Zhang Y, Zhu D, Xiong H, Chen H, Xiang J, Lin X. Development and transition of rice planting in China. Agric Sci Technol. 2012;13(6):1270–6.
Google Scholar
Zhu D, Zhang Y, Chen H, Xiang J, Zhang Y. Innovation and practice of high-yield rice cultivation technology in China. Acta Agron Sin. 2015;48(17):3404–14.
Google Scholar
Bai RP. Several issues on the route choice of mechanization of rice production technology. Chinese Agric Mechanization. 2011;1(15~18):22.
Google Scholar
Xu Y, Zhu D, Zhao Y, Chen H. Effects of broadcast sowing and precision drilling of super rice seed on seedling quality and effectiveness of mechanized transplanting. Transactions Chinese Soc Agric Eng. 2009;25(1):99–103.
Google Scholar
Zhu D, Chen H, Xu Y. The confinement factors and development counter measures of mechanical production of double cropping rice in China. China Rice. 2013;19:1–4.
Google Scholar
Chen S, Wang D, Xu C, Ji C, Zhang X, Zhao X, Zhang X, Chauhan BS. Responses of super rice (Oryza sativa L.) to different planting methods for grain yield and nitrogen-use efficiency in the single cropping season. Plos One. 2014;9(8):e104950.
Article
PubMed
PubMed Central
CAS
Google Scholar
Li Z, Ma X, Xie J, Chen G, Zhen Z, Tan Y, Huang Y. Experiment on precision seedling raising and mechanized transplanting of hybrid rice under low sowing rate in double cropping area. Transactions Chinese Soc Agric Eng. 2014;30(6):17–27.
CAS
Google Scholar
Li Z, Ma X, Long Q, Tan S, Chen X, Tan Y, Liang Z, Sun G, Huang Y. Comparison and evaluation of different rice mechanized transplanting methods in double cropping area of South China. Transactions Chinese Soc Agric Eng. 2015;31(3):40–7.
Google Scholar
Chen J, Cao F, Yin X, Huang M, Zou Y. Yield performance of early-season rice cultivars grown in the late season of double-season crop production under machine-transplanted conditions. PLoS One. 2019;14(3):e0213075.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jia X, Zhu Q, Yang Z, Sun Y, Guo X, Shi Y, Ma J. Effect of seedling age on yield and population quality of mechanized transplanted hybrid rice. Transactions Chinese Soc Agric Eng. 2014;30(12):18–25.
Google Scholar
Liu Q, Wu X, Ma J, Chen B, Xin C. Effects of delaying transplanting on agronomic traits and grain yield of rice under mechanical transplantation pattern. PLoS One. 2015;10(4):e0123330.
Article
PubMed
PubMed Central
CAS
Google Scholar
Liu Q, Zhou X, Li J, Xin C. Effects of seedling age and cultivation density on agronomic characteristics and grain yield of mechanically transplanted rice. Sci Rep. 2017;7(1):14072.
Article
PubMed
PubMed Central
CAS
Google Scholar
Reuben P, Katambara Z, Kahimba FC, Mahoo HF, Mbungu WB, Mhenga F, Nyarubamba A, Maugo M. Influence of transplanting age on paddy yield under the system of rice intensification. Agric Sci. 2016;07(3):154–63.
Google Scholar
Hu Y, Wu P, Zhang H, Dai Q, Huo Z, Xu K, Gao H, Wei H, Guo B, Cui P. Comparison of agronomic performance between inter-sub-specific hybrid and inbred japonica rice under different mechanical transplanting methods. J Integr Agric. 2018;17(4):806.
Article
Google Scholar
Zhang J, Wang X, Shi G, Mi CS, Guo B, Li B, Fang S, Lu H, Liu Z, Zhang Y. Yield and its formation of hybrid rice under different mechanical transplanted methods. Transactions Chinese Soc Agric Eng. 2015;31(10):84–91.
Google Scholar
Wang D, Chen S, Wang Z, Ji C, Xu C, Zhang X, Chauhan BS. Optimizing hill seeding density for high-yielding hybrid rice in a single rice cropping system in South China. PLoS One. 2014;9(10):e109417.
Article
PubMed
PubMed Central
CAS
Google Scholar
Zhang J. Status and research progress on key techniques of hybrid rice transplanting with machinery. Modern Agric Sci Technol. 2011;3:50–2.
Google Scholar
Zhang WX, Zhu DF, Lin XQ, Yi-Cheng XU, Lin XJ, Chen HZ, Zhang YP. The effects of different sowing densities and raising materials on seedling quality of mechanical transplanting rice. J Yangzhou Univ. 2007;28(1):45–8.
Google Scholar
Kobayashi K, Takahashi Y, Fukuyama T. Studies on the seedling raising method in giant-embryo rice cultivar ‘Koshiguruma’ and its adaptability to machine transplanting. Japanese J Crop Sci. 2009;78(1):17–26.
Article
Google Scholar
Yao X, Yang W, Ren W. Effects seedling raising methods and sowing rates on machine-transplanted long-age rice seedling. Transactions Chinese Soc Agric Eng. 2009;25(6):152–7.
Google Scholar
Zhang H, Gong J. Research status and development discussion on high-yielding agronomy of mechanized planting rice in China. Sci Agric Sin. 2014;47(7):1273–89.
Google Scholar
Li G, Yu L, Hou P, Wang S, Liu Z, Wang Q, Ling Q, Ding Y. Calculation and verification of quantitative parameters of optimal planting density of machine-transplant rice. Transactions Chinese Soc Agric Eng. 2012;28(8):98–104.
Google Scholar
Chen H, Zhu D, Xu Y. Mechanized planting technology of rice bowl-shaped blanket seedling and application effect. China Rice. 2009;15(3):5–7.
CAS
Google Scholar
Du L, Yu G, Zhang G, Li G, Liu D. Design and experiment of vertically feeding-seedling device for pot-blanket seedling based on high-speed rice transplanter. Transactions Chinese Soc Agric Eng. 2014;30(14):17–25.
Google Scholar
Zhang Z, Qu X, Wan S, Chen L, Zhu Y. Comparison of QTL controlling seedling vigour under different temperature conditions using recombinant inbred lines in rice (Oryza Sativa). Ann Bot. 2005;95(3):423–9.
Article
CAS
PubMed
Google Scholar
Hu J, Yang B, Zhou W, Zhang P, Zhang Q, Li P, Ren W, Yang W, Hu J, Yang B. Effect of seeding method and density on the benefit of mechanical transplanting in indica hybrid rice. Chinese J Rice Sci. 2017;31(1):81–90.
Google Scholar
Pan S, Wen X, Tian H, Chen Y, Zhaowen MO, Duan M, Tang X. Effects of broadcasting density and seedling strengthen agent on physiological characteristics of rice seedling. J South China Agric Univ. 2015;36(3):32–6.
CAS
Google Scholar
Casal JJ. Shade avoidance. Arabidopsis Book. 2012;10:e0157.
Article
PubMed
PubMed Central
Google Scholar
Pierik R, de Wit M. Shade avoidance: phytochrome signalling and other aboveground neighbour detection cues. J Exp Bot. 2013;65(11):2815–24.
Article
PubMed
Google Scholar
Wang X, Gao X, Liu Y, Fan S, Ma Q. Progress of research on the regulatory pathway of the plant shade-avoidance syndrome. Front Plant Sci. 2020;11:439.
Article
PubMed
PubMed Central
Google Scholar
Carriedo LG, Maloof JN, Brady SM. Molecular control of crop shade avoidance. Curr Opin Plant Biol. 2016;30:151–8.
Article
CAS
PubMed
Google Scholar
Liu H, Yang C, Li L. Shade-induced stem elongation in rice seedlings: implication of tissue-specific phytohormone regulation. J Integr Plant Biol. 2016;58(7):614–7.
Article
CAS
PubMed
Google Scholar
Fang S, Clark RT, Zheng Y, Iyer-Pascuzzi AS, Weitz JS, Kochian LV, Edelsbrunner H, Liao H, Benfey PN. Genotypic recognition and spatial responses by rice roots. Proc Natl Acad Sci U S A. 2013;110(7):2670–5.
Article
CAS
PubMed
PubMed Central
Google Scholar
Sandhu N, Torres RO, Sta Cruz MT, Maturan PC, Jain R, Kumar A, Henry A. Traits and QTLs for development of dry direct-seeded rainfed rice varieties. J Exp Bot. 2015;66(1):225–44.
Article
CAS
PubMed
Google Scholar
Lu Q, Zhang M, Niu X, Wang C, Xu Q, Feng Y, Wang S, Yuan X, Yu H, Wang Y, et al. Uncovering novel loci for mesocotyl elongation and shoot length in indica rice through genome-wide association mapping. Planta. 2016;243(3):645–57.
Article
CAS
PubMed
Google Scholar
Lee HS, Sasaki K, Higashitani A, Ahn SN, Sato T. Mapping and characterization of quantitative trait loci for mesocotyl elongation in rice (Oryza sativa L.). Rice. 2012;5(1):13.
Article
PubMed
PubMed Central
Google Scholar
Dang X, Thi TG, Dong G, Wang H, Edzesi WM, Hong D. Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.). Planta. 2014;239(6):1309–19.
Article
CAS
PubMed
Google Scholar
Singh UM, Yadav S, Dixit S, Ramayya PJ, Devi MN, Raman KA, Kumar A. QTL hotspots for early vigor and related traits under dry direct-seeded system in rice (Oryza sativa L.). Front Plant Sci. 2017;8:286.
PubMed
PubMed Central
Google Scholar
Wang F, Longkumer T, Catausan SC, Calumpang CLF, Tarun JA, Cattin-Ortola J, Ishizaki T, Pariasca Tanaka J, Rose T, Wissuwa M, et al. Genome-wide association and gene validation studies for early root vigour to improve direct seeding of rice. Plant Cell Environ. 2018;41(12):2731–43.
Article
CAS
PubMed
Google Scholar
Zhao Y, Zhao W, Jiang C, Wang X, Xiong H, Todorovska EG, Yin Z, Chen Y, Wang X, Xie J, et al. Genetic architecture and candidate genes for deep-sowing tolerance in rice revealed by non-syn GWAS. Front Plant Sci. 2018;9:332.
Article
PubMed
PubMed Central
Google Scholar
Abe A, Takagi H, Fujibe T, Aya K, Kojima M, Sakakibara H, Uemura A, Matsuoka M, Terauchi R. OsGA20ox1, a candidate gene for a major QTL controlling seedling vigor in rice. Theor Appl Genet. 2012;125(4):647–57.
Article
CAS
PubMed
Google Scholar
Cui K, Huang J, Xing Y, Yu S, Xu C, Peng S. Mapping QTLs for seedling characteristics under different water supply conditions in rice (Oryza sativa). Physiol Plant. 2008;132(1):53–68.
CAS
PubMed
Google Scholar
Zhao Y, Jiang CH, Rehman RMA, Zhang HL, Li J, Li ZC. Genetic analysis of roots and shoots in rice seedling by association mapping. Genes Genom. 2018;41(1):95–105.
Article
CAS
Google Scholar
Ikeda H, Kamoshita A, Manabe T. Genetic analysis of rooting ability of transplanted rice (Oryza sativa L.) under different water conditions. J Exp Bot. 2007;58(2):309–18.
Article
CAS
PubMed
Google Scholar
Shakiba E, Edwards JD, Jodari F, Duke SE, Baldo AM, Korniliev P, McCouch SR, Eizenga GC. Genetic architecture of cold tolerance in rice (Oryza sativa) determined through high resolution genome-wide analysis. PLoS One. 2017;12(3):e0172133.
Article
PubMed
PubMed Central
CAS
Google Scholar
Redoña ED, Mackill DJ. Mapping quantitative trait loci for seedling vigor in rice using RFLPs. Theor Appl Genet. 1996;92:395–402.
Article
PubMed
Google Scholar
Price AH, Steele KA, Moore BJ, Barraclough PB, Clark LJ. A combined RFLP and AFLP linkage map of upland rice (Oryza sativa L.) used to identify QTLs for root-penetration ability. Theor Appl Genet. 2000;100(1):49–56.
Article
CAS
Google Scholar
Li Z, Mu P, Li C, Zhang H, Gao Y, Wang X. QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments. Theor Appl Genet. 2005;110(7):1244–52.
Article
CAS
PubMed
Google Scholar
Yano K, Takashi T, Nagamatsu S, Kojima M, Sakakibara H, Kitano H, Matsuoka M, Aya K. Efficacy of microarray profiling data combined with QTL mapping for the identification of a QTL gene controlling the initial growth rate in rice. Plant Cell Physiol. 2012;53(4):729–39.
Article
CAS
PubMed
Google Scholar
Cui K, Peng S, Xing Y, Xu C, Yu S, Zhang Q. Molecular dissection of seedling-vigor and associated physiological traits in rice. Theor Appl Genet. 2002;105(5):745–53.
Article
CAS
PubMed
Google Scholar
Xu CG, Li XQ, Xue Y, Huang YW, Gao J, Xing YZ. Comparison of quantitative trait loci controlling seedling characteristics at two seedling stages using rice recombinant inbred lines. Theor Appl Genet. 2004;109(3):640–7.
Article
CAS
PubMed
Google Scholar
Zhang Q. Strategies for developing Green super Rice. Proc Natl Acad Sci U S A. 2007;104(42):16402–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Teng F, Chen H, Zhu D, Cai X, Xiang J, Xu Y, Zhang Z. Effects of sowing rates on seedling root entwining and seedling quality of machine-transplanted rice. Acta Agric Univ Jiangxiensis. 2015;37(3):389–403.
Google Scholar
Zhu D, Zhou G, Xu C, Zhang Q. Genetic components of heterosis for seedling traits in an elite rice hybrid analyzed using an immortalized F2 population. J Genet Genomics. 2016;43(2):87–97.
Article
PubMed
Google Scholar
Shen C, Wang S, Zhang S, Xu Y, Qian Q, Qi Y, Jiang d A. OsARF16, a transcription factor, is required for auxin and phosphate starvation response in rice (Oryza sativa L.). Plant Cell Environ. 2013;36(3):607–20.
Article
CAS
PubMed
Google Scholar
Shen C, Yue R, Yang Y, Zhang L, Sun T, Tie S, Wang H. OsARF16 is involved in cytokinin-mediated inhibition of phosphate transport and phosphate signaling in rice (Oryza sativa L.). Plos One. 2014;9(11):e112906.
Article
PubMed
PubMed Central
CAS
Google Scholar
Jörgens CI, Grünewald N, Hülskamp M, Uhrig JF. A role for ABIL3 in plant cell morphogenesis. Plant J. 2010;62(6):925–35.
PubMed
Google Scholar
Jagadhesan B, Sathee L, Meena HS, Jha SK, Chinnusamy V, Kumar A, Kumar S. Genome wide analysis of NLP transcription factors reveals their role in nitrogen stress tolerance of rice. Sci Rep. 2020;10(1):9368.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shaik R, Ramakrishna W. Machine learning approaches distinguish multiple stress conditions using stress-responsive genes and identify candidate genes for broad resistance in rice. Plant Physiol. 2014;164(1):481–95.
Article
CAS
PubMed
Google Scholar
Smita S, Katiyar A, Chinnusamy V, Pandey DM, Bansal KC. Transcriptional regulatory network analysis of MYB transcription factor family genes in Rice. Front Plant Sci. 2015;6:1157.
Article
PubMed
PubMed Central
Google Scholar
Hong Y, Zhang H, Huang L, Li D, Song F. Overexpression of a stress-responsive NAC transcription factor gene ONAC022 improves drought and salt tolerance in Rice. Front Plant Sci. 2016;7:4–4.
Article
PubMed
PubMed Central
Google Scholar
Nawaz Z, Kakar KU, Saand MA, Shu Q-Y. Cyclic nucleotide-gated ion channel gene family in rice, identification, characterization and experimental analysis of expression response to plant hormones, biotic and abiotic stresses. BMC Genomics. 2014;15(1):853.
Article
PubMed
PubMed Central
CAS
Google Scholar
Kim H, Hwang H, Hong JW, Lee YN, Ahn IP, Yoon IS, Yoo SD, Lee S, Lee SC, Kim BG. A rice orthologue of the ABA receptor, OsPYL/RCAR5, is a positive regulator of the ABA signal transduction pathway in seed germination and early seedling growth. J Exp Bot. 2012;63(2):1013–24.
Article
CAS
PubMed
Google Scholar
Mukhopadhyay P, Tyagi AK. OsTCP19 influences developmental and abiotic stress signaling by modulating ABI4-mediated pathways. Sci Rep. 2015;5:9998.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen G, Zou Y, Hu J, Ding Y. Genome-wide analysis of the rice PPR gene family and their expression profiles under different stress treatments. BMC Genomics. 2018;19(1):720.
Article
PubMed
PubMed Central
CAS
Google Scholar
Kaur C, Kushwaha HR, Mustafiz A, Pareek A, Sopory SK, Singla-Pareek SL. Analysis of global gene expression profile of rice in response to methylglyoxal indicates its possible role as a stress signal molecule. Front Plant Sci. 2015;6:682.
PubMed
PubMed Central
Google Scholar
Reig-Valiente JL, Borredá C, Talón M, Domingo C. The G123 rice mutant, carrying a mutation in SE13, presents alterations in the expression patterns of photosynthetic and major flowering regulatory genes. PLoS One. 2020;15(5):e0233120.
Article
PubMed
PubMed Central
CAS
Google Scholar
Wang L, Wang A, Huang X, Zhao Q, Dong G, Qian Q, Sang T, Han B. Mapping 49 quantitative trait loci at high resolution through sequencing-based genotyping of rice recombinant inbred lines. Theor Appl Genet. 2011;122(2):327–40.
Article
PubMed
Google Scholar
Stowell S. Using R for statistics. New York: Apress; 2014.
Book
Google Scholar
Snedecor GW, Cochran WG. Statistical methods. Ames: Iowa State College Press; 1980.
Google Scholar
Zhou G, Chen Y, Yao W, Zhang C, Xie W, Hua J, Xing Y, Xiao J, Zhang Q. Genetic composition of yield heterosis in an elite rice hybrid. Proc Natl Acad Sci U S A. 2012;109(39):15847–52.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hua JP, Xing YZ, Xu CG, Sun XL, Yu SB, Zhang QF. Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance. Genetics. 2002;162(4):1885–95.
CAS
PubMed
PubMed Central
Google Scholar
Huang X, Feng Q, Qian Q, Zhao Q, Wang L, Wang A, Guan J, Fan D, Weng Q, Huang T, et al. High-throughput genotyping by whole-genome resequencing. Genome Res. 2009;19(6):1068–76.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln SE, Newburg L. MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics. 1987;1(2):174–81.
Article
CAS
PubMed
Google Scholar
Broman KW, Wu H, Sen S, Churchill GA. R/QTL: QTL mapping in experimental crosses. Bioinformatics. 2003;19(7):889–90.
Article
CAS
PubMed
Google Scholar
Yu H, Xie W, Wang J, Xing Y, Xu C, Li X, Xiao J, Zhang Q. Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers. PLoS One. 2011;6(3):e17595.
Article
CAS
PubMed
PubMed Central
Google Scholar