][44][45]. Review of these studies indicated that most studies used pots with diameter < 100 mm and required scanning times of > 1 h. This indicated that our developed process flow is suitable for 4-D RSA phenotyping, when applied to rice showing relatively large RSAs.…”

Section: Discussionmentioning

confidence: 99%

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

et al. 2020

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Background: X-ray computed tomography (CT) allows us to visualize root system architecture (RSA) beneath the soil, non-destructively and in a three-dimensional (3-D) form. However, CT scanning, reconstruction processes, and root isolation from X-ray CT volumes, take considerable time. For genetic analyses, such as quantitative trait locus mapping, which require a large population size, a high-throughput RSA visualization method is required. Results: We have developed a high-throughput process flow for the 3-D visualization of rice (Oryza sativa) RSA (consisting of radicle and crown roots), using X-ray CT. The process flow includes use of a uniform particle size, calcined clay to reduce the possibility of visualizing non-root segments, use of a higher tube voltage and current in the X-ray CT scanning to increase root-to-soil contrast, and use of a 3-D median filter and edge detection algorithm to isolate root segments. Using high-performance computing technology, this analysis flow requires only 10 min (33 s, if a rough image is acceptable) for CT scanning and reconstruction, and 2 min for image processing, to visualize rice RSA. This reduced time allowed us to conduct the genetic analysis associated with 3-D RSA phenotyping. In 2-weekold seedlings, 85% and 100% of radicle and crown roots were detected, when 16 cm and 20 cm diameter pots were used, respectively. The X-ray dose per scan was estimated at < 0.09 Gy, which did not impede rice growth. Using the developed process flow, we were able to follow daily RSA development, i.e., 4-D RSA development, of an upland rice variety, over 3 weeks. Conclusions: We developed a high-throughput process flow for 3-D rice RSA visualization by X-ray CT. The X-ray dose assay on plant growth has shown that this methodology could be applicable for 4-D RSA phenotyping. We named the RSA visualization method 'RSAvis3D' and are confident that it represents a potentially efficient application for 3-D RSA phenotyping of various plant species.

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“…To harden the X-ray beam, a 1.0 mm Cu filter was used. Recent studies on rice roots that involved X-ray CT have been listed in Table 2 [40,41,42,43,44,45,46]. Review of these studies indicated that most studies used pots with diameter < 100 mm and required scanning times of > one h. This indicated that our developed process flow is suitable for 4-D RSA phenotyping, when applied to rice showing relatively large RSAs.…”

Section: Discussionmentioning

confidence: 99%

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

Teramoto¹,

Takayasu²,

Kitomi³

et al. 2020

Preprint

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Background: X-ray computed tomography (CT) allows us to visualize root system architecture (RSA) beneath the soil, non-destructively and in a three-dimensional (3-D) form. However, CT scanning, reconstruction processes, and root isolation from X-ray CT volumes, take considerable time. For genetic analyses, such as quantitative trait locus mapping, which require a large population size, a high-throughput RSA visualization method is required.Results: We have developed a high-throughput process flow for the 3-D visualization of rice (Oryza sativa) RSA (consisting of radicle and crown roots), using X-ray CT. The process flow includes use of a uniform particle size, calcined clay to reduce the possibility of visualizing non-root segments, use of a higher tube voltage and current in the X-ray CT scanning to increase root-to-soil contrast, and use of a 3-D median filter and edge detection algorithm to isolate root segments. Using high-performance computing technology, this analysis flow requires only 10 min (33 s, if a rough image is acceptable) for CT scanning and reconstruction, and 2 min for image processing, to visualize rice RSA. This reduced time allowed us to conduct the genetic analysis associated with 3-D RSA phenotyping. In 2-week-old seedlings, 85% and 100% of radicle and crown roots were detected, when 16 cm and 20 cm diameter pots were used, respectively. The X-ray dose per scan was estimated at < 0.09 Gy, which did not impede rice growth. Using the developed process flow, we were able to follow daily RSA development, i.e., 4-D RSA development, of an upland rice variety, over three weeks. Conclusions: We developed a high-throughput process flow for 3-D rice RSA visualization by X-ray CT. The X-ray dose assay on plant growth has shown that this methodology could be applicable for 4-D RSA phenotyping. We named the RSA visualization method ‘RSAvis3D’ and are confident that it represents a potentially efficient application for 3-D RSA phenotyping of various plant species.

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Soil carbon dioxide venting through rice roots

Cited by 22 publications

References 49 publications

Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

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Soil carbon dioxide venting through rice roots

Cited by 22 publications

References 49 publications

Root O2 consumption, CO2 production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

Root O2 consumption, CO2 production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

Contact Info

Product

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Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia

Root O₂ consumption, CO₂ production and tissue concentration profiles in chickpea, as influenced by environmental hypoxia