Breeding rice for a changing climate by improving adaptations to water saving technologies.

Publisher: Springer Country of Publication: Germany NLM ID: 0145600 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-2242 (Electronic) Linking ISSN: 00405752 NLM ISO Abbreviation: Theor Appl Genet Subsets: MEDLINE

Original Publication: Berlin, New York, Springer

Adaptation, Physiological* ; Climate Change* ; Plant Breeding*; Oryza/*physiology ; Water/*metabolism; Oryza/genetics ; Oryza/metabolism ; Temperature

Climate change is expected to increasingly affect rice production through rising temperatures and decreasing water availability. Unlike other crops, rice is a main contributor to greenhouse gas emissions due to methane emissions from flooded paddy fields. Climate change can therefore be addressed in two ways in rice: through making the crop more climate resilient and through changes in management practices that reduce methane emissions and thereby slow global warming. In this review, we focus on two water saving technologies that reduce the periods lowland rice will be grown under fully flooded conditions, thereby improving water use efficiency and reducing methane emissions. Rice breeding over the past decades has mostly focused on developing high-yielding varieties adapted to continuously flooded conditions where seedlings were raised in a nursery and transplanted into a puddled flooded soil. Shifting cultivation to direct-seeded rice or to introducing non-flooded periods as in alternate wetting and drying gives rise to new challenges which need to be addressed in rice breeding. New adaptive traits such as rapid uniform germination even under anaerobic conditions, seedling vigor, weed competitiveness, root plasticity, and moderate drought tolerance need to be bred into the current elite germplasm and to what extent this is being addressed through trait discovery, marker-assisted selection and population improvement are reviewed.
(© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Anand S, York LM (2020). RhizoVision Explorer- Interactive software for generalized root image analysis designed for everyone Zenodo.
Ali N, Li D, Eltahawy MS, Abdulmajid D, Bux L, Liu E, Dang X, Hong D (2020) Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping. BMC Genet. https://doi.org/10.1186/s12863-020-0811-3. (PMID: 10.1186/s12863-020-0811-3319484086966888)
Anandan A, Mahender A, Sah RP, Bose LK, Subudhi H, Meher J, Reddy JN, Ali J (2020) Non-destructive phenotyping for early seedling vigor in direct-seeded rice. Plant Methods. https://doi.org/10.1186/s13007-020-00666-6. (PMID: 10.1186/s13007-020-00666-6329739137507283)
Backhaus A, Kuwabara A, Bauch M, Monk N, Sanguinetti G, Fleming A (2010) Leafprocessor: a new leaf phenotyping tool using contour bending energy and shape cluster analysis. New Phytol 187:251–261. https://doi.org/10.1111/j.1469-8137.2010.03266.x. (PMID: 10.1111/j.1469-8137.2010.03266.x20456045)
Belder P, Bouman BAM, Spiertz JHJ, Cabangon R, Guoan L, Quilang EJP, Yuanhua Li, Tuong TP (2004) Effect of water and nitrogen management on water use and yield of irrigated rice. Agri Water Manag 65:193–210. (PMID: 10.1016/j.agwat.2003.09.002)
Bernier J, Kumar A, Ramaiah V, Spaner D, Atlin G (2007) A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Science 47(2):507–516. https://doi.org/10.2135/cropsci2006.07.0495. (PMID: 10.2135/cropsci2006.07.0495)
Bouman BAM, Tuong TP (2001) Field water management to save water and increase its productivity in irrigated lowland rice. Agric Water Manag 49:11–30. (PMID: 10.1016/S0378-3774(00)00128-1)
Bouman BAM, Lampayan RM, Tuong TP (2007) Water Management in Irrigated Rice: Coping with Water Scarcity. International Rice Research Institute.
Bylesjö M, Segura V, Soolanayakanahally RY, Rae AM, Trygg J, Gustafsson P, Jansson S, Street NR (2008) LAMINA: a tool for rapid quantification of leaf size and shape parameters. BMC Plant Biol 8:82. https://doi.org/10.1186/1471-2229-8-82. (PMID: 10.1186/1471-2229-8-82186473992500018)
Carminati A, Passioura JB, Zarebanadkouki M, Ahmed MA, Ryan PR, Watt M, Delhaize E (2017) Root hairs enable high transpiration rates in drying soils. New Phytol 216:771–781. https://doi.org/10.1111/nph.14715. (PMID: 10.1111/nph.1471528758687)
Carrijo DR, Lundy ME, Linquist BA (2017) Rice yields and water use under alternate wetting and drying irrigation: A meta-analysis. Field Crops Res 203:173–180. (PMID: 10.1016/j.fcr.2016.12.002)
Cheng X, Cheng J, Huang X, Lai Y, Wang L, Du W, Wan Z, Zhang H (2013) Dynamic quantitative trait loci analysis of seed reserve utilization during three germination stages in rice. PLoS ONE 8(11):e80002. https://doi.org/10.1371/journal.pone.0080002. (PMID: 10.1371/journal.pone.0080002242445923823834)
Cobb JN, Biswas PS, Platten JD (2019) Back to the future: revisiting MAS as a tool for modern plant breeding. Theor Appl Genet 132(3):647–667. https://doi.org/10.1007/s00122-018-3266-4. (PMID: 10.1007/s00122-018-3266-430560465)
Cobb JN, Juma RU, Biswas PS, Arbelaez JD, Rutkoski J, Atlin G, Hagen T, Quinn M, Ng EH (2019) Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder’s equation. Theor Appl Genet 132(3):627–645. https://doi.org/10.1007/s00122-019-03317-0. (PMID: 10.1007/s00122-019-03317-0308249726439161)
Colmer TD, Cox MCH, Voesenek LACJ (2006) Root aeration in rice (Oryza sativa): evaluation of oxygen, carbon dioxide, and ethylene as possible regulators of root acclimatizations. New Phytol 170:767–778. https://doi.org/10.1111/j.1469-8137.2006.01725.x. (PMID: 10.1111/j.1469-8137.2006.01725.x16684237)
Condon AG, Richards RA, Rebetzke GJ, Farquhar GD (2004) Breeding for high water-use efficiency. J Exp Bot 55(407):2447–2460. https://doi.org/10.1093/jxb/erh277. (PMID: 10.1093/jxb/erh27715475373)
Cordero-Lara KI, Kim HJ, Tai TH (2016) Identification of seedling vigor-associated quantitative trait loci in temperate japonica rice. Plant Breed Biotechnol 4(4):426–440. https://doi.org/10.9787/PBB.2016.4.4.426. (PMID: 10.9787/PBB.2016.4.4.426)
Dai A (2013) Increasing drought under global warming in observations and models. Nature Climate Change 3:52–58. https://doi.org/10.1038/nclimate1633. (PMID: 10.1038/nclimate1633)
Das A, Schneider H, Burridge J, Martinez Ascanio AK, Wojciechowski T, Topp CN, Lynch JP, Weitz JS, Bucksch A (2015) Digital imaging for root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics. Plant Methods 11:51. https://doi.org/10.1186/s13007-015-0093-3. (PMID: 10.1186/s13007-015-0093-3265350514630929)
de Bauw P, Mai TH, Schnepf A, Merckx R, Smolders E, Vanderborght J (2020) A functional-structural model of upland rice root systems reveals the importance of laterals and growing root tips for phosphate uptake from wet and dry soils. Annal Bot 126(4):789–806. https://doi.org/10.1093/aob/mcaa120. (PMID: 10.1093/aob/mcaa120)
de Brauw. (2007, February). Seasonal migration and agriculture in Vietnam. Paper presented at the workshop on Migration, Transfers and Household Economic Decision Making, Rome, Italy.
Dechorgnat J, Nguyen CT, Armengaud P, Jossier M, Diatloff E, Filleur S, Daniel-Vedele F (2011) From the soil to the seeds: the long journey of nitrate in plants. J Exp Bot 62:1349–1359. (PMID: 10.1093/jxb/erq409)
Devia CA, Rojas JP, Petro E, Martinez C, Mondragon IF, Patino D, Rebolledo MC, Colorado J (2019) High-throughput biomass estimation in rice crops using UAV multispectral imagery. J Intell Robot Syst 96:573–589. https://doi.org/10.1007/s10846-019-01001-5. (PMID: 10.1007/s10846-019-01001-5)
Dinh T, Choi I, Son Y, Kim J (2016) A review on non-dispersive infrared gas sensors: Improvement of sensor detection limit and interference correction. Sens Actuators B Chem 231:529–538. https://doi.org/10.1016/j.snb.2016.03.040. (PMID: 10.1016/j.snb.2016.03.040)
Dixit S, Swamy BPM, Vikram P, Ahmed HU, Sta Cruz MT, Amante M, Atri D, Leung H, Kumar A (2012) Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities. Theor Appl Genet 125(1):155–169. https://doi.org/10.1007/s00122-012-1823-9. (PMID: 10.1007/s00122-012-1823-922361948)
Dixit S, Huang BE, Sta Cruz MT, Maturan PT, Ontoy JCE, Kumar A (2014) QTLs for tolerance of drought and breeding for tolerance of abiotic and biotic stress: An integrated approach. PLoS ONE. https://doi.org/10.1371/journal.pone.0109574. (PMID: 10.1371/journal.pone.0109574255419984277318)
Dixit S, Singh A, Sta Cruz MT, Maturan PT, Amante M, Kumar A (2014) Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities. BMC Genet. https://doi.org/10.1186/1471-2156-15-16. (PMID: 10.1186/1471-2156-15-16248859904048250)
Dixit S, Grondin A, Lee C-R, Henry A, Olds T-M, Kumar A (2015) Understanding rice adaptation to varying agro-ecosystems: trait interactions and quantitative trait loci. BMC Genet. https://doi.org/10.1186/s12863-015-0249-1. (PMID: 10.1186/s12863-015-0249-1262436264526302)
Dixit S, Singh A, Sandhu N, Bhandari A, Vikram P, Kumar A (2017) Combining drought and submergence tolerance in rice: marker-assisted breeding and QTL combination effects. Mol Breed. https://doi.org/10.1007/s11032-017-0737-2. (PMID: 10.1007/s11032-017-0737-2291518045670188)
Duan B, Fang S, Zhu R, Wu X, Wang S, Gong Y, Peng Y (2019) Remote estimation of rice yield with unmanned aerial vehicle (UAV) data and spectral mixture analysis. Front Plant Sci. https://doi.org/10.3389/fpls.2019.00204. (PMID: 10.3389/fpls.2019.00204321749276884059)
Fartyal D, Agarwal A, James D, Borphukan B, Ram B, Sheri V, Agrawal PK, Achary VMM, Reddy MK (2018) Developing dual herbicide tolerant transgenic rice plants for sustainable weed management. Sci Rep 8(1):11598–11598. https://doi.org/10.1038/s41598-018-29554-9. (PMID: 10.1038/s41598-018-29554-9300728106072789)
Fukuda A, Kondo K, Ikka T, Takai T, Tanabata T, Yamamoto T (2018) A novel QTL associated with rice canopy temperature difference affects stomatal conductance and leaf photosynthesis. Breed Sci 68(3):305–315. https://doi.org/10.1270/jsbbs.17129. (PMID: 10.1270/jsbbs.17129301007976081301)
Galeng-Lawilao J, Kumar A, De Waele D (2018) QTL mapping for resistance to and tolerance for the rice root-knot nematode Meloidogyne graminicola. BMC Genet 19(1):53. https://doi.org/10.1186/s12863-018-0656-1. (PMID: 10.1186/s12863-018-0656-1300818176080554)
Galeng-Lawilao J, Swamy BPM, Hore TK, Kumar A, Waele DD (2020) Identification of quantitative trait loci underlying resistance and tolerance to the rice root-knot nematode, Meloidogyne graminicola, in Asian rice (Oryza sativa). Mol Breed. https://doi.org/10.1007/s11032-020-01137-5. (PMID: 10.1007/s11032-020-01137-5)
Ghosal S, Casal C, Quilloy FA, Septiningsih EM, Mendioro MS, Dixit S (2019) Deciphering genetics underlying stable anaerobic germination in rice: phenotyping, QTL identification, and interaction analysis. Rice 12(1):50. https://doi.org/10.1186/s12284-019-0305-y. (PMID: 10.1186/s12284-019-0305-y313093516629739)
Ghosal S, Quilloy FA, Casal C, Septiningsih EM, Mendioro MS, Dixit S (2020) Trait-based mapping to identify the genetic factors underlying anaerobic germination of rice: Phenotyping, GXE, and QTL mapping. BMC Genet 21(1):1–13. https://doi.org/10.1186/s12863-020-0808-y. (PMID: 10.1186/s12863-020-0808-y)
Grenier C, Cao T-V, Ospina Y, Quintero C, Châtel MH, Tohme J, Courtois B, Ahmadi N (2015) Accuracy of genomic selection in a rice synthetic population developed for recurrent selection breeding. PLoS ONE 10(8):e0136594. https://doi.org/10.1371/journal.pone.0136594. (PMID: 10.1371/journal.pone.0136594263134464551487)
GRiSP (Global Rice Science Partnership). (2013). Rice almanac, 4th edition. Los Baños (Philippines): International Rice Research Institute. 283 p.
Grondin A, Dixit S, Torres R, Venkateshwarlu C, Rogers E, Mitchell-Olds T, Benfey PN, Kumar A, Henry A (2018) Physiological mechanisms contributing to the QTL qDTY(3.2) effects on improved performance of rice Moroberekan x Swarna BC(2)F(3:4) lines under drought. Rice 11(1):43–43. https://doi.org/10.1186/s12284-018-0234-1. (PMID: 10.1186/s12284-018-0234-1300660526068063)
Hartmann A, Czauderna T, Hoffmann R, Stein N, & Schreiber F (2011). HTPheno: An image analysis pipeline for high-throughput plant phenotyping. BMC Bioinformatics, 12(148).
Hasan E (2013) Proposing mitigation strategies for reducing the impact of rice cultivation on climate change in Egypt. Water Sci 27(54):69–77. https://doi.org/10.1016/j.wsj.2013.12.007. (PMID: 10.1016/j.wsj.2013.12.007)
Hasegawa T, Ishimaru T, Kondo M, Kuwagata T, Yoshimoto M, Fukuoka M (2011) Spikelet sterility of rice observed in the record hot summer of 2007 and the factors associated with its variation. J Agric Meteorol 67:225–232. (PMID: 10.2480/agrmet.67.4.3)
Hirabayashi H, Sasaki K, Kambe T, Gannaban RB, Miras MA, Mendioro MS, Simon EV, Lumanglas PD, Fujita D, Takemoto-Kuno Y, Takeuchi Y, Kaji R, Kondo M, Kobayashi N, Ogawa T, Ando I, Jagadish KSV, Ishimaru T (2015) qEMF3, a novel QTL for the early-morning flowering trait from wild rice, Oryza officinalis, to mitigate heat stress damage at flowering in riceO. sativa. J Exp Bot 66(5):1227–1236. https://doi.org/10.1093/jxb/eru474. (PMID: 10.1093/jxb/eru47425534925)
Hirotsu N, Ujiie K, Perera I, Iri A, Kashiwagi T, Ishimaru K (2017) Partial loss-of-function of NAL1 alters canopy photosynthesis by changing the contribution of upper and lower canopy leaves in rice. Sci Rep 7(1):15958. https://doi.org/10.1038/s41598-017-15886-5. (PMID: 10.1038/s41598-017-15886-5291629185698313)
Holz M, Zarebanadkouki M, Kuzyakov Y, Pausch J, Carminati A (2018) Root hairs increase rhizosphere extension and carbon input to soil. Annal Bot 121:61–69. https://doi.org/10.1093/aob/mcx127. (PMID: 10.1093/aob/mcx127)
Hussain S, Peng S, Fahad S, Khaliq A, Huang J, Cui K, Nie L (2015) Rice management interventions to mitigate greenhouse gas emissions: a review. Environ Sci Poll Res 22:3342–3360. https://doi.org/10.1007/s11356-014-3760-4. (PMID: 10.1007/s11356-014-3760-4)
Ishfaq M, Farooq M, Zulfiqar U, Hussain S, Akbar N, Nawaz A, Anjum SA (2020) Alternate wetting and drying: a water-saving and eco friendly rice production system. Agric Water Manag. https://doi.org/10.1016/j.agwat.2020.106363. (PMID: 10.1016/j.agwat.2020.106363)
Ishimaru T, Hirabayashi H, Ida M, Takai T, San-Oh YA, Yoshinaga S, Ando I, Ogawa T, Kondo M (2010) A genetic resource for early-morning flowering trait of wild rice Oryza officinalis to mitigate high temperature-induced spikelet sterility at anthesis. Annal Bot 106(3):515–520. https://doi.org/10.1093/aob/mcq124. (PMID: 10.1093/aob/mcq124)
Jagadish SV, Murty MV, Quick WP (2015) Rice responses to rising temperatures–challenges, perspectives and future directions. Plant Cell Environ 38(9):1686–1698. https://doi.org/10.1111/pce.12430. (PMID: 10.1111/pce.1243025142172)
Jeong J, Cho Y, Jeong J, Mo Y, Kim C, Kim W, Baek M, Kim S (2020) QTL mapping and effect confirmation for anaerobic germination tolerance derived from the japonica weedy rice landrace PBR. Plant Breed 139:83–92. (PMID: 10.1111/pbr.12753)
Jones HG (2004). Application of thermal imaging and infrared sensing in plant physiology and ecophysiology. In Advances in Botanical Research (pp 107-163). doi: https://doi.org/10.1016/S0065-2296(04)41003-9 .
Julia C, Dingkuhn M (2013) Predicting temperature induced sterility of rice spikelets requires simulation of crop-generated microclimate. Euro J Agro 49:50–60. https://doi.org/10.1016/j.eja.2013.03.006. (PMID: 10.1016/j.eja.2013.03.006)
Julia CC, Rose TJ, Pariasca-Tanaka J, Jeong K, Matsuda T, Wissuwa M (2018) Phosphorus uptake commences at the earliest stages of seedling development in rice. J Exp Bot 69(21):5233–5240. https://doi.org/10.1093/jxb/ery267. (PMID: 10.1093/jxb/ery26730053197)
Kano M, Inukai Y, Kitano H, Yamauchi A (2011) Root plasticity as the key root trait for adaptation to various intensities of drought stress in rice. Plant and Soil 342:117–128. (PMID: 10.1007/s11104-010-0675-9)
Kano-Nakata M, Gowda VRP, Henry A, Serraj R, Inukai Y, Fujita D, Kobayashi N, Suralta RR, Yamauchi A (2013) Functional roles of the plasticity of root system development in biomass production and water uptake under rainfed lowland conditions. Field Crops Res 144:288–296. (PMID: 10.1016/j.fcr.2013.01.024)
Kawamura K, Asai H, Yasuda T, Khanthavong P, Soisouvanh P, Phongchanmixay S (2020) Field phenotyping of plant height in an upland rice field in Laos using low-cost small unmanned aerial vehicles (UAVs). Plant Production Sci. https://doi.org/10.1080/1343943X.2020.1766362. (PMID: 10.1080/1343943X.2020.1766362)
Klukas C, Chen D, Pape JM (2014) Integrated Analysis Platform: An open-source information system for high-throughput plant phenotyping. Plant Physiol 165(2):506–518. https://doi.org/10.1104/pp.113.233932. (PMID: 10.1104/pp.113.233932247608184044849)
Lanceras JC, Pantuwan G, Jongdee B, Toojinda T (2004) Quantitative trait loci associated with drought tolerance at reproductive stage in rice. Am Soc Plant Biolog 135(1):384–399. https://doi.org/10.1104/pp.103.035527. (PMID: 10.1104/pp.103.035527)
Lesmeister L, Koschorreck M (2017) A closed-chamber method to measure greenhouse gas fluxes from dry aquatic sediments. Atmos Meas Tech 10(6):2377–2382. https://doi.org/10.5194/amt-10-2377-2017. (PMID: 10.5194/amt-10-2377-2017)
Linquist B, van Groenigen KJ, Adviento-Borbe MA, Pittelkow C, van Kessel C (2012) An agronomic assessment of greenhouse gas emissions from major cereal crops. Global Change Biol 18(1):194–209. https://doi.org/10.1111/j.1365-2486.2011.02502.x. (PMID: 10.1111/j.1365-2486.2011.02502.x)
Liu X, Wu S, Xu J, Sui C, Wei J (2017) Application of CRISPR/Cas9 in plant biology. Acta Pharmaceutica Sinica B 7(3):292–302. https://doi.org/10.1016/j.apsb.2017.01.002. (PMID: 10.1016/j.apsb.2017.01.002285890775443236)
Long W, Dan D, Yuan Z, Chen Y, Jin J, Yang W, Li S (2020) Deciphering the genetic basis of lodging resistance in wild rice Oryza longistaminata. Front Plant Sci 11:628–628. https://doi.org/10.3389/fpls.2020.00628. (PMID: 10.3389/fpls.2020.00628325475767274161)
Mahender A, Anandan A, Pradhan SK (2015) Early seedling vigour, an imperative trait for direct-seeded rice: an overview on physio-morphological parameters and molecular markers. Planta 241:1027–1050. (PMID: 10.1007/s00425-015-2273-9)
Melandri G, Prashar A, McCouch SR, van der Linden G, Jones HG, Kadam N, Ruyter-Spira C (2019) Association mapping and genetic dissection of drought-induced canopy temperature differences in rice. J Exp Bot 71(4):1614–1627. https://doi.org/10.1093/jxb/erz527. (PMID: 10.1093/jxb/erz5277031080)
Miao C, Xiao L, Hua K, Zou C, Zhao Y, Bressan RA, Zhu J (2018) Mutations in a subfamily of abscisic acid receptor genes promote rice growth and productivity. Proceed Nat Acad Sci United States of Am 115:6058–6063. https://doi.org/10.1073/pnas.1804774115. (PMID: 10.1073/pnas.1804774115)
Moose SP, Mumm RH (2008) Molecular plant breeding as the foundation for 21st century crop improvement. Am Soc Plant Biol 147(3):969. https://doi.org/10.1104/pp.108.118232. (PMID: 10.1104/pp.108.118232)
Müller-Linow M, Wilhelm J, Briese C, Wojciechowski T, Schurr U, Fiorani F (2019) Plant Screen mobile: an open-source mobile device app for plant trait analysis. Plant Methods. https://doi.org/10.1186/s13007-019-0386-z. (PMID: 10.1186/s13007-019-0386-z306517496329080)
Neeraja CN, Maghirang-Rodriguez R, Pamplona A, Heuer S, Collard BCY, Septiningsih EM, Vergara G, Sanchez D, Xu K, Ismail AM, Mackill DJ (2007) A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. Theor Appl Genet 115(6):767–776. https://doi.org/10.1007/s00122-007-0607-0. (PMID: 10.1007/s00122-007-0607-017657470)
Nestler J, Wissuwa M (2016) Superior root hair formation confers root efficiency in some, but not all, rice genotypes upon P deficiency. Front Plant Sci. https://doi.org/10.3389/fpls.2016.01935. (PMID: 10.3389/fpls.2016.01935280664875174101)
Nestler J, Keyes SD, Wissuwa M (2016) Root hair formation in rice (Oryza sativa L.) differs between root types and is altered in artificial growth conditions. J Exp Bot 67:3699–3708. (PMID: 10.1093/jxb/erw115)
Palta J, Watt M (2009) Vigorous Crop Root Systems. In V. Sadras & D. Calderini (Eds.) Crop Physiology: Applications for Genetic Improvement and Agronomy (pp 309-325). Elsevier.
Pariasca-Tanaka J, Vandamme E, Mori A, Segda Z, Saito K, Rose TJ, Wissuwa M (2015) Does reducing seed-P concentrations affect seedling vigor and grain yield of rice? Plant Soil 392:253–266. https://doi.org/10.1007/s11104-015-2460-2. (PMID: 10.1007/s11104-015-2460-2)
Peng S, Khush GS (2003) Four decades of breeding for varietal improvement of irrigated lowland rice in the International Rice Research Institute. Plant Production Sci 6(3):157–164. (PMID: 10.1626/pps.6.157)
Peng S, Huang J, Sheehy JE, Laza RC, Visperas RM, Zhong X, Centeno G, Khush GS, Cassman KG (2004) Rice yields decline with higher night temperature from global warming. Proceed Nat Acad Sci United States of Am 101(27):9971. https://doi.org/10.1073/pnas.0403720101. (PMID: 10.1073/pnas.0403720101)
Poorter H, Fiorani F, Pieruschka R, Wojciechowski T, van der Putten WH, Kleyer M, Schurr U, Postma J (2016) Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field. New Phytol 212:838–855. https://doi.org/10.1111/nph.14243. (PMID: 10.1111/nph.1424327783423)
Porter JR, Xie L, Challinor AJ, Cochrane K, Howden SM, Iqbal MM, Lobell DB, Travasso MI (2014) Food security and food production systems. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate Change 2014: Impacts, Adaptation, and Vulnerability. Cambridge University Press, Cambridge, United Kingdom, pp 485–533.
Price AH, Norton GJ, Salt DE, Ebenhoeh O, Meharg AA, Meharg C, Islam MR, Sarma RN, Dasgupta T, Ismail AM, McNally KL, Zhang H, Dodd IC, Davies WJ (2013) Alternate wetting and drying irrigation for rice in Bangladesh: Is it sustainable and has plant breeding something to offer? Food and Energy Security 2(2):120–129. https://doi.org/10.1002/fes3.29. (PMID: 10.1002/fes3.29)
Pritchard SL, Charlton WL, Baker A, Graham IA (2002) Germination and storage reserve mobilization are regulated independently in Arabidopsis. Plant J 31(5):639–647. https://doi.org/10.1046/j.1365-313X.2002.01376.x. (PMID: 10.1046/j.1365-313X.2002.01376.x12207653)
Rao, A. N., Johnson, D. E., Sivaprasad, B., Ladha, J. K., & Mortimer, A. M. (2007). Weed management in direct‐seeded rice. In: Advances in agronomy. Elsevier, 153–255.
Sabar M, Shabir G, Shah SM, Aslam K, Naveed SA, Arif M (2019) Identification and mapping of QTLs associated with drought tolerance traits in rice by a cross between Super Basmati and IR55419-04. Breed Sci 69(1):169–178. https://doi.org/10.1270/jsbbs.18068. (PMID: 10.1270/jsbbs.18068310864956507710)
Sadras V, Alston J, Aphalo P, Connor D, Denison RF, Fischer T, Gray R, Hayman P, Kirkegaard J, Kirchmann H, Kropff M, Lafitte HR, Langridge P, Lenne J, Mínguez MI, Passioura J, Portern JR, Reeves T, Rodriguez D, Ryan M, Villalobos MF, Wood D (2020) Making science more effective for agriculture. Adv Agro 163:153–177. https://doi.org/10.1016/bs.agron.2020.05.003. (PMID: 10.1016/bs.agron.2020.05.003)
Sagare DB, Abbai R, Jain A, Jayadevappa PK, Dixit S, Singh AK, Challa V, Alam S, Singh UM, Yadav S (2020) More and more of less and less: Is genomics-based breeding of dry direct-seeded rice (DDSR) varieties the need of the hour? Plant Biotechnol J. https://doi.org/10.1111/pbi.13454. (PMID: 10.1111/pbi.13454327259337589319)
Saika H, Horita J, Taguchi-Shiobara F, Nonaka S, Nishizawa-Yokoi A, Iwakami S, Toki S (2014) A novel rice cytochrome P450 gene, CYP72A31, confers tolerance to acetolactate synthase-inhibiting herbicides in rice and Arabidopsis. Am Soc Plant Biol 166(3):1232–1240. https://doi.org/10.1104/pp.113.231266. (PMID: 10.1104/pp.113.231266)
Sandhu N, Raman KA, Torres RO, Audebert A, Dardou A, Kumar A, Henry A (2016) Rice root architectural plasticity traits and genetic regions for adaptability to variable cultivation and stress conditions. Plant Physiol. https://doi.org/10.1104/pp.16.00705. (PMID: 10.1104/pp.16.00705273423114972292)
Sandhu N, Dixit S, Swamy BPM, Vikram P, Venkateshwarlu C, Catolos M, Kumar A (2018) Positive interactions of major-effect QTLs with genetic background that enhances rice yield under drought. Sci Rep 8(1):1626–1626. https://doi.org/10.1038/s41598-018-20116-7. (PMID: 10.1038/s41598-018-20116-7293742405786057)
Sandhu N, Subedi SR, Singh VK, Sinha P, Kumar S, Singh SP, Ghimire SK, Pandey M, Yadaw RB, Varshney RK, Kumar A (2019). Deciphering the genetic basis of root morphology, nutrient uptake, yield, and yield-related traits in rice under dry direct-seeded cultivation systems. Scientific Reports, 9(9334). doi: https://doi.org/10.1038/s41598-019-45770-3 .
Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nature methods 9(7):671–675. (PMID: 10.1038/nmeth.2089)
Septiningsih EM, Ignacio JCI, Sendon PMD, Sanchez DL, Ismail AM, Mackill DJ (2013) QTL mapping and confirmation for tolerance of anaerobic conditions during germination derived from the rice landrace Ma-Zhan Red. Theor Appl Genet 126(5):1357–1366. https://doi.org/10.1007/s00122-013-2057-1. (PMID: 10.1007/s00122-013-2057-123417074)
Shah L, Yahya M, Shah SMA, Nadeem M, Ali A, Wang J, Riaz MW, Rehman S, Wu W (2019). Improving lodging resistance: Using wheat and rice as classical examples. International Journal of Molecular Sciences, 20(4211).
Shamsudin NAA, Swamy BPM, Ratnam W, StaCruzSandhuRamanKumar MTNAKA (2016) Pyramiding of drought yield QTLs into a high quality Malaysian rice cultivar MRQ74 improves yield under reproductive stage drought. Rice 9(1):21. https://doi.org/10.1186/s12284-016-0093-6. (PMID: 10.1186/s12284-016-0093-6271649824864745)
Shaw, R., Nguyen, H., Habiba, U., & Takeuchi, Y. (2011). Chapter 1 Overview and Characteristics of Asian Monsoon Drought. In Shaw, R. & Nguyen, H. (Eds.), Droughts in Asian Monsoon Region (pp. 1-24). Bingley: Emerald Group Publishing Limited. doi: https://doi.org/10.1108/S2040-7262(2011)0000008007.
Singh UM, Yadav S, Dixit S, Ramayya PJ, Devi MN, Raman KA, Kumar A (2017) QTL hotspots for early vigor and related traits under dry direct-seeded system in rice (Oryza sativa L). Front Plant Sci. https://doi.org/10.3389/fpls.2017.00286. (PMID: 10.3389/fpls.2017.00286293267295742331)
Smith P, Martino D, Cai Z, Gwary D, Janzen H, Kumar P, McCarl B, Ogle S, O’Mara F, Rice C, Scholes B, Sirotenko O (2007) Agriculture. In: Metz B, Davidson OR, Bosch PR, Dave R, Meye LA (eds) Climate change 2007: Mitigation. Cambridge Univ. Press, Cambridge, UK.
Sriphirom P, Chidthaisong A, Towprayoon S (2019) Effect of alternate wetting and drying water management on rice cultivation with low emissions and low water used during wet and dry season. J Clean Production 223:980–988. (PMID: 10.1016/j.jclepro.2019.03.212)
Suralta RR, Inukai Y, Yamauchi A (2010) Dry matter production in relation to root plastic development, oxygen transport, and water uptake of rice under transient soil moisture stresses. Plant and Soil 332:87–104. (PMID: 10.1007/s11104-009-0275-8)
Suralta RR, Niones JM, Kano-Nakata M, Tran TT, Mitsuya S, Yamauchi A (2018) Plasticity in nodal root elongation through the hardpan triggered by rewatering during soil moisture fluctuation stress in rice. Sci Rep 8(4341). https://doi.org/10.1038/s41598-018-22809-5.
Swamy BP, Ahmed HU, Henry A, Mauleon R, Dixit S, Vikram P, Tilatto R, Verulkar SB, Perraju P, Mandal NP, Variar M, Robin S, Chandrababu R, Singh ON, Dwivedi JL, Das SP, Mishra KK, Yadaw RB, Aditya TL, Karmakar B, Kumar A (2013) Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought. PloS one 8(5):e62795. https://doi.org/10.1371/journal.pone.0062795. (PMID: 10.1371/journal.pone.006279523667521)
Torti S, Schlesier R, Thummler A et al (2021) Transient reprogramming of crop plants for agronomic performance. Nature Plants 7:159–171. https://doi.org/10.1038/s41477-021-00851-y. (PMID: 10.1038/s41477-021-00851-y33594264)
Tracy SR, Nagel KA, Postma JA, Fassbender H, Wasson A, Watt M (2020) Crop improvement from phenotyping roots: highlights reveal expanding opportunities. Trends in Plant Sci 25:105–118. (PMID: 10.1016/j.tplants.2019.10.015)
Tran TT, Kano-Nakata M, Suralta RR, Menge D, Mitsuya S, Inukai Y, Yamauchi A (2015) Root plasticity and its functional roles were triggered by water deficit but not by the resulting changes in the forms of soil N in rice. Plant and Soil 386:65–76. (PMID: 10.1007/s11104-014-2240-4)
Uga Y, Sugimoto K, Ogawa S et al (2013) Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nature Genet 45:1097–1102. https://doi.org/10.1038/ng.2725. (PMID: 10.1038/ng.272523913002)
Vaughan DA, Morishima H, Kadowaki K (2003) Diversity in the Oryza genus. Current Opinion in Plant Biol 6(2):139–146. https://doi.org/10.1016/S1369-5266(03)00009-8. (PMID: 10.1016/S1369-5266(03)00009-8)
Venuprasad R, Sta Cruz MT, Amante M, Magbanua R, Kumar A, Atlin GN (2008) Response to two cycles of divergent selection for grain yield under drought stress in four rice breeding populations. Field Crops Res 107:232–244. https://doi.org/10.1016/j.fcr.2008.02.004. (PMID: 10.1016/j.fcr.2008.02.004)
Vikram P, Swamy BPM, Dixit S, Miro B, Kohli A, Kumar A, Henry A (2015) Drought susceptibility of modern rice varieties: an effect of linkage of drought tolerance with undesirable traits. Sci Rep. https://doi.org/10.1038/srep14799. (PMID: 10.1038/srep14799264587444602206)
Wang Y, Thorup-Kristensen K, Jensen LS, Magid J (2016) Vigorous root growth is a better indicator of early nutrient uptake than root hair traits in spring wheat grown under low fertility. Front Plant Sci. https://doi.org/10.3389/fpls.2016.00865. (PMID: 10.3389/fpls.2016.00865281492985186801)
Wang F, Longkumer T, Catausan SC, Calumpang C, Tarun JA, Cattin-Ortola J, Ishizaki T, Pariasca Tanaka J, Rose T, Wissuwa M, Kretzschmar T (2018) Genome-wide association and gene validation studies for early root vigour to improve direct seeding of rice. Plant Cell Environ 41(12):2731–2743. (PMID: 10.1111/pce.13400)
Wassmann R, Jagadish SVK, Heuer S, Ismail A, Redona E, Serraj R, Singh RK, Howell G, Pathak H, Sumfleth K (2009) Climate change affecting rice production: the physiological and agronomic basis for possible adaptation strategies. Adv Agro 101:59–122. (PMID: 10.1016/S0065-2113(08)00802-X)
Watanabe Y, Kabuki T, Kakehashi T, Kano-Nakata M, Mitsuya S, Yamauchi A (2020) Morphological and histological differences among three types of component roots and their differential contribution to water uptake in the rice root system. Plant Production Science 23:191–201. (PMID: 10.1080/1343943X.2020.1730701)
Weight C, Parnham D, Waites R (2008) Technical Advance: LeafAnalyser: a computational method for rapid and large-scale analyses of leaf shape variation. Plant J 53:578–586. https://doi.org/10.1111/j.1365-313X.2007.03330.x. (PMID: 10.1111/j.1365-313X.2007.03330.x18028263)
Yadav S, Singh UM, Naik SM, Venkateshwarlu C, Ramayya PJ, Raman KA, Sandu A, Kumar A (2017) Molecular mapping of QTLs associated with lodging resistance in dry direct-seeded rice (Oryza sativa L). Front Plant Sci. https://doi.org/10.3389/fpls.2017.01431. (PMID: 10.3389/fpls.2017.01431295520205742331)
Yadav S, Sandhu N, Singh VK, Catolos M, Kumar A (2019) Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance. Sci Rep. https://doi.org/10.1038/s41598-019-50880-z. (PMID: 10.1038/s41598-019-50880-z318827816934786)
Yan T, Wang J, Huang J (2015) Urbanization, agricultural water use, and regional and national crop production in China. Ecol Model 318:226–235. https://doi.org/10.1016/j.ecolmodel.2014.12.021. (PMID: 10.1016/j.ecolmodel.2014.12.021)
Ye C, Argayoso MA, Redoña ED, Sierra SN, Laza MA, Dilla CJ, Hernandez JE (2012) Mapping QTL for heat tolerance at flowering stage in rice using SNP markers. Plant Breed 131(1):33–41. https://doi.org/10.1111/j.1439-0523.2011.01924.x. (PMID: 10.1111/j.1439-0523.2011.01924.x)
Ye C, Tenorio FA, Argayoso MA, Laza MA, Koh H-J, Redoña ED, Gregorio GB (2015) Identifying and confirming quantitative trait loci associated with heat tolerance at flowering stage in different rice populations. BMC Genet 16(1):41. https://doi.org/10.1186/s12863-015-0199-7. (PMID: 10.1186/s12863-015-0199-7258956824415243)
Zeigler RS, Dobermann A (2011). A global rice science partnership. In Food for all - Investing in food security in Asia and the Pacific issues, innovations, and Practices. ADB, Mandaluyong City, Philippines, pp. 106-116.
Zhang X, Zhou S, Fu Y, Su Z, Wang X, Sun C (2006) Identification of a drought tolerant introgression line derived from Dongxiang common wild rice (O rufipogon Griff). Plant Mol Biol 62(1):247–259. https://doi.org/10.1007/s11103-006-9018-x. (PMID: 10.1007/s11103-006-9018-x16845479)

059QF0KO0R (Water)

Date Created: 20210704 Date Completed: 20220317 Latest Revision: 20220317

20221213

10.1007/s00122-021-03899-8

34218290