Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2026 Sep 3;252(3):1035–1049. doi: 10.1111/nph.71549

Radial oxygen loss, rhizospheric methane oxidation and methane emissions from rice roots

Juan de la Cruz Jiménez 1,✉, Zhiwei Song 1,2, Marcela Pineda 3, Paula Lozano 3, Maria Camila Rebolledo 3,4, Juan A Cardoso 3, Maria F Alvarez 3, William Armstrong 5, Ole Pedersen 1,6
PMCID: PMC13628551  PMID: 42693546

Summary

  • Methane (CH4) produced in flooded paddy soils is emitted by passive diffusion, by ebullition and by diffusion through the rice (Oryza sativa) plant. Counter‐diffusing oxygen (O2) via shoot to root and rhizosphere will inhibit methanogenesis and support aerobic rhizospheric methanotrophs and heterotrophs.

  • In this study, we analyzed the anatomical, morphological and physiological traits of roots of several rice varieties and used modeling approaches to assess the potential effects on methane emissions.

  • Modeling showed that traits that enhance internal O2 diffusion: increased cortical porosity, a reduced stelar radius, lower respiratory O2 demand and subapical exodermal barriers to radial O2 loss should widen the oxygenated rhizospheres in apical regions and reduce CH4 emissions. This reduction arises because of increased rhizosphere resistance to CH4 diffusion as the methanogenic front retreats rather than increased methanotrophic CH4 consumption. Increasing methanotrophic rate per unit volume raised emissions by narrowing the oxygenated rhizosphere. Larger root radii (with stelar radius constant) increased oxygenated rhizosphere thickness and CH4 consumption, but resistance to CH4 diffusion was sufficiently reduced for CH4 emissions to increase.

  • Overall, the results challenge the widely held assumption that increased methanotrophy will inevitably reduce CH4 emissions. However, increased methanotrophy could reduce emissions where it replaces heterotrophic O2 consumption.

Keywords: gas diffusion, methanotrophy, Oryza sativa L., porosity, rhizosphere oxidation, root anatomy

Longitudinal variation in rice (Oryza sativa) root traits affecting the bidirectional diffusion of O2 and CH4.

graphic file with name NPH-252-1035-g007.webp

Introduction

Rice cultivation predominantly occurs in naturally or irrigated flooded areas. During flooding, organic matter is decomposed under anaerobic conditions by soil microorganisms, leading to the production of methane (CH4) by methanogens. Methane accumulates in the flooded soil and is eventually emitted to the atmosphere. This process can occur via (1) slow diffusion in the liquid phase of the flooded soil, (2) accumulation in bubbles that are later emitted via ebullition or (3) via the rice plants through their interconnected gas‐space systems: so‐called plant‐mediated diffusion (Jiménez & Pedersen, 2023). The latter is the primary CH4 diffusion pathway, accounting for up to 90% of total CH4 emissions (Holzapfel‐Pschorn et al., 1986; Schütz et al., 1989; Butterbach‐Bahl et al., 1997).

The root and shoot gas‐space continuum provides a low‐resistance diffusion path for O2 movement into and within the root, supporting root respiration and, unless impeded by subapical exodermal apoplastic barriers (Armstrong, 1979; Colmer, 2003a; Jiménez et al., 2021b, 2024b), supporting also some radial O2 loss (ROL) to the rhizosphere, where reductants such as reduced iron, sulfide and other potential phytotoxins can be immobilized/detoxified, and where CH4 can be ‘oxidized’ by methanotrophs (Kirk, 2004). The rhizosphere and the root itself are effectively in competition for the O2 diffusing along the root. The degree to which each is accommodated is determined by the balance between the degree and distribution of longitudinal (gas phase) and radial (liquid phase) diffusive resistances and the oxygen demands of root and rhizosphere (Armstrong & Beckett, 1987). The reverse diffusion of CH4 from the rhizosphere, to and through the root, will depend primarily on the prevailing CH4 generation activity and consumption rates and concentrations in the soil, rhizosphere O2 consumption, the radial resistances from soil to root, the radial resistances across the outer cell layers of the root (epidermis/exodermis) and longitudinal resistance in the root/shoot gas space continuum (Beckett et al., 2001).

CH4 production and oxidation have been detected in incubations of isolated root segments under specific conditions (Watanabe et al., 1997; Gilbert & Frenzel, 1998; Inubushi et al., 2002). However, the relative contributions of root tissues, root‐associated microorganisms and soil processes remain unresolved because tissue sterility was not verified in the available studies.

Analysis of the CH4 diffusion via roots is not by any means as well researched as for O2. It has been reported that root characteristics such as high porosity, low respiratory O2 consumption, smaller stele‐to‐cortex ratios and the deposition of suberin and glycerol esters in cell walls of the root exodermis contribute to an efficient internal diffusion of O2 in roots (Armstrong, 1979; Colmer, 2003a; Pedersen et al., 2021; Jiménez et al., 2024a; Jiménez & Pedersen, 2026). Information about the influence of root characteristics on CH4 diffusion is largely limited to aerenchyma (i.e. large gas spaces in roots). Some studies report lower CH4 emissions from rice plants with lower aerenchyma formation (Kim et al., 2018; Iqbal et al., 2021), whereas others report lower CH4 emissions from plants with high aerenchyma formation (Li et al., 2025). Little is published on the effects of ROL (Zheng et al., 2018; Chen et al., 2019) or on root and stele diameters on CH4 emissions from rice paddies (Roy et al., 2025a,b).

Root traits that enhance rhizosphere oxygenation might play a key role in promoting CH4 oxidation. In flooded soils, CH4 is produced by strictly anaerobic methanogenic archaea, which utilize carbon substrates derived from soil organic matter, plant residues and root exudates to generate CH4 (Conrad, 2007). A hallmark of all methanogens is the enzyme methyl coenzyme M reductase, which catalyzes both CH4 formation and its anaerobic oxidation (Scheller et al., 2010; Ragsdale et al., 2017). The methyl coenzyme M reductase is an extremely O2‐labile protein, undergoing rapid inactivation upon exposure to O2 because its active site contains the nickel(I) hydrocorphin coenzyme F‐430 as a prosthetic group. The nickel enzyme catalyzes the reversible reduction in methyl‐coenzyme M to CH4 and is one of the most O2‐sensitive enzymes known (Thauer, 2019). Consequently, root traits that enhance internal O2 diffusion within roots and promote O2 loss into flooded soil can suppress methanogenesis by expanding the oxygenated rhizosphere and shifting anaerobic CH4 production away from the root surfaces.

Methane emissions from paddy rice fields are typically measured using static chambers, which allow a quantification of CH4 fluxes over a specific period. These measurements consider the whole system, including the emissions coming from the soil or via the plant. Mathematical modeling incorporating factors such as climate, soil biochemical characteristics and rice developmental stages (including shoot characteristics and root release of carbon and O2) is commonly used to assess the contribution of major parameters to total CH4 emission (Li, 2000; Li et al., 2004; Fumoto et al., 2008; Oikawa et al., 2016). Understanding how specific root characteristics contribute to total emissions is often complicated by the simultaneous occurrence of multiple morphological and anatomical variations in roots, as well as the complex root system characteristic of rice plants. A suitable approach to help understand the potential effects of root traits on the counter‐diffusion process of O2 and CH4 through roots is the use of mathematical models for root aeration that simulate tissue distributions and embrace the longitudinal variations in root wall permeability, cortical diffusive resistance, cortical and stelar respiratory demand and radial diffusivities to gases (Armstrong & Beckett, 1987; Beckett et al., 2001).

The purpose of this study was to predict how the morphological, physiological and anatomical characteristics of rice roots influence CH4 emission and CH4 oxidation in soils. We hypothesized that root traits facilitating internal O2 diffusion and expanding the oxygenated rhizosphere would effectively reduce CH4 emissions by suppressing methanogenesis in the rhizosphere, whereas increased O2 consumption in the rhizosphere by microorganisms would diminish this oxygenated zone and enhance CH4 emissions. Root porosity, stele and root diameters, root respiration and the formation of apoplastic barriers impeding gas diffusion from six rice genotypes were quantified. Longitudinal variation in root specific traits was incorporated into a multicylinder mathematical model (Armstrong & Beckett, 1987; Beckett et al., 2001) to determine the potential influence of (1) root porosity, (2) cortex‐to‐stele ratios (CSR), (3) root respiration, (4) root apoplastic barriers, (5) root length and (6) non‐methanotrophic and methanotrophic O2 consumption in the soil on CH4 emission from the root base and rhizosphere CH4 oxidation.

Materials and Methods

Plant material and growing conditions

Seeds of six rice (Oryza sativa L.) cultivars (APO:C1, CT11891, FED68, IR64, IRAT190 and Lemont) were germinated in petri dishes with moist paper for 2 d before being transferred into 3.7‐l pots filled with nutrient solutions and continuous forced aeration. The six selected genotypes exhibited contrasting cortical porosity, root diameter, root respiration and root length and surface area (Supporting Information Table S1). These measured trait values were used to parameterize the model. Seven‐day‐old plants were further transferred into 3.7‐l pots filled with deoxygenated nutrient solutions. Nutrient solution contained the following macronutrients (mM): K+, 5.95; Ca2+, 1.5; NH4 +, 0.625; Mg2+, 0.40; Na+, 0.20; NO3−, 4.375; SO4 2−, 1.905; H2PO4 −, 0.20 and SiO2 2−, 0.10. Micronutrients were (mM): Mn2+, 0.0020; Zn2+, 0.0020; Ni2+, 0.0010; Cu2+, 0.00050; Cl−, 0.050; BO3 3−, 0.025; MoO4 2−, 0.00050; Fe‐EDTA, 0.05. pH was adjusted to 6.5. The stagnant deoxygenated solution was prepared by dissolving 0.1% (w/v) agar in the nutrient solution to prevent convection and simulate changes in gas composition as commonly occur in flooded soils (Wiengweera et al., 1997). These solutions were flushed with high purity N2 gas to purge out O2 of the solution before the plants were transferred. Plants were grown in deoxygenated stagnant solutions rather than soil to enable recovery of intact root systems with minimal damage, particularly to root apices and lateral roots, which were required for the detailed anatomical and physiological analyses (will be discussed later). Each pot contained five randomly selected plants from each genotype. The experiment was conducted in a glasshouse with natural sunlight at 30°C : 19°C, day : night air temperatures in Cali, Colombia. The experiment lasted for 5 wk, during which the plants remained in the vegetative stage. Root anatomy, morphology and respiration were assessed at a single sampling conducted at the final harvest; no intermediate root samplings were performed. Pots were organized following a completely randomized design with five replications. Pots were re‐randomized when all nutrient solutions were renewed every 7 d.

Root anatomy

One adventitious root (c. 120 mm in length) and one long‐type lateral root (c. 30‑40 mm in length) were excised from each cultivar in each pot, resulting in five replicate roots of each root type per genotype. For adventitious roots, segments of 10 mm length were taken from apical developing zones (e.g. 10 mm behind the root tip) and basal developed zones (e.g. 80 mm behind the root tip). For lateral roots, 10‐mm‐length segments were taken from mid regions (e.g. 15–25 mm behind the base). All segments were then embedded in 5% (w/v) warm agar. Cross sections (100 μm thickness) were obtained by cutting solid agar blocks using a vibrating blade microtome (Leica VT1200S, Leica Biosystems). Suberin was visualized by green–yellow fluorescence after staining cross sections with 0.01% (w/v) Fluorol Yellow 088 in polyethylene glycol glycerol for 1 h (Brundrett et al., 1991) and viewed under UV light (ECLIPSE Ci‐L, Nikon; UV1‐A filter, band pass = 365 nm, dichroic mirror = 400, barrier filter = 400). Cross sections were photographed with a DS‐Fi3 camera (Nikon, Tokyo, Japan). The root, stele and exodermal/epidermal radius, as well as the aerenchyma percentage (% gas‐filled large spaces in the root cortex) and the small intercellular spaces in each root type and at each of the two positions along the adventitious roots, were determined using white light images and the ImageJ software (National Institutes of Health, Bethesda, USA). The cortical porosity due to the small intercellular air spaces in non‐aerenchymatous regions (e.g. root tip) were calculated based on the point of contact and uniformity of shapes displayed by cells arranged in a cubic geometry as described by Justin & Armstrong (1987). One cross section was analyzed from each sampled root segment.

Root morphology

Rice displays a characteristic fibrous root system with abundant formation of adventitious and lateral roots. One plant from each pot was harvested, and all roots were separated and scanned using a flatbed scanner with a transparency unit (Epson Expression 12000XL, Epson, Suwa, Japan). Images were digitalized at 600 dpi as 16‐bit greyscale images and saved as Tagged Image File Format (TIFF). Total root lengths and root diameters from either adventitious or lateral roots were extracted using the open‐source software RhizoVision (Seethepalli et al., 2021). Specific root diameters of adventitious or lateral roots from each genotype were obtained from root cross sections (as discussed earlier) and were used for classifying root types. Short‐type laterals were not further separated from long‐type laterals in this study.

Respiratory O2 consumption of root segments

Respiratory rates were measured in excised root segments at the developing and developed zones of the adventitious roots and at the mid part of long‐type lateral roots. Rates were measured following the procedure described in Colmer & Pedersen (2008) using a MicroResp system (Unisense A/S, Aarhus, Denmark). Briefly, root segments of 25 mm length were excised from each root type or segment and inserted in 4‐ml glass vials containing O2 air‐saturated water. Each vial contained a glass‐coated magnetic stir bar, and the stirring rate was set to 600 rpm using a stirrer controller unit (MR2‐St‐Co; Unisense A/S). The vials were placed in a rack and submerged into a constant temperature bath (30°C) and left to stabilize for c. 15 min. Oxygen consumption by the root sections was measured in each vial using an O2 optode (OP‐MR; Unisense A/S) every 10 min for c. 1 h. Vials filled with saturated O2 water but without tissues served as blanks. The volume of each vial was determined immediately after finishing the O2 measurements. The volume of each root segment was calculated using the cross‐sectional area and length of roots within each vial. Oxygen uptake rates were calculated as the difference in O2 concentration (μmol O2 l−1) between two time points multiplied by the vial volume (l) using Rate (Sensortrace Suite v.2.3.100; Unisense A/S) and divided by the volume (cm3) of the tissue. At mature parts of adventitious roots, segments were sliced opened, to allow O2 consumption by root tissue, as previously described by Jiménez et al. (2021a), while roots segments from developing parts of adventitious or from lateral roots with higher O2 permeability were left intact.

Modeling

We used the multicylindrical model of Beckett et al. (2001) to examine the individual effects of root anatomical, morphological and physiological traits on predicted CH4 emissions and rhizospheric CH4 oxidation. The model was parameterized using trait values measured in six rice genotypes, while individual traits were varied across the ranges specified in the corresponding figures and Tables S1–S10. The simulations were designed as mechanistic analyses to isolate the effect of each root trait on CH4 emission and oxidation through its influence on O2 and CH4 diffusion, rather than as direct predictions of soil‐ or field‐scale CH4 fluxes. Consequently, the direction of the predicted trait effects may also be relevant to soil‐grown roots expressing comparable trait values, whereas the absolute fluxes will depend on soil‐specific physical and biogeochemical conditions. All simulations assumed steady‐state diffusion under fixed boundary conditions. Consequently, the model did not represent transient variation associated with root growth, diurnal changes, fluctuating microbial activity or changing rhizosphere redox conditions.

The model treats the root plus any oxygenated rhizosphere as a series of concentric cylinders: two nonporous stelar cylinders (treated here as one for simplicity), surrounded by a porous cortical cylinder, followed by a nonporous hypodermal–exodermal–epidermal (HEE) cylinder, and finally the surrounding rhizosphere. The default O2 source concentration at the root base was set at 259 μg cm−3. The CH4 source, introduced at a concentration of 6.4 μg cm−3, was positioned at the outer edge of the oxygenated rhizosphere, under the assumption that methanogenesis is inhibited within oxygenated zones.

Oxygen diffuses longitudinally downward through the cortex in the gas phase, while CH4 diffuses upward. By contrast, diffusion within the stelar and HEE cylinders and the surrounding soil occurs radially and in the liquid phase. Oxygen consumption was programmed for the stelar, HEE and rhizosphere cylinders, whereas CH4 consumption via methanotrophy was restricted to the oxygenated rhizosphere, with no methanotrophy assumed within the root tissues.

The extent of the oxygenated rhizosphere is governed by the integrated effects of O2 consumption in both the root and the rhizosphere, including methanotrophic and non‐methanotrophic O2 demand, together with the diffusive resistances throughout the system. Non‐methanotrophic O2 consumption was represented as an aggregated rhizosphere O2 sink rather than being separated into individual microbial and abiotic processes. The simulations therefore quantify the consequences of an imposed non‐methanotrophic O2 demand without distinguishing the individual processes responsible for that demand.

For computational implementation, the root was divided longitudinally into nine segments, not necessarily of equal length. Within each segment, the cylinders were assigned specific diffusive and respiratory properties based on their position along the root (Tables S1–S10). In the cortical cylinder, the effective diffusive coefficient was calculated as the product of the gas‐phase diffusion coefficient and the fractional porosity, assuming no tortuosity in the diffusion path. For nonporous cylinders, resistance relative to the gas phase was determined by their dimensions and the diffusion coefficient for gases in water, adjusted by a 34‐fold factor to account for the concentration drop at the gas–water interface (Armstrong & Beckett, 1987). Rates of O2 consumption by root respiration, methanotrophy and the aggregated non‐methanotrophic rhizosphere O2 sink were treated as unaffected by O2 concentration at all values above zero, with consumption ceasing at zero.

A resistance parameter (λ) was imposed at the surface of the HEE cylinder to simulate the barrier to O2 efflux and CH4 influx. This was calibrated to reflect near‐zero permeability at the root base, increasing sharply toward full permeability at the developing apex, consistent with rice roots grown in deoxygenated media (Fig. 1; cf. Jiménez et al., 2021b). Soil diffusive resistance incorporated a combined fractional porosity and tortuosity of 0.46, along with the same 34‐fold solubility correction.

Fig. 1.

Fig. 1

Open in a new tab

Longitudinal variation in rice (Oryza sativa L.) root traits affecting the bidirectional diffusion of O2 and CH4. (a) Longitudinal variation in root permeability to gas diffusion (orange), cortical porosity (green) and respiratory O2 consumption (light blue). (b) Half vertical root section showing a longitudinal increase in CH4 (blue) and a decrease in O2 (red) from apex to base within the cortex, as well as the extent of the oxygenated rhizosphere (green). (c) Radial concentration profiles of CH4 (blue) and O2 (red) at five positions in the root and rhizosphere. Panels (b, c) represent steady‐state diffusion for adventitious roots of rice of 12 cm in length, based on the traits shown in (a). Fractional values are for typical adventitious root of rice grown in flooded soils. See Supporting Information Figs S1 and S2, for differences in porosity and suberization between apical and basal regions, and Fig. S3, for differences in respiration. Permeability is directly associated with the development of a suberized exodermis, which forms a barrier to impede gas diffusion. Co, cortex; Ep/ex, epidermis/exodermis; Rhiz, rhizosphere; St, stele. Radius stele (rs = 0.13 mm), radius cortex (rc = 0.54 mm), radius root (rr = 0.57 mm), radius of oxygenated rhizosphere from root epidermis (ror = 0.91 mm).

Longitudinal variation in cortical porosity was modeled using a logistic function (cf. Yamauchi et al., 2020). Mean anatomical, morphological and physiological values from five biological replicates were used as the reference parameterization. For each individual‐trait analysis, the focal parameter was then varied above and/or below this reference value, depending on the trait and simulation scenario, while the remaining parameters were held constant unless otherwise stated. All parameter values used in the simulations are reported in the corresponding figures and Tables S1–S10.

Rhizosphere resistance to CH4 diffusion

R rh, the rhizosphere resistance to CH4 diffusion to the root at its most permeable part, was calculated per cm length of root (s cm−3) as follows (Eqn 1):

Rrh=rr×logerrh/rr×34De×2π×rr. (Eqn 1)

where r r is the root radius (cm), r rh is the rhizosphere radius (cm), D e is the effective diffusive coefficient of CH4 in the rhizosphere (cm2 s−1). D e = D o ƐT, where D o is the diffusion coefficient for CH4 in water, Ɛ is the fractional porosity of the rhizosphere (taken as 0.45), and T is a tortuosity factor (taken as 0.55).

Results

Influence of longitudinal variation in adventitious root traits on CH4 emissions and CH4 oxidation

Adventitious roots of rice exhibit longitudinal variation in porosity, respiration and permeability (Figs 1a, S1–S3). In general, root cortical porosity was lower in apical parts, with an average of 6.5% for the six genotypes evaluated, and increased toward the basal parts, with an average of 53.3% (Fig. S2). Respiratory O2 consumption also varied among the six genotypes evaluated, being on average 2.9‐fold higher in apical parts, with a rate of 131.5 ng O2 cm−3 s−1, compared to 45.4 ng O2 cm−3 s−1 for basal parts of roots (Fig. S3). Root permeability to gas diffusion, evaluated by the deposition of suberin in the exodermal cell walls, also exhibited longitudinal variations along the adventitious roots of rice. A fully suberized lamellae was developed at the exodermis at basal parts of the root, while no apoplastic barriers were visible at the apical parts (Fig. S1).

Computing the longitudinal changes in root traits of individual adventitious roots reveals radial variations in O2 and CH4 fluxes along the root (Fig. 1b,c). In a typical adventitious rice root, characterized by lower gas permeability, higher cortical porosity and lower respiration compared to the apex (Fig. 1a), a 12‐cm root would exhibit a fully aerobic cortex and an oxygenated rhizosphere of 0.91 mm surrounding the apex (Fig. 1b). The spatial distribution of CH4 and O2 concentrations throughout a single rice root and its rhizosphere indicates that cortical CH4 concentrations decrease monotonically with distance up the root, while O2 concentrations decline in the opposite direction (Fig. 1b). At the apex, the concentration gradient implies that CH4 is diffusing toward the root from outside the oxygenated rhizosphere. By contrast, CH4 diffusion is limited in the basal regions due to lower gas permeability of the exodermis (Fig. 1c).

Root types and their potential for CH4 emissions and CH4 oxidation

Rice plants have a characteristic fibrous root system composed of numerous adventitious roots, from which abundant long‐type lateral roots emerge. Short‐type lateral roots can also develop, either from long‐type lateral roots or directly from the adventitious roots; however, these are excluded from the analysis in this study. Therefore, all references to lateral roots in this study refer to long‐type laterals. Variations in cortical porosity, respiration and root diameter are evident among the different genotypes evaluated and between adventitious and lateral roots (Table 1; Figs S1–S4). In general, lateral roots resemble a smaller version of the basal part of an adventitious root. They exhibited a suberized exodermis (Fig. S5), and cortical porosity at the mid part of a 4‐cm root ranging from 17% to 30%, compared to 8–12% and 46–61% in the apical and basal parts of adventitious roots, respectively. Lateral roots also have smaller diameters, ranging from 208 to 435 μm, whereas adventitious roots range from 957 to 1369 μm at the apical part and 1084 to 1532 μm at the basal part (Table 1). The respiratory O2 consumption of lateral roots was, on average, 224.8 ng O2 cm−3 s−1, which was 4.9‐fold higher than that of the basal part of an adventitious root, but only 1.7‐fold higher than that of the apical part (Fig. S3). Lateral roots per plant were more abundant than adventitious roots, with a total lateral root length ranging from 47.1 to 77.6 m, compared to 20.3 to 24.8 m for adventitious roots (Fig. S6). Given the larger diameters of adventitious roots, their surface area was, on average, 1.7‐fold greater than that of lateral roots, with averages of 619.8 and 360.6 cm2, respectively (Fig. S6).

Table 1.

Root traits affecting the diffusion of O2 and CH4 into and throughout the adventitious and lateral roots of rice (Oryza sativa L.).

Trait Adventitious Laterals
Stele diameter (μm) Apical 186–310 69–101
Basal 209–364
Root diameter (μm) Apical 957–1369 208–435
Basal 1084–1532
Hypodermis/epidermis/exodermis (HEE) thickness (μm) Apical 17–29 12–22
Basal 25–45
Root cortical porosity (%) Apical 8–12 17–30
Basal 46–61
Longitudinal resistance (104 s cm−3) a Apical 3.42–1.15 45.2–5.22
Basal 0.94–0.37
Radial resistance (104 s cm−3) b Apical 0.94–1.13 3.19–2.77
Basal 1.23–1.58
Predicted CH4 emission per root (ng CH4 s−1) c 0.46–0.56 0.32–0.47 d
Predicted CH4 oxidation per root (pg CH4 s−1) 51.17–107.75 52.29–116.75 d
Open in a new tab

The ranges represent the minimum and maximum average values from the six genotypes evaluated. Traits were measured at the apical and basal regions of 12‐cm adventitious root and at the mid part of 4‐cm long‐type laterals. Predicted emission and oxidation rates are described for individual adventitious or long‐type lateral roots without branching.

a

In adventitious roots, longitudinal resistance to CH4 diffusion was calculated based on minimum and maximum variations in both root diameter and cortical porosity at the apical (4 cm) and basal (8 cm) parts of the roots, along a 12‐cm root length. In lateral roots, longitudinal resistance was calculated on a 4‐cm root length with porosity and diameters assumed to be homogeneous.

b

Radial resistance to CH4 diffusion across the epidermal/exodermal cells of 1 cm length of root, with the respective anatomical characteristics of either adventitious or lateral roots, assuming no development of apoplastic barriers in exodermis.

c

The multicylindrical model was used to predict emission and oxidation rates. The ranges represent minimum and maximum values from the six genotypes evaluated (Supporting Information Table S10). No development of apoplastic barriers was assumed for lateral roots.

d

The concentration of O2 at the lateral root base is assumed to be the same as in adventitious roots (i.e. O2 concentration in moist air of 259 μg cm−3 at 30°C). Note that for laterals, this may actually vary, depending on the sites where laterals are attached to the adventitious roots.

The longitudinal resistance to CH4 diffusion in a 12‐cm adventitious root of rice, with an average root diameter of 1042 μm, apical porosity of 8% and basal porosity of 46%, is 4.36 × 104 s cm−3. This resistance decreases to 1.52 × 104 s cm−3 in a root with a thicker average diameter of 1478 μm, 12% apical and 61% basal porosity (see Table 1, for longitudinal resistances at the basal and apical regions of the root). In thinner individual lateral roots, the longitudinal resistance over a 4‐cm root with a diameter of 208 μm and porosity of 17% is 45.2 × 104 s cm−3, and it decreases to 5.22 × 104 s cm−3 in a wider lateral root with a diameter of 435 μm and 30% porosity. In adventitious roots, the radial resistance to CH4 diffusion in a 1‐cm root segment at the apical part ranges from 0.94 × 104 s cm−3 in a root with a diameter of 957 μm and an HEE thickness of 17 μm, to 1.13 × 104 s cm−3 in a root with a larger diameter of 1369 μm and an HEE thickness of 29 μm. At the basal part, and assuming no development of apoplastic barriers, radial resistances ranged from 1.23 × 104 s cm−3 in a root with a diameter of 1084 μm and an HEE thickness of 25 μm, to 1.58 × 104 s cm−3 in a root with a bigger diameter of 1532 μm and an HEE thickness of 45 μm. For the thinner lateral roots, the radial resistance to CH4 over a 1‐cm segment of a 208 μm diameter root and with an HEE thickness of 12 μm is 3.19 × 104 s cm−3 but it decreases to 2.77 × 104 s cm−3 in a wider root of 435 μm diameter with an HEE thickness of 22 μm. Individual adventitious roots exhibited a higher capacity for CH4 emission and CH4 oxidation than lateral roots. The predicted CH4 emission per root is higher than the predicted CH4 rhizospheric oxidation capacity, regardless of root type (Table 1).

Increased cortical porosity reduces CH4 emissions

Given the simultaneous variation in root anatomical traits within a root, we analyzed the individual effects that variations in mean cortical porosity will have on CH4 emission from the base of the root and CH4 oxidation in the rhizosphere. In adventitious roots of 12 cm, with an average longitudinal porosity of 11%, the CH4 emission from the root base was predicted to be 3.48 ng CH4 s−1 (Fig. 2a). The CH4 emission was sharply decreased to 0.61 ng CH4 s−1 in roots of 17% cortical porosity, and further decreased slightly to 0.47 ng CH4 s−1 in roots of 32% averaged cortical porosity. By contrast, the CH4 oxidation in rhizosphere was predicted to be 2.97 pg CH4 s−1 in low‐porosity roots of 11%, and substantially increased to 39.87 pg CH4 s−1 in roots of 17% porosity, and then further to 78.11 pg CH4 s−1 in roots of 32% porosity (Fig. 2a). Reductions in CH4 emissions from more porous roots are driven by the expansion of the oxygenated rhizosphere and by an increased rhizosphere resistance to CH4 diffusion (Fig. 2b). For example, in roots with an average cortical porosity of 11%, O2 diffusion is so restricted that it does not reach the rhizosphere at the apical part of the root, thereby providing essentially no resistance to CH4 diffusion. By contrast, in roots with 32% cortical porosity, O2 diffuses to 0.94 mm into the rhizosphere, and rhizosphere resistance to CH4 diffusion increases to 1.03 × 106 s cm−3 (Fig. 2b).

Fig. 2.

Fig. 2

Open in a new tab

Predicted effects of rice (Oryza sativa L.) root cortical porosity on CH4 emissions, rhizosphere CH4 oxidation and the oxygenated rhizosphere and rhizosphere resistance to CH4 diffusion. (a) Predicted CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). (b) Corresponding effects on the extent of the oxygenated rhizosphere (green) and on rhizosphere resistance to CH4 diffusion (orange). Although cortical porosity in each root increases from apex to base, we used here the mean porosities for each root. In (b), the extent of the oxygenated rhizosphere at the root apex is shown for roots with different mean cortical porosity. Root diameter was assumed to be uniform along the root, while respiration and gas permeability varied longitudinally according to typical rice root profiles (Fig. 1; Supporting Information Table S3). All predictions are based on an adventitious rice root of 12 cm in length. Green horizontal stipple lines denote the root epidermis; values below that line indicate that O2 does not reach the epidermis.

Effects of cortex to stele ratios on emissions

Stele diameter fixed, root and cortex diameters increasing

CH4 emissions and CH4 oxidation rates were lower in roots with smaller CSR, with values of 0.31 ng CH4 s−1 and 31.9 pg CH4 s−1, respectively, at a CSR of 3, increasing to 0.49 ng CH4 s−1 and 80.4 pg CH4 s−1 when the CSR increased to 19 (Fig. 3a). Interestingly, increasing the CSR expanded the oxygenated rhizosphere from 0.62 mm at a CSR of 3 to 0.92 mm at a CSR of 19, while decreasing the rhizosphere resistance to CH4 diffusion from 1.22 × 106 s cm−3 at a CSR of 3 to 9.83 × 105 s cm−3 at a CSR of 19 (Fig. 3b).

Fig. 3.

Fig. 3

Open in a new tab

Predicted effects of the cortex to stele ratio and stele diameter in roots of rice (Oryza sativa L.) on CH4 emissions, rhizosphere CH4 oxidation, the oxygenated rhizosphere and rhizosphere resistance to CH4 diffusion. (a) Effects of cortex to stele ratio on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). (b) Corresponding effects on the extent of the oxygenated rhizosphere (green) and rhizosphere resistance to CH4 diffusion (orange). (c) Effects of stele diameter on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). (d) Corresponding effects on the extent of the oxygenated rhizosphere (green) and rhizosphere resistance to CH4 diffusion (orange). In (a), stele diameter as well as exodermal/epidermal thickness were kept constant, while the root diameter varied to increase the cortex to stele ratio, as indicated on the x‐axis. In (c), root diameter and exodermal/epidermal thickness were kept constant, while the stele diameter varied to increase, as indicated on the x‐axis. In (b, d), the extent of the oxygenated rhizosphere and rhizosphere resistance to CH4 diffusion at the root apex are shown for roots with different cortex to stele ratios or stele diameters, respectively. Cortical porosity, respiration and gas permeability varied longitudinally according to typical rice root profiles (Fig. 1; Supporting Information Table S4). All predictions are based on an adventitious rice root of 12 cm in length.

Root and cortex diameter fixed, stelar diameter decreasing

In roots with a smaller stele diameters (0.20 mm), CH4 emissions were lower and oxidation rates higher, 0.471 ng CH4 s−1 and 77.8 pg CH4 s−1, respectively, compared with roots having a larger stele diameter (0.30 mm), where emissions increased to 0.475 ng CH4 s−1 and oxidation decreased to 75.9 pg CH4 s−1, respectively (Fig. 3c). Reducing stele diameter within a fixed root diameter increased both the extent of the oxygenated rhizosphere and the rhizosphere resistance to CH4 diffusion (Fig. 3d).

Increased root respiratory O2 consumption and absence of an apoplastic barrier increase CH4 emissions

In addition to anatomical traits, the effects of root respiration (a) and the development of apoplastic permeability barriers (b) were also examined, since they also help to determine the O2 concentrations within the root and the root's ability to oxygenate the rhizosphere.

  1. For a 12‐cm adventitious root with porosities and permeability barriers as in Fig. 1 and Table S5, but with halved respiratory rates (Table S5), the predicted CH4 emission was 0.43 ng s−1 and the oxidation in the rhizosphere was 94.7 pg CH4 s−1 (Fig. 4a). The O2 concentration in the apex was 184 μg cm−3 (c. 14.5 kPa). A fourfold increase in root respiration rates raised the CH4 emissions to 0.69 ng s−1, decreased the CH4 oxidation in the rhizosphere to 34.43 pg s−1 (Fig. 4a) and lowered the O2 concentration in the apex to 26.3 μg cm−3 (c. 2.1 kPa).

  2. A typical 12‐cm adventitious root of rice was modeled with structural characteristics as in Fig. 1 and Table S6 (respiration rates of step size 2; Fig. 4a). With the permeability barrier complete by 5 cm from the tip (Fig. 1), CH4 emission and CH4 rhizospheric oxidation were 0.47 ng s−1 and 76.9 pg s−1, respectively (Stage 1; Fig. 4b). Progressive basipetal removal of the root apoplastic barrier, which normally restricts gas diffusion between the root and the rhizosphere, caused a steady rise in both CH4 emissions and CH4 oxidation in the surrounding soil. With the barrier wholly removed (Stage 9; Fig. 4b), CH4 emissions were nearly fivefold greater, at 2.29 ng s−1 and CH4 oxidation nearly sevenfold greater at 527.6 pg s−1 (Fig. 4b). The additional leakage resulting from barrier removal also reduced the O2 concentration in the root apex 1.2‐fold from 131 μg cm−3 (c. 10.3 kPa) to 110 μg cm−3 (c. 8.7 kPa).

Fig. 4.

Fig. 4

Open in a new tab

Predicted effects of rice (Oryza sativa L.) root respiration and apoplastic barriers on CH4 emissions and rhizosphere CH4 oxidation. (a) Effects of root respiration on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). (b) Effects of the development of apoplastic barriers impeding gas diffusion on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). In (a), roots were modeled with respiration highest at the apex, decreasing basipetally to a stable value 50 mm from the apex. All respiratory values along the root were then increased stepwise from their initial settings (1), as shown on the x‐axis (Supporting Information Table S5). In (b), apoplastic barriers were incrementally removed. Stage 1 represents a typical rice root with the respiration rates of step size increment 2 in (a) and with longitudinal variation in barrier formation (Fig. 1), while Stage 9 depicts a root with no barrier formation (Table S6). Root diameter was assumed to be uniform along the root, while cortical porosity varied longitudinally according to typical rice root profiles (see Fig. 1 and Table S5, for (a) and Table S6 for (b)). All predictions are based on an adventitious rice root of 12 cm in length.

Shorter roots display lower CH4 emissions and higher CH4 oxidation capacity, regardless of the soil non‐methanotrophic O2 consumption

Non‐methanotrophic O2 consumption in soil influences the size of the oxygenated rhizosphere around the root and consequently the CH4 emissions and the root capacity to oxidize CH4. In soils with a high non‐methanotrophic O2 consumption rate (Qox = 50 ng cm−3 s−1), CH4 emissions from roots were higher than in soils with a low non‐methanotrophic O2 consumption rate (Qox = 0.5 ng cm−3 s−1). Short roots of 10 cm exhibited a CH4 emission rate of 0.98 ng CH4 s−1 in soils with a high non‐methanotrophic O2 consumption rate, which decreased to 0.39 ng CH4 s−1 in soils with a low O2 consumption rate (Fig. 5). Higher CH4 oxidation rates were predicted from roots in soils with low O2 consumption. Short roots of 10 cm exhibited CH4 oxidation rates of 16.7 pg CH4 s−1 in soils with a high non‐methanotrophic O2 consumption, which increased to 121.4 pg CH4 s−1 in soils with a low non‐methanotrophic O2 consumption rate (Fig. 5).

Fig. 5.

Fig. 5

Open in a new tab

Predicted effects of rice (Oryza sativa L.) root length on CH4 emissions and rhizosphere CH4 oxidation. (a) Effects of root length on CH4 emissions from the root base (blue) and rhizosphere CH4 oxidation (red) under high non‐methanotrophic O2 consumption in rhizosphere (Qox = 50 ng cm−3 s−1), and (b) under low non‐methanotrophic O2 consumption (Qox = 0.5 ng cm−3 s−1). The background methanotrophic O2 consumption rate for (a) and (b) was assumed to be Qmox = 2.4 ng cm−3 s−1. Root length was increased by extending the root at its base using basal root characteristics, while root diameter was assumed to be uniform. Cortical porosity, respiration and gas permeability varied longitudinally according to typical rice root profiles (Fig. 1; Supporting Information Table S7). Based on the root characteristics, the length at which the root becomes anoxic is 24.1 cm in (a) and 24.4 cm in (b).

Emissions increased with root length, and by 20 cm, it had reached 1.34 and 0.52 ng CH4 s−1 in roots under high or low soil non‐methanotrophic O2 consumption rates, respectively. Emissions eventually peaked at 4.7 ng CH4 s−1 in roots of 26 cm, regardless of soil non‐methanotrophic O2 consumption rate (Fig. 5). CH4 oxidation rates decreased with increasing root length, reaching as low as 0.04 or 0.65 pg CH4 s−1 in roots of 30 cm, in high or low non‐methanotrophic O2 consumption soils, respectively (Fig. 5). It should be noted that for roots to have grown much beyond 24 cm under the pertaining soil conditions some other parameters would have needed to change (see the Discussion section).

Increased non‐methanotrophic and methanotrophic O2 consumption rates in soil increases CH4 emissions

For a typical adventitious rice root (characteristics as in Fig. 1; Table S8), increasing non‐methanotrophic and methanotrophic O2 consumption rates in the surrounding soil led to higher CH4 emissions and a narrowing of the oxygenated rhizosphere (Fig 6a–d). Panels 6c,d show the corresponding changes in oxygenated rhizosphere thickness for the simulations presented in Panels 6a,b, respectively. A 200‐fold increase in non‐methanotrophic O2 consumption rate (Fig. 6a) brought about a threefold rise in emissions (0.41–1.28 ng s−1), reduced rhizospheric CH4 oxidation by 91% (0.11–0.01 ng s−1) and narrowed the oxygenated rhizosphere at the apex from 1.15–0.20 mm (Fig. 6c). A 24‐fold increase in methanotrophic O2 consumption rate (Fig. 6b) raised emissions by 27% (0.43–0.58 ng s−1), increased rhizospheric CH4 oxidation approximately eightfold (0.02–0.16 ng s−1) and narrowed the oxygenated rhizosphere at the apex from 1.17 to 0.59 mm (Fig. 6d).

Fig. 6.

Fig. 6

Open in a new tab

Predicted effects of non‐methanotrophic and methanotrophic O2 consumption in the rhizosphere on CH4 emissions, rhizosphere CH4 oxidation and the oxygenated rhizosphere. (a) Effects of non‐methanotrophic O2 consumption on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). (b) Effects of methanotrophic O2 consumption on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). Panels (c, d) show the thickness of the oxygenated rhizosphere as non‐methanotrophic (a) or methanotrophic (b) O2 consumption increases. The background methanotrophic O2 consumption rate for (a) and (c) was assumed to be Qmox = 2.4 ng cm−3 s−1. The background non‐methanotrophic O2 consumption rate for (b, d) was assumed to be Qox = 2.4 ng cm−3 s−1. Root diameter was assumed to be uniform along the root, while cortical porosity, respiration and gas permeability varied longitudinally according to typical rice root profiles (Fig. 1; Supporting InformationTable S8). All predictions are based on an adventitious rice root of 12 cm in length.

Specific conditions under which methanotrophic activity decreases CH4 emissions

Given that an increase in methanotrophic O2 consumption rate in the soil per se increases CH4 emissions (see the previously described paragraph), we explored a scenario in which methanotrophy instead could reduce CH4 emissions. For the standard 12‐cm root, when non‐methanotrophic O2 consumption rates (i.e. basic O2 consumption) in the soil was high and methanotrophic O2 consumption rate was low, CH4 emission was high (0.76 ng s−1), while CH4 oxidation was low (26.6 pg s−1; Fig. 7). By contrast, when methanotrophic O2 consumption increased at the expense of non‐methanotrophic O2 consumption, but the overall rate of O2 consumption in the rhizosphere remained constant, CH4 emissions decreased to 0.72 ng s−1 and CH4 oxidation increased to 146.5 pg s−1 (Fig. 7). As overall O2 consumption rate remained constant at 22.4 ng cm−3 s−1 across variations in both non‐methanotrophic and methanotrophic activities, the extent of the oxygenated rhizosphere and the rhizosphere resistance to CH4 diffusion remained unchanged at 0.43 mm and 5.98 × 105 s cm−3, respectively.

Fig. 7.

Fig. 7

Open in a new tab

Conditions in the rhizosphere under which methanotrophic activity decreases CH4 emissions. (a) Predicted effects of increasing methanotrophic O2 consumption on CH4 emissions from the root base (blue) and CH4 oxidation in the rhizosphere (red). Methanotrophic O2 consumption (Qmox) was doubled sequentially exactly at the expense of the non‐methanotrophic O2 consumption (Qox) within the rhizosphere. The overall O2 consumption in the rhizosphere for all scenarios remained constant at 22.4 ng cm−3 s−1. The rhizosphere thickness and the rhizosphere resistance to CH4 diffusion remained constant at 0.43 mm and 5.98 × 105 s cm−3, respectively. Root diameter was assumed to be uniform along the root, while cortical porosity, respiration and gas permeability varied longitudinally according to typical rice root profiles (Fig. 1; Supporting Information Table S9). All predictions are based on an adventitious rice root of 12 cm in length.

Discussion

Rice plants have a complex root system characterized by thick adventitious roots with abundant lateral roots emerging from them. Both adventitious and lateral roots are of different diameters and lengths and exhibit differences in respiratory O2 consumption, as well as longitudinal variation in anatomical and physiological characteristics. In this study, we used a mathematical model (Beckett et al., 2001) to predict how these variations could influence CH4 emissions and rhizospheric CH4 oxidation. Root traits that enhance internal O2 diffusion from shoots to the rhizosphere, such as increased cortical porosity, reduced respiratory O2 consumption, a reduced stelar radius and the development of apoplastic barriers that impede gas diffusion, were predicted to create expanded oxygenated rhizospheres in apical parts leading to more rhizospheric methanotrophic CH4 oxidation and reduced CH4 emissions. The modeling indicated, however, that this reduction resulted primarily from displacement of the anaerobic CH4‐supplying front farther from the root, causing a suppression of methanogenesis and increasing the resistance to CH4 diffusion to the root, rather than from the amount of CH4 consumed by methanotrophy. Indeed, contrary to prevailing assumptions, increasing rates (ng O2 cm−3 s−1) of methanotrophy mostly increased CH4 emissions by shrinking the oxygenated rhizosphere, thereby shifting the CH4 front closer to the root and reducing rhizospheric resistance to CH4 diffusion.

An expanded oxygenated rhizosphere not only inhibits methanogenesis but also increases O2 availability to soil microorganisms, leading to competition between methanotrophic and non‐methanotrophic microorganisms for O2, in which heterotrophic activity often outcompetes methanotrophs (van Bodegom et al., 2001b). An increase in O2 consumption by microorganisms in the rhizosphere should enhance CH4 emissions by directly reducing the extent of the oxygenated rhizosphere and shifting the CH4 front closer to root (Fig. 6). Notably, greater activity of methanotrophs, which are responsible for CH4 oxidation but require 4 g of O2 for the complete oxidation of 1 g of CH4 (CH4 + 2O2 → CO2 + 2H2O), should paradoxically increase CH4 emissions, as it intensifies competition for O2 within the soil. A situation in which methanotrophs can actually reduce CH4 emissions occurs when their activity increases at the expense of non‐methanotrophic O2 consumption in the rhizosphere, while overall O2 consumption rates in the soil remain constant (Fig. 7). Therefore, the net effect of microbial O2 consumption on CH4 emissions depends not only on methanotrophic activity but also on the relative contributions of other aerobic processes competing for O2 in the rhizosphere. A simple characterization of microbial community composition around the rhizosphere may be insufficient to explain CH4 emission dynamics, as the interplay between ROL or other exudates from roots and microbial O2 demand largely determines the balance between CH4 formation, oxidation and emission.

ROL from roots to flooded soils is impeded by apoplastic barriers that develop in the outer cell layers of the root. A typical rice root grown in flooded soils, exhibiting subapical development of barriers to ROL, shows markedly lower CH4 emission and oxidation rates compared to a hypothetical root without barrier development, by 4.9‐ and 6.9‐fold, respectively (Fig. 4b). Total ROL from roots varies significantly among rice cultivars and is negatively correlated with total CH4 emissions (Zheng et al., 2018; Chen et al., 2019). It may appear counterintuitive, however, that reduced ROL from individual adventitious roots with barrier formation (Fig. 1) corresponds with both lower rhizosphere oxidation and reduced CH4 emissions (Fig. 4b). In this case, subapical barrier development restricts ROL across mature root regions while maintaining O2 diffusion toward the apex, thereby enhancing apical ROL and generating an oxygenated rhizosphere. Moreover, reduced permeability to ROL also limits the diffusion of CH4 in the opposite direction, from the soil to the root, producing a spatial configuration in which rhizosphere oxygenation is greatest at the apex while CH4 entry at the base is limited. Under steady‐state conditions, roots of 12 cm in length with characteristic barrier development were predicted to sustain an oxygenated rhizosphere radius of 0.91 mm at the apex (Fig. 1). In paddy soils, however, rhizosphere oxidation occurs dynamically along rhizosphere microsites influenced by root growth and local rhizosphere dynamics (van Bodegom et al., 2001a). Additionally, variation in the timing and strength of barrier formation (Colmer, 2003b; Shiono et al., 2011) and environmental factors such as sulfides (Armstrong & Armstrong, 2005), organic acids (Colmer et al., 2019) and high Fe availability and associated root Fe‐plaque formation (Jiménez et al., 2025) can further modulate barrier formation, ROL and CH4 permeability across root zones.

In flooded soils, O2 released by roots can be used by a broad range of rhizosphere biogeochemical processes, including aerobic heterotrophic respiration (van Bodegom et al., 2001b), nitrification (Yao et al., 2024a) and the oxidation of reduced compounds such as Fe2+ and sulfide (Kirk, 2004; Maisch et al., 2019). Interactions between ROL and Fe‐plaques can also generate reactive oxygen species through Fenton‐type reactions (Yao et al., 2024a), potentially affecting organic‐matter turnover and other microbial redox processes (Yao et al., 2025). Fe plaque may additionally influence methanogenic activity through its effects on electron transfer and O2 diffusion (Yao et al., 2024b; Jiménez et al., 2025). These processes, together with other rhizosphere biogeochemical reactions, were not resolved separately in the model; instead, their combined contribution to O2 consumption was represented by the aggregated non‐methanotrophic O2 sink. High root porosity enables efficient O2 diffusion from shoot to roots, yet this trait can also facilitate CH4 diffusion from the rhizosphere to the atmosphere through the plant. Our results indicated that enhanced cortical porosity increases rhizosphere oxidation by expanding the oxygenated rhizosphere zone, thereby increasing the rhizosphere resistance to CH4 diffusion into the root and ultimately reducing CH4 emissions (Fig. 2). This suggests that root porosity plays a more critical role in rhizosphere oxygenation, reducing methanogenesis by aerating the rhizosphere, than in facilitating CH4 diffusion to the atmosphere (cf. Roy et al., 2025b). Although aerenchyma develops within the cortex, an increase in cortical area, assuming constant stelar area, without a corresponding increase in tissue porosity, would instead promote higher CH4 emissions. For example, a root with a CSR of 19 (i.e. a cortex 19 times bigger than the stele) exhibits 1.6‐ and 2.5‐fold higher CH4 emissions and oxidation rates, respectively, compared with a root with CSR of 3 (a cortex three times bigger than the stele; Fig. 3a). While a wider root diameter enhances longitudinal O2 diffusion (Table 1) and thus expands the oxygenated rhizosphere, the radial resistance for CH4 diffusion from rhizosphere into the root decreases with increasing root diameter because of the larger surface area available for CH4 entry (Eqn 1; Fig. 3b). Therefore, selecting rice genotypes with wider root diameters should also ensure enhanced overall root porosity (Roy et al., 2025b).

In flooded, anoxic soil, O2 supply to roots depends on internal longitudinal gas diffusion from the shoots. Consequently, the apical O2 concentration progressively declines as the root elongates and extends away from this source (Armstrong, 1979; Colmer, 2003a; Jiménez & Pedersen, 2026). The maximum root length that rice can sustain under such conditions depends on its capacity for internal O2 diffusion and has been reported to range from 17 to 25 cm (Colmer, 2003b). In our study, based on typical rice root characteristics (Fig. 1), the root apex became anoxic at c. 24 cm (Fig. 5). Consequently, CH4 emissions from longer roots of 26 cm were 4.8‐ or 11.9‐fold higher than those from shorter roots of 10 cm under high or low non‐methanotrophic O2 consumption in soil, respectively (Fig. 5). This difference is due to the lower O2 concentrations in the apices of longer roots and the consequently narrower or absent oxygenated rhizospheres. A slight decline in CH4 emissions from roots longer than 26 cm (i.e. 28–30 cm; Fig. 5) was attributable to anoxia in the apical region, coupled with the extra diffusive resistance within the extended root length. As the root was predicted to become anoxic at a length of 24 cm, those extending to 26–30 cm likely need to be developed under alternate wetting and drying cycles or during daytime growth in clear waters, when photosynthesis by partly submerged shoots enhances O2 diffusion to roots (Waters et al., 1989). Interestingly, in soils with higher non‐methanotrophic O2 consumption rates, where CH4 emissions were predicted to be greater than in soils with lower microbial O2 demand (Fig. 5), CH4 emissions were still consistently lower in shorter roots (Fig. 5). Selecting genotypes with shorter roots may therefore be particularly beneficial, even under alternate wetting and drying schemes, in which soil O2 consumption can vary due to fluctuations in microbial activity (Haque et al., 2022; Majumdar et al., 2023), especially considering that genotypes with extensive aerenchyma formation, which exhibited lower CH4 emissions under continuous flooding, showed increased CH4 emissions once the soil was drained (Li et al., 2025).

Lateral roots, although much less studied, represent another important site for O2 loss and CH4 entry. Mathematical models have indicated that lateral roots can oxygenate a zone nearly as large and, relative to their size, larger than the adventitious root from which they arise (Armstrong, 1970). Differences in lateral root characteristics were evident among the genotypes evaluated (Figs S2–S6). However, we refrain from drawing conclusions about the influence of lateral roots on CH4 diffusion and oxidation because variations in O2 at the base of the lateral root can vary greatly depending on where the lateral roots emerge from the adventitious root. In the hypothetical case where lateral roots receive the same O2 as the adventitious (i.e. near the root base), CH4 emissions at the base of a 4‐cm lateral root with typical characteristics were predicted to range from 0.32 to 0.47 ng s−1, while CH4 oxidation was predicted to range from 52.29 to 116.75 pg s−1 (Table 1). Given their lower porosity and thinner root diameters, individual emission and oxidation rates are lower in lateral compared to adventitious roots (Table 1). However, lateral roots have a greater total length compared to adventitious roots (an average of 59.6 m vs 22.9 m per plant; Fig. S6), and therefore, they could potentially contribute more to total CH4 emissions and oxidation. Further experimental work is needed to quantify the distribution of laterals along adventitious roots in rice and to analyze their effects on O2 diffusion, particularly given that long‐type laterals form barriers to impede ROL, whereas short‐type laterals do not (Noorrohmah et al., 2020). Abundant short laterals lacking barriers, which emerge from multiple adventitious roots and overlap extensively, likely constitute the bulk of the root mass. As a result, much of the soil volume explored by the root system might be largely devoid of methanogenesis. Consequently, CH4 emissions would depend primarily on the apical regions of the adventitious roots located at the periphery of the root ball. Selecting genotypes in which lateral roots emerge predominantly near the root base ensures an efficient O2 diffusion system to both laterals and adventitious (Armstrong et al., 1990). By contrast, when abundant laterals emerge evenly along the adventitious roots, O2 supply to the adventitious root apex is significantly reduced (Sorrell et al., 2000; Kirk, 2003) and therefore should facilitate more emissions.

The identification of specific root traits associated with reduced CH4 emissions and increased CH4 oxidation in the rhizosphere opens the possibility of developing cultivars with lower environmental impact through selection and breeding. The main difficulties lie in the complexity of phenotyping anatomical traits and the concomitant variation among them. For example, selecting genotypes with higher cortical porosity would increase rhizosphere oxidation and reduce CH4 emissions (Fig. 2), but this could also lead to the development of longer roots, which in turn would increase CH4 emissions (Fig. 5). The development of rice cultivars with tight barriers that impede gas diffusion, formed by deposits of suberin and glycerol esters in exodermal cell walls, has been suggested as a next step toward producing rice genotypes with reduced CH4 emissions (Jiménez & Pedersen, 2023). Recent advances in our understanding of the environmental triggering conditions, cellular localization, chemical composition and molecular regulation of these barriers in rice roots (Colmer et al., 2019; Shiono et al., 2022, 2024; Peralta Ogorek et al., 2024; Jiménez et al., 2024b, 2025) provide further support for this approach. A precise characterization of the anatomical and physiological traits influencing root aeration in the whole root system, including both adventitious and lateral roots, remains challenging and could be further refined in future studies. Nonetheless, the modeling approach used in this study successfully describes the bidirectional diffusion of O2 and CH4 through rice roots at a much finer scale than is possible with direct measurements. Because the model inputs were obtained from roots grown in stagnant nutrient solution, the absolute predicted fluxes should not be interpreted as direct estimates for paddy soils. Rather, the simulations isolate the direction and relative magnitude of individual‐trait effects under fixed boundary conditions and can be applied to comparable trait values in soil‐grown roots.

This study evaluated the complex variations in root anatomical and physiological traits of rice roots and used a modeling approach to embrace longitudinal variations in these traits and compute their potential influence in the bidirectional diffusion of O2 and CH4. Traits that enhance internal O2 diffusion, including increased cortical porosity, a reduced stelar radius, lower respiratory O2 consumption and the formation of apoplastic barriers impeding gas diffusion, were predicted to be associated with reduced CH4 emissions by enhancing rhizosphere oxygenation, thereby suppressing methanogenesis near the root and shifting the CH4‐production front away from the root epidermis, which increased resistance to CH4 diffusion. The modeling suggests that rice genotypes with shorter adventitious roots (i.e. 10 cm long in the simulations) could contribute to reduced CH4 emissions in cropping systems, even under variable microbial O2 consumption conditions such as those found in alternate wetting and drying irrigation schemes. Moreover, selecting rice genotypes with tight barriers to impede gas diffusion could significantly decrease CH4 emissions and enhance rhizosphere oxygenation. Although lateral roots are thinner, less porous, and exhibit lower potential for O2 and CH4 diffusion compared to adventitious roots, their extensive total length may significantly influence O2 and CH4 dynamics, warranting further investigations. Contrary to prevailing assumptions, our modeling suggests that increasing methanotroph activity in the rhizosphere should enhance CH4 emissions rather than reduce them, provided that the additional O2 demand is not compensated for by a reduction in non‐methanotrophic O2 consumption. Where total rhizospheric O2 consumption rises, the oxygenated rhizosphere contracts and the methanogenic front moves closer to the root, thereby increasing emissions.

Competing interests

None declared.

Author contributions

JCJ, WA and OP conceptualized the study. PL, MP, MCR, JAC and MFA selected the genotypes and contributed to the methodology. JCJ, ZS, PL and MP conducted experiments. JCJ and WA performed the formal analysis. JCJ wrote the original draft of the manuscript. JCJ, SZ, WA and OP reviewed and edited the manuscript. All authors approved the final version of the manuscript.

Disclaimer

The New Phytologist Foundation remains neutral with regard to jurisdictional claims in maps and in any institutional affiliations.

Supporting information

Fig. S1 Root anatomy and development of a suberized exodermis in basal (80 mm behind root tip) and apical (10 mm behind root tip) parts of adventitious roots of rice.

Fig. S2 Cortical porosity at the apical and basal parts of adventitious root and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S3 Respiratory O2 consumption at the apical and basal parts of adventitious roots and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S4 Root diameter at the apical and basal parts of adventitious and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S5 Root anatomy and development of a suberized exodermis in long‐type lateral roots of rice.

Fig. S6 Total root length and root surface area of adventitious and lateral roots for the six rice genotypes evaluated.

Table S1 Subspecies classification, mean root traits of the six rice genotypes and fold variation among genotypes.

Table S2 Gas properties and environmental conditions used in this study. Values are provided for a reference temperature of 30°C.

Table S3 Parameter values used for modeling the effect of root cortical porosity on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S4 Parameter values used for modeling the effect of cortex‐to‐stele ratio on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S5 Parameter values used for modeling the effect of root respiration on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S6 Parameter values used for modeling the effect of barriers to impede gas diffusion on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S7 Parameter values used for modeling the effect of root length on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S8 Parameter values used for modeling the effect of non‐methanotrophic (Qox) or methanotrophic O2 (Qmox) consumption in rhizosphere on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S9 Parameter values used for modeling the scenario in which methanotrophic O2 (Qmox) consumption in the rhizosphere increases CH4 emissions from the root base.

Table S10 Predicted CH4 emissions from the root base and CH4 oxidation in the rhizosphere from the six rice genotypes evaluated in this study.

Please note: Wiley is not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

NPH-252-1035-s001.pdf (565.7KB, pdf)

Acknowledgements

We are grateful to Jean Armstrong for extensive, thoughtful discussions that helped improve this manuscript. We thank Miller Escobar and Alfer Valencia for their assistance during the experiment setup and harvest process. JCJ was funded by the European Union under a Marie Skłodowska‐Curie Postdoctoral Fellowship (grant no. 101061962, SmartRoots) and by the Novo Nordisk Foundation (grant no. NNF23OC0084801). SZ gratefully acknowledges support from the Carbon Sequestration Fellowship (Bezos Earth Fund). OP was funded by two Danida grants (No. 19‐03‐KU and 25‐9 07‐KU).

Data availability

All data supporting the findings of this study are included within the article and its Supporting Information. See Tables S2–S9.

References

  1. Armstrong J, Armstrong W. 2005. Rice: sulfide‐induced barriers to root radial oxygen loss, Fe2+ and water uptake, and lateral root emergence. Annals of Botany 96: 625–638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Armstrong W. 1970. Rhizosphere Oxidation in Rice and other Species: A Mathematical Model Based on the Oxygen Flux Component. Physiologia Plantarum 23: 623–630. [Google Scholar]
  3. Armstrong W. 1979. Aeration in Higher Plants. In: Woolhouse HW, ed. Advances in botanical research, vol. 7. London, UK: Academic Press, 225–332. doi: 10.1016/S0065-2296(08)60089-0. [DOI] [Google Scholar]
  4. Armstrong W, Armstrong J, Beckett PM. 1990. Measurement and modelling of oxygen release from roots of Phragmites australis . In: Cooper PF, Findlater BC, eds. Constructed wetlands in water pollution control. Oxford, UK: Pergamon, 41–51. doi: 10.1016/B978-0-08-040784-5.50009-7. [DOI] [Google Scholar]
  5. Armstrong W, Beckett PM. 1987. Internal aeration and development of stelar anoxia in submerged roots: a multi‐shelled mathematical model combining axial diffusion of oxygen in the cortex with radial losses to the stele, the wall layers and the rhizosphere. New Phytologist 105: 221–245. [Google Scholar]
  6. Beckett PM, Armstrong W, Armstrong J. 2001. Mathematical modelling of methane transport by Phragmites: the potential for diffusion within the roots and rhizosphere. Aquatic Botany 69: 293–312. [Google Scholar]
  7. van Bodegom P, Goudriaan J, Leffelaar P. 2001a. A mechanistic model on methane oxidation in a rice rhizosphere. Biogeochemistry 55: 145–177. [Google Scholar]
  8. van Bodegom P, Stams F, Mollema L, Boeke S, Leffelaar P. 2001b. Methane oxidation and the competition for oxygen in the rice rhizosphere. Applied and Environmental Microbiology 67: 3586–3597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Brundrett MC, Kendrick B, Peterson CA. 1991. Efficient lipid staining in plant material with Sudan red 7B or fluorol [correction of fluoral] yellow 088 in polyethylene glycol‐glycerol. Biotechnic & Histochemistry 66: 111–116. [DOI] [PubMed] [Google Scholar]
  10. Butterbach‐Bahl, K. , Papen, H. , Rennenberg, H. 1997. Impact of gas transport through rice cultivars on methane emission from rice paddy fields. Plant, Cell & Environment 20(9): 1175–1183. doi: 10.1046/j.1365-3040.1997.d01-142.x [DOI] [Google Scholar]
  11. Chen Y, Li S, Zhang Y, Li T, Ge H, Xia S, Gu J, Zhang H, Lü B, Wu X et al. 2019. Rice root morphological and physiological traits interaction with rhizosphere soil and its effect on methane emissions in paddy fields. Soil Biology and Biochemistry 129: 191–200. [Google Scholar]
  12. Colmer TD. 2003a. Long‐distance transport of gases in plants: a perspective on internal aeration and radial oxygen loss from roots. Plant, Cell & Environment 26: 17–36. [Google Scholar]
  13. Colmer TD. 2003b. Aerenchyma and an inducible barrier to radial oxygen loss facilitate root aeration in upland, paddy and deep‐water rice (Oryza sativa L.). Annals of Botany 91 Spec No(2): 301–309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Colmer TD, Kotula L, Malik AI, Takahashi H, Konnerup D, Nakazono M, Pedersen O. 2019. Rice acclimation to soil flooding: low concentrations of organic acids can trigger a barrier to radial oxygen loss in roots. Plant, Cell & Environment 42: 2183–2197. [DOI] [PubMed] [Google Scholar]
  15. Colmer TD, Pedersen O. 2008. Oxygen dynamics in submerged rice (Oryza sativa). New Phytologist 178: 326–334. [DOI] [PubMed] [Google Scholar]
  16. Conrad R. 2007. Microbial Ecology of Methanogens and Methanotrophs. In: Advances in agronomy, vol. 96. San Diego, CA, USA: Academic Press, 1–63. doi: 10.1016/S0065-2113(07)96005-8. [DOI] [Google Scholar]
  17. Fumoto T, Kobayashi K, Li C, Yagi K, Hasegawa T. 2008. Revising a process‐based biogeochemistry model (DNDC) to simulate methane emission from rice paddy fields under various residue management and fertilizer regimes. Global Change Biology 14: 382–402. [Google Scholar]
  18. Gilbert B, Frenzel P. 1998. Rice roots and CH4 oxidation: the activity of bacteria, their distribution and the microenvironment. Soil Biology and Biochemistry 30: 1903–1916. [Google Scholar]
  19. Haque ANA, Uddin MK, Sulaiman MF, Amin AM, Hossain M, Solaiman ZM, Mosharrof M. 2022. Rice growth performance, nutrient use efficiency and changes in soil properties influenced by biochar under alternate wetting and drying irrigation. Sustainability 14: 7977. [Google Scholar]
  20. Holzapfel‐Pschorn A, Conrad R, Seiler W. 1986. Effects of vegetation on the emission of methane from submerged paddy soil. Plant and Soil 92: 223–233. [Google Scholar]
  21. Inubushi K, Sugii H, Watanabe I, Wassmann R. 2002. Evaluation of methane oxidation in rice plant–soil system. Nutrient Cycling in Agroecosystems 64: 71–77. [Google Scholar]
  22. Iqbal MF, Liu S, Zhu J, Zhao L, Qi T, Liang J, Luo J, Xiao X, Fan X. 2021. Limited aerenchyma reduces oxygen diffusion and methane emission in paddy. Journal of Environmental Management 279: 583. [DOI] [PubMed] [Google Scholar]
  23. Jiménez JC, Cardoso JA, Kotula L, Veneklaas EJ, Pedersen O, Colmer TD. 2021a. Root length is proxy for high‐throughput screening of waterlogging tolerance in Urochloa spp. grasses. Functional Plant Biology 48: 411–421. [DOI] [PubMed] [Google Scholar]
  24. Jiménez JC, Pedersen O. 2023. Mitigation of greenhouse gas emissions from rice via manipulation of key root traits. Rice 16: 24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Jiménez JC, Pellegrini E, Pedersen O, Nakazono M. 2021b. Radial oxygen loss from plant roots‐methods. Plants 10: 2322. doi: 10.3390/plants10112322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Jiménez JC, Armstrong W, Colmer TD, Pedersen O. 2024a. Overcoming constraints to measuring O2 diffusivity and consumption of intact roots. Plant Physiology 195: 283–286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Jiménez JC, Noorrohmah S, Suresh K, Zeisler‐Diehl VV, Peralta Ogorek LL, Herzog M, Pellegrini E, Nagai K, Ashikari M, Takahashi H et al. 2024b. Leaf Gas Film 1 promotes glycerol ester accumulation and formation of a tight root barrier to radial O2 loss in rice. Plant Physiology 196: 2437–2449. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Jiménez JC, Pedersen O. 2026. Oxygen consumption and diffusional resistance both determine maximum root length in flooded soils. Journal of Experimental Botany. doi: 10.1093/jxb/erag030. [DOI] [PubMed] [Google Scholar]
  29. Jiménez JC, Suresh K, Zeisler‐Diehl V, Oi T, Hirakawa T, Takahashi H, Schreiber L, Nakazono M. 2025. Formation of apoplastic barriers to radial O2 loss in rice roots: effects of low‐O2 and high‐Fe conditions, and the roles of suberin, glycerol esters, and iron plaques. Plant, Cell & Environment 48: 2937–2949. [DOI] [PubMed] [Google Scholar]
  30. Justin SHFW, Armstrong W. 1987. The anatomical characteristics of roots and plant responses to soil flooding. New Phytologist 106: 465–495. [Google Scholar]
  31. Kim WJ, Bui LT, Chun JB, McClung AM, Barnaby JY. 2018. Correlation between methane (CH4) emissions and root aerenchyma of rice varieties. Plant Breeding and Biotechnology 6: 381–390. [Google Scholar]
  32. Kirk GJ. 2004. Reduction and oxidation. In: The biogeochemistry of submerged soils. Chichester, UK: John Wiley & Sons, 93–134. doi: 10.1002/047086303X.ch4. [DOI] [Google Scholar]
  33. Kirk GJD. 2003. Rice root properties for internal aeration and efficient nutrient acquisition in submerged soil. New Phytologist 159: 185–194. [DOI] [PubMed] [Google Scholar]
  34. Li C, Mosier A, Wassmann R, Cai Z, Zheng X, Huang Y, Tsuruta H, Boonjawat J, Lantin R. 2004. Modeling greenhouse gas emissions from rice‐based production systems: sensitivity and upscaling. Global Biogeochemical Cycles 18: GB1043. doi: 10.1029/2003GB002045. [DOI] [Google Scholar]
  35. Li CS. 2000. Modeling trace gas emissions from agricultural ecosystems. Nutrient Cycling in Agroecosystems 58: 259–276. [Google Scholar]
  36. Li S, Zhang Y, Zhao J, van Groenigen KJ, Shen X, Zhang H, Gu J, Zhang W, Hui D, Chen Y et al. 2025. Water‐saving irrigation practices in rice paddies reverse the impact of root aerenchyma on methane emissions. Agriculture, Ecosystems & Environment 378: 109309. [Google Scholar]
  37. Maisch M, Lueder U, Kappler A, Schmidt C. 2019. Iron lung: how rice roots induce iron redox changes in the rhizosphere and create niches for microaerophilic Fe(II)‐oxidizing bacteria. Environmental Science & Technology Letters 6: 600–605. [Google Scholar]
  38. Majumdar A, Dubey PK, Giri B, Moulick D, Srivastava AK, Roychowdhury T, Bose S, Jaiswal MK. 2023. Combined effects of dry‐wet irrigation, redox changes and microbial diversity on soil nutrient bioavailability in the rice field. Soil and Tillage Research 232: 752. [Google Scholar]
  39. Noorrohmah S, Takahashi H, Nakazono M. 2020. Formation of a barrier to radial oxygen loss in L‐type lateral roots of rice. Plant Root 14: 33–41. [Google Scholar]
  40. Oikawa PY, Jenerette GD, Knox SH, Sturtevant C, Verfaillie J, Dronova I, Poindexter CM, Eichelmann E, Baldocchi DD. 2016. Evaluation of a hierarchy of models reveals importance of substrate limitation for predicting carbon dioxide and methane exchange in restored wetlands. Journal of Geophysical Research: Biogeosciences 122: 145–167. [Google Scholar]
  41. Pedersen O, Sauter M, Colmer TD, Nakazono M. 2021. Regulation of root adaptive anatomical and morphological traits during low soil oxygen. New Phytologist 229: 42–49. [DOI] [PubMed] [Google Scholar]
  42. Peralta Ogorek LL, Jiménez JC, Visser EJW, Takahashi H, Nakazono M, Shabala S, Pedersen O. 2024. Outer apoplastic barriers in roots: prospects for abiotic stress tolerance. Functional Plant Biology 51: FP23133. doi: 10.1071/FP23133. [DOI] [PubMed] [Google Scholar]
  43. Ragsdale SW, Raugei S, Ginovska B, Wongnate T. 2017. Biochemistry of methyl‐coenzyme M reductase. In: Zamble D, Rowińska‐Żyrek M, Kozlowski H, eds. The biological chemistry of nickel. Cambridge, UK: The Royal Society of Chemistry. doi: 10.1039/9781788010580-00149. [DOI] [Google Scholar]
  44. Roy RK, Hosseiniyan Khatibi SM, Kim S‐R, Trijatmiko KR, Diaz MGQ, Ocampo ETM, Hernandez JE, Pirmoradi S, Henry A, Kohli A. 2025b. A robust model based on root morphological and anatomical features to distinguish high and low methane emission rice varieties through machine learning approaches. In Silico Plants 7: diaf017. [Google Scholar]
  45. Roy RK, Misra G, Sharma S, Pahi B, Hosseiniyan Khatibi SM, Trijatmiko KR, Kim SR, Hernandez JE, Henry A, Sreenivasulu N et al. 2025a. Genetic dissection of root traits in a rice ‘global MAGIC’ population for candidate traits to breed for reduced methane emission. Frontiers in Plant Science 16: 1616424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Scheller S, Goenrich M, Boecher R, Thauer RK, Jaun B. 2010. The key nickel enzyme of methanogenesis catalyses the anaerobic oxidation of methane. Nature 465: 606–608. [DOI] [PubMed] [Google Scholar]
  47. Schütz H, Seiler W, Conrad R. 1989. Processes involved in formation and emission of methane in rice paddies. Biogeochemistry 7: 33–53. [Google Scholar]
  48. Seethepalli A, Dhakal K, Griffiths M, Guo H, Freschet GT, York LM. 2021. rhizovision explorer: open‐source software for root image analysis and measurement standardization. AoB Plants 13: plab056. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Shiono K, Ejiri M, Sawazaki Y, Egishi Y, Tsunoda T. 2024. Low nitrate under waterlogging triggers exodermal suberization to form a barrier to radial oxygen loss in rice roots. Plant Physiology 196: 551–563. [DOI] [PubMed] [Google Scholar]
  50. Shiono K, Ogawa S, Yamazaki S, Isoda H, Fujimura T, Nakazono M, Colmer TD. 2011. Contrasting dynamics of radial O2‐loss barrier induction and aerenchyma formation in rice roots of two lengths. Annals of Botany 107: 89–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Shiono K, Yoshikawa M, Kreszies T, Yamada S, Hojo Y, Matsuura T, Mori IC, Schreiber L, Yoshioka T. 2022. Abscisic acid is required for exodermal suberization to form a barrier to radial oxygen loss in the adventitious roots of rice (Oryza sativa). New Phytologist 233: 655–669. [DOI] [PubMed] [Google Scholar]
  52. Sorrell B, Mendelssohn IA, Mckee KL, Woods RA. 2000. Ecophysiology of wetland plant roots: a modelling comparison of aeration in relation to species distribution. Annals of Botany 86: 675–685. [Google Scholar]
  53. Thauer RK. 2019. Methyl (alkyl)‐coenzyme M reductases: nickel F‐430‐containing enzymes involved in anaerobic methane formation and in anaerobic oxidation of methane or of short chain alkanes. Biochemistry 58: 5198–5220. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Watanabe I, Hashimoto T, Shimoyama A. 1997. Methane‐oxidizing activities and methanotrophic populations associated with wetland rice plants. Biology and Fertility of Soils 24: 261–265. [Google Scholar]
  55. Waters I, Armstrong W, Thompson CJ, Setter TL, Adkins S, Gibbs J, Greenway H. 1989. Diurnal changes in radial oxygen loss and ethanol metabolism in roots of submerged and non‐submerged rice seedlings. New Phytologist 113: 439–451. [Google Scholar]
  56. Wiengweera A, Greenway H, Thomson CJ. 1997. The use of agar nutrient solution to simulate lack of convection in waterlogged soils. Annals of Botany 80: 115–123. [Google Scholar]
  57. Yamauchi T, Nakazono M, Inukai Y, Tsutsumi N. 2020. Distance‐to‐time conversion using Gompertz Model reveals age‐dependent aerenchyma formation in rice roots. Plant Physiology 183: 1424–1427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Yao J, Fu Y, Yu Z, Liu T, Clough TJ, Hu C, Qin S. 2024a. Interaction of rice root Fe plaque with radial oxygen loss enhances paddy‐soil N2O emission by increasing •OH production and subsequently inhibiting N2O reduction. Soil Biology & Biochemistry 195: 109475. [Google Scholar]
  59. Yao J, Song W, Wang C, Clough T, Qin S. 2025. Rice root Fe plaque‐induced hydroxyl radicals increase paddy soil CO2 emissions. Environmental Science & Technology 59: 15142–15150. [DOI] [PubMed] [Google Scholar]
  60. Yao J, Xie M, Yu L, Liu T, Clough TJ, Wrage‐Mönnig N, Luo J, Hu C, Ge T, Zhou S et al. 2024b. Rice root Fe plaque increases paddy soil CH4 emissions via the promotion of electron transfer for syntrophic methanogenesis. Soil Biology & Biochemistry 191: 109332. [Google Scholar]
  61. Zheng H, Fu Z, Zhong J, Long W. 2018. Low methane emission in rice cultivars with high radial oxygen loss. Plant and Soil 431: 119–128. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Fig. S1 Root anatomy and development of a suberized exodermis in basal (80 mm behind root tip) and apical (10 mm behind root tip) parts of adventitious roots of rice.

Fig. S2 Cortical porosity at the apical and basal parts of adventitious root and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S3 Respiratory O2 consumption at the apical and basal parts of adventitious roots and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S4 Root diameter at the apical and basal parts of adventitious and at the mid‐segment of lateral roots for the six rice genotypes evaluated.

Fig. S5 Root anatomy and development of a suberized exodermis in long‐type lateral roots of rice.

Fig. S6 Total root length and root surface area of adventitious and lateral roots for the six rice genotypes evaluated.

Table S1 Subspecies classification, mean root traits of the six rice genotypes and fold variation among genotypes.

Table S2 Gas properties and environmental conditions used in this study. Values are provided for a reference temperature of 30°C.

Table S3 Parameter values used for modeling the effect of root cortical porosity on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S4 Parameter values used for modeling the effect of cortex‐to‐stele ratio on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S5 Parameter values used for modeling the effect of root respiration on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S6 Parameter values used for modeling the effect of barriers to impede gas diffusion on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S7 Parameter values used for modeling the effect of root length on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S8 Parameter values used for modeling the effect of non‐methanotrophic (Qox) or methanotrophic O2 (Qmox) consumption in rhizosphere on CH4 emissions from the root base and CH4 oxidation in the rhizosphere.

Table S9 Parameter values used for modeling the scenario in which methanotrophic O2 (Qmox) consumption in the rhizosphere increases CH4 emissions from the root base.

Table S10 Predicted CH4 emissions from the root base and CH4 oxidation in the rhizosphere from the six rice genotypes evaluated in this study.

Please note: Wiley is not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

NPH-252-1035-s001.pdf (565.7KB, pdf)

Data Availability Statement

All data supporting the findings of this study are included within the article and its Supporting Information. See Tables S2–S9.

Articles from The New Phytologist are provided here courtesy of Wiley

RESOURCES