Rice Science ›› 2025, Vol. 32 ›› Issue (6): 813-830.DOI: 10.1016/j.rsci.2025.08.003
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Kossi Lorimpo Adjah1, Vimal Kumar Semwal2, Nana Kofi Abaka Amoah1, Isaac Tawiah1, Negussie Zenna3, Raafat Elnamaky4, Koichi Futakuchi5, Elliott Ronald Dossou-Yovo5, Shailesh Yadav1(
)
Received:2025-03-29
Accepted:2025-08-28
Online:2025-11-28
Published:2025-12-04
Contact:
Shailesh Yadav (Kossi Lorimpo Adjah, Vimal Kumar Semwal, Nana Kofi Abaka Amoah, Isaac Tawiah, Negussie Zenna, Raafat Elnamaky, Koichi Futakuchi, Elliott Ronald Dossou-Yovo, Shailesh Yadav. Designing Climate-Resilient Rice Production Systems: Leveraging Genomics for Low-Emission Rice Varieties[J]. Rice Science, 2025, 32(6): 813-830.
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Fig. 1. Different emitted greenhouse gases (CH4, N2O, and CO2) from both lowland and upland rice production ecosystems and photosynthate or sucrose allocation to sink (panicles and grains) and roots. Greenhouse gases (GHGs) are vented to the atmosphere via plant-mediated diffusion and ebullition through soil. The high accumulation of photosynthate or sucrose in the panicles or grains leads to increased yield and low GHG emissions, while that in the roots leads to high GHG emissions (Jiménez and Pedersen, 2023; Kwon et al, 2023).
Fig. 2. Factors influencing greenhouse gas emissions from rice fields.
Fig. 3. Low greenhouse gas emission technologies and practices for rice fields.
| Rice variety | CH4 emission | N2O emission | Global warming potential | Reference |
|---|---|---|---|---|
| Hanyou 3 | Decreased by 60%-83% | Increased by 9%-11% | Decreased by 25% | Xu et al, |
| Hanyou 73 | Decreased to zero | Increased by 7.6% | Decreased by 95% | Zhang et al, |
| Hanyou 73 | Decreased by 8.2%-21.64% | Decreased by 20.69%-76.56% | Reduced by 11.48%-20.83% | Zhang et al, |
| 7Y88 and 7Y370 | Decreased by 8.5%-10.51% | Decreased by 11.17%-13.76% | Reduced by 10.66%-13.13% | Feng et al, |
Table 1. Drought-tolerant rice variety and water-saving effects on greenhouse gase-emission.
| Rice variety | CH4 emission | N2O emission | Global warming potential | Reference |
|---|---|---|---|---|
| Hanyou 3 | Decreased by 60%-83% | Increased by 9%-11% | Decreased by 25% | Xu et al, |
| Hanyou 73 | Decreased to zero | Increased by 7.6% | Decreased by 95% | Zhang et al, |
| Hanyou 73 | Decreased by 8.2%-21.64% | Decreased by 20.69%-76.56% | Reduced by 11.48%-20.83% | Zhang et al, |
| 7Y88 and 7Y370 | Decreased by 8.5%-10.51% | Decreased by 11.17%-13.76% | Reduced by 10.66%-13.13% | Feng et al, |
| Management strategya | CH4-emission change | N2O-emission change | Global warming potential change | Location | Reference |
|---|---|---|---|---|---|
| AWD | Decreased by 51%-65% | Increased by 70% | Decreased by 47% | China and Vietnam | Xu et al, |
| AWD-FWI | Decreased by 60% | Increased by 9% | Decreased by 20%-30% | China | Xu et al, |
| AWD-FDI | Decreased by 83% | Increased by 11% | Decreased by 30%-35% | China | Xu et al, |
| MSD | Decreased by 52% | Increased by 242% | Decreased by 47% | China and Southeast Asia | Liu et al, |
| SRI | Decreased by 61% | Increased by 49% | Decreased by 27% | India | Jain et al, |
| Dry DSR | Decreased by 80% | Increased by 114% | Decreased by 76% | China | Tao et al, |
| Wet DSR | Decreased by 62% | Increased by 49% | Decreased by 57% | China | Tao et al, |
Table 2. Effects of management strategies on CH4, N2O emissions, and global warming potential across multiple study locations.
| Management strategya | CH4-emission change | N2O-emission change | Global warming potential change | Location | Reference |
|---|---|---|---|---|---|
| AWD | Decreased by 51%-65% | Increased by 70% | Decreased by 47% | China and Vietnam | Xu et al, |
| AWD-FWI | Decreased by 60% | Increased by 9% | Decreased by 20%-30% | China | Xu et al, |
| AWD-FDI | Decreased by 83% | Increased by 11% | Decreased by 30%-35% | China | Xu et al, |
| MSD | Decreased by 52% | Increased by 242% | Decreased by 47% | China and Southeast Asia | Liu et al, |
| SRI | Decreased by 61% | Increased by 49% | Decreased by 27% | India | Jain et al, |
| Dry DSR | Decreased by 80% | Increased by 114% | Decreased by 76% | China | Tao et al, |
| Wet DSR | Decreased by 62% | Increased by 49% | Decreased by 57% | China | Tao et al, |
| Breeding approach | Target trait | Mechanism | GHG impact | Reduction (%) | Reference |
|---|---|---|---|---|---|
| Transgenic | Reduced root exudates (insertion of SUSIBA2) | Reduce root exudates and suppress methanogenesis (allocation of photosynthates to aboveground biomass over roots) | Decreased CH4 | 50-90 | Su et al, |
| Transgenic | Root exudate modification (H2 oxidation) via overexpressing gene plant peptides containing sulfated tyrosine | Reduction of H2 (available for hydrogenotrophic methanogenesis) | Decreased CH4 | 38-58 | Shi et al, |
| Gene/QTL pyramiding and multi-omics | Multi-trait improvement (Nitrogen-use efficiency, drought, low-input, etc.) | Combine high yield with low-input demand and enhanced soil-microbe balance | Decreased CH4 | 37 | Taghavi et al, |
| Mutagenesis via knockdown | Reduced aerenchyma formation (insertion of Tos17 and T-DNA in OsLSD1.1 mutant) | Limit CH4 transport via aerenchyma in roots | Decreased CH4 | 27-36 | Iqbal et al, |
| Gene/QTL discovery | qTN1-2, qTN3-1, qTN3-2, qTN3-3, qTN4-1, qRB3-1, and qRB5-1 | Associated with high tillering and root biomass during the maximum tillering stage at the peak of emissions | - | - | Barnaby et al, |
| Metabolomic and transcriptomic | Loss-of-function gs3 mutant allele and root exudate transporter genes (OsALMT1, OsSWEET11, OsSWEET14, and OsMFS1) | Alter carbon exudates (allocation of photosynthates to aboveground biomass over roots) and reduces methanogens activities | Decreased CH4 | 16-37 | Kwon et al, |
| Conventional breeding | Fumarate and ethanol production | Fumarate promotes CH4 production and ethanol mitigates CH4 emissions by inhibiting fumarate synthesis in the root | Decreased CH4 | 70 | Jin et al, |
| Hybrid breeding | High biomass, high yield, short duration, and elevated carbon sequestration capacity | Carbon substrates allocation to the grain and biomass over the roots | Decreased CH4 | 52 | Khatibi et al, |
Table 3. Rice breeding strategies for mitigating greenhouse gas emissions.
| Breeding approach | Target trait | Mechanism | GHG impact | Reduction (%) | Reference |
|---|---|---|---|---|---|
| Transgenic | Reduced root exudates (insertion of SUSIBA2) | Reduce root exudates and suppress methanogenesis (allocation of photosynthates to aboveground biomass over roots) | Decreased CH4 | 50-90 | Su et al, |
| Transgenic | Root exudate modification (H2 oxidation) via overexpressing gene plant peptides containing sulfated tyrosine | Reduction of H2 (available for hydrogenotrophic methanogenesis) | Decreased CH4 | 38-58 | Shi et al, |
| Gene/QTL pyramiding and multi-omics | Multi-trait improvement (Nitrogen-use efficiency, drought, low-input, etc.) | Combine high yield with low-input demand and enhanced soil-microbe balance | Decreased CH4 | 37 | Taghavi et al, |
| Mutagenesis via knockdown | Reduced aerenchyma formation (insertion of Tos17 and T-DNA in OsLSD1.1 mutant) | Limit CH4 transport via aerenchyma in roots | Decreased CH4 | 27-36 | Iqbal et al, |
| Gene/QTL discovery | qTN1-2, qTN3-1, qTN3-2, qTN3-3, qTN4-1, qRB3-1, and qRB5-1 | Associated with high tillering and root biomass during the maximum tillering stage at the peak of emissions | - | - | Barnaby et al, |
| Metabolomic and transcriptomic | Loss-of-function gs3 mutant allele and root exudate transporter genes (OsALMT1, OsSWEET11, OsSWEET14, and OsMFS1) | Alter carbon exudates (allocation of photosynthates to aboveground biomass over roots) and reduces methanogens activities | Decreased CH4 | 16-37 | Kwon et al, |
| Conventional breeding | Fumarate and ethanol production | Fumarate promotes CH4 production and ethanol mitigates CH4 emissions by inhibiting fumarate synthesis in the root | Decreased CH4 | 70 | Jin et al, |
| Hybrid breeding | High biomass, high yield, short duration, and elevated carbon sequestration capacity | Carbon substrates allocation to the grain and biomass over the roots | Decreased CH4 | 52 | Khatibi et al, |
| Selection stage | Trait profile for progeny screening |
|---|---|
| Pre-breeding stage | Deep rooting and expanded root distributions, along with the formation of porous roots and enlarged aerenchyma, contribute to reduced or eliminated non-productive tillers, increased aboveground biomass, and higher grain yields. Additionally, there are implications for CH4, N2O, and CO2 emissions, as well as variations in methanogen abundance across the rhizospheres of different cultivars. Observations include reduced levels of glucose and carbohydrates in the roots, alongside a high abundance of sugar transporter genes in the panicles and grains |
| Early stage (BCnF1 to BCnF4 generations) | Deep rooting and expanded root distributions, the development of porous roots with enlarged aerenchyma, reduced or eliminated non-productive tillers, increased aboveground biomass, and enhanced grain yields |
| Late stage (BCnF5 and BCnF6 generations) | Methanogen abundance varies across the rhizospheres of each cultivar, alongside reduced levels of glucose and carbohydrates in the roots. Notably, there is a high abundance of sugar transporter genes, such as SUT-C, SWEET, OsSUT1, OsSUT5, and OsDOF11, in the panicles and grains. Conversely, there is a lower abundance of carbohydrate and root exudate transporter genes (including OsALMT1, OsSWEET11, OsSWEET14, and OsMFS) in the roots. These factors are associated with emissions of CH4, N2O, and CO2 |
Table 4. Stratified traits profile to consider when developing low greenhouse gas emission rice varieties.
| Selection stage | Trait profile for progeny screening |
|---|---|
| Pre-breeding stage | Deep rooting and expanded root distributions, along with the formation of porous roots and enlarged aerenchyma, contribute to reduced or eliminated non-productive tillers, increased aboveground biomass, and higher grain yields. Additionally, there are implications for CH4, N2O, and CO2 emissions, as well as variations in methanogen abundance across the rhizospheres of different cultivars. Observations include reduced levels of glucose and carbohydrates in the roots, alongside a high abundance of sugar transporter genes in the panicles and grains |
| Early stage (BCnF1 to BCnF4 generations) | Deep rooting and expanded root distributions, the development of porous roots with enlarged aerenchyma, reduced or eliminated non-productive tillers, increased aboveground biomass, and enhanced grain yields |
| Late stage (BCnF5 and BCnF6 generations) | Methanogen abundance varies across the rhizospheres of each cultivar, alongside reduced levels of glucose and carbohydrates in the roots. Notably, there is a high abundance of sugar transporter genes, such as SUT-C, SWEET, OsSUT1, OsSUT5, and OsDOF11, in the panicles and grains. Conversely, there is a lower abundance of carbohydrate and root exudate transporter genes (including OsALMT1, OsSWEET11, OsSWEET14, and OsMFS) in the roots. These factors are associated with emissions of CH4, N2O, and CO2 |
Fig. 4. Integration of low greenhouse gas (GHG) emission traits into elite rice breeding pipeline. MAS, Marker-assisted selection; GS, Genomic selection; GWAS, Genome-wide association study; CRISPR, Clustered regularly interspaced short palindromic repeats; AWD, Alternative wetting and drying; DSR, Direct-seeded rice.
Fig. 5. Decision tree for selecting breeding strategies for low greenhouse gas emission rice. MABC, Marker-assisted backcrossing; NUE, Nitrogen use efficiency; GWAS, Genome-wide association study; CRISPR, Clustered regularly interspaced short palindromic repeats; AWD, Alternative Wetting and Drying; DSR, Direct-seeded rice.
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