[1] |
Jian L, Yan J, Liu J. 2022. De novo domestication in the multi-omics era. Plant and Cell Physiology 63:1592−606 doi: 10.1093/pcp/pcac077 |
[2] |
Wang X, Han L, Li J, Shang X, Liu Q, et al. 2023. Next-generation bulked segregant analysis for Breeding 4.0. Cell Reports 42:113039 doi: 10.1016/j.celrep.2023.113039 |
[3] |
Jamil IN, Remali J, Azizan KA, Nor Muhammad NA, Arita M, et al. 2020. Systematic multi-omics integration (MOI) approach in plant systems biology. Frontiers in Plant Science 11:944 doi: 10.3389/fpls.2020.00944 |
[4] |
Alseekh S, Karakas E, Zhu F, Wijesingha Ahchige M, Fernie AR. 2023. Plant biochemical genetics in the multiomics era. Journal of Experimental Botany 74:4293−307 doi: 10.1093/jxb/erad177 |
[5] |
Sandhu K, Patil SS, Pumphrey M, Carter A. 2021. Multitrait machine- and deep-learning models for genomic selection using spectral information in a wheat breeding program. The Plant Genome 14:e20119 doi: 10.1002/tpg2.20119 |
[6] |
Gill T, Gill SK, Saini DK, Chopra Y, de Koff JP, et al. 2022. A comprehensive review of high throughput phenotyping and machine learning for plant stress phenotyping. Phenomics 2:156−83 doi: 10.1007/s43657-022-00048-z |
[7] |
Kaul S, Koo HL, Jenkins J, Rizzo M, Rooney T, et al. 2000. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408:796−815 doi: 10.1038/35048692 |
[8] |
Jaillon O, Aury JM, Noel B, Policriti A, Clepet C, et al. 2007. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature 449:463−67 doi: 10.1038/nature06148 |
[9] |
Zhang Q, Chen W, Sun L, Zhao F, Huang B, et al. 2012. The genome of Prunus mume. Nature Communications 3:1318 doi: 10.1038/ncomms2290 |
[10] |
Sun Y, Shang L, Zhu Q, Fan L, Guo L. 2022. Twenty years of plant genome sequencing: achievements and challenges. Trends in Plant Science 27:391−401 doi: 10.1016/j.tplants.2021.10.006 |
[11] |
Wang X, Xu Y, Zhang S, Cao L, Huang Y, et al. 2017. Genomic analyses of primitive, wild and cultivated citrus provide insights into asexual reproduction. Nature Genetics 49:765−72 doi: 10.1038/ng.3839 |
[12] |
Tan Q, Li S, Zhang Y, Chen M, Wen B, et al. 2021. Chromosome-level genome assemblies of five Prunus species and genome-wide association studies for key agronomic traits in peach. Horticulture Research 8:213 doi: 10.1038/s41438-021-00648-2 |
[13] |
Fan Z, Tieman DM, Knapp SJ, Zerbe P, Famula R, et al. 2022. A multi-omics framework reveals strawberry flavor genes and their regulatory elements. New Phytologist 236:1089−107 doi: 10.1111/nph.18416 |
[14] |
Park M, Vera D, Kambrianda D, Gajjar P, Cadle-Davidson L, et al. 2022. Chromosome-level genome sequence assembly and genome-wide association study of Muscadinia rotundifolia reveal the genetics of 12 berry-related traits. Horticulture Research 9:uhab011 doi: 10.1093/hr/uhab011 |
[15] |
Yang J, Wang J, Li Z, Li X, He Z, et al. 2021. Genomic signatures of vegetable and oilseed allopolyploid Brassica juncea and genetic loci controlling the accumulation of glucosinolates. Plant Biotechnology Journal 19:2619−28 doi: 10.1111/pbi.13687 |
[16] |
Niu Z, Zhu F, Fan Y, Li C, Zhang B, et al. 2021. The chromosome-level reference genome assembly for Dendrobium officinale and its utility of functional genomics research and molecular breeding study. Acta Pharmaceutica Sinica B 11:2080−92 doi: 10.1016/j.apsb.2021.01.019 |
[17] |
Zhang Q, Zhang H, Sun L, Fan G, Ye M, et al. 2018. The genetic architecture of floral traits in the woody plant Prunus mume. Nature Communications 9:1702 doi: 10.1038/s41467-018-04093-z |
[18] |
Wei Q, Wang J, Wang W, Hu T, Hu H, et al. 2020. A high-quality chromosome-level genome assembly reveals genetics for important traits in eggplant. Horticulture Research 7:153 doi: 10.1038/s41438-020-00391-0 |
[19] |
Wang J, Li J, Li Z, Liu B, Zhang L, et al. 2022. Genomic insights into longan evolution from a chromosome-level genome assembly and population genomics of longan accessions. Horticulture Research 9:uhac021 doi: 10.1093/hr/uhac021 |
[20] |
Zhou Y, Zheng T, Cai M, Feng L, Chi X, et al. 2023. Genome assembly and resequencing analyses provide new insights into the evolution, domestication and ornamental traits of crape myrtle. Horticulture Research 10:uhad146 doi: 10.1093/hr/uhad146 |
[21] |
Li H, Durbin R. 2024. Genome assembly in the telomere-to-telomere era. Nature Reviews Genetics doi: 10.1038/s41576-024-00718-w |
[22] |
Fu A, Zheng Y, Guo J, Grierson D, Zhao X, et al. 2023. Telomere-to-telomere genome assembly of bitter melon (Momordica charantia L. var. abbreviata Ser.) reveals fruit development, composition and ripening genetic characteristics . Horticulture Research 10:uhac228 doi: 10.1093/hr/uhac228 |
[23] |
Deng Y, Liu S, Zhang Y, Tan J, Li X, et al. 2022. A telomere-to-telomere gap-free reference genome of watermelon and its mutation library provide important resources for gene discovery and breeding. Molecular Plant 15:1268−84 doi: 10.1016/j.molp.2022.06.010 |
[24] |
Shi X, Cao S, Wang X, Huang S, Wang Y, et al. 2023. The complete reference genome for grapevine (Vitis vinifera L.) genetics and breedingHorticulture Research 10:uhad061 doi: 10.1093/hr/uhad061 |
[25] |
Han X, Zhang Y, Zhang Q, Ma N, Liu X, et al. 2023. Two haplotype-resolved, gap-free genome assemblies for Actinidia latifolia and Actinidia chinensis shed light on the regulatory mechanisms of vitamin C and sucrose metabolism in kiwifruit. Molecular Plant 16:452−70 doi: 10.1016/j.molp.2022.12.022 |
[26] |
Belser C, Baurens FC, Noel B, Martin G, Cruaud C, et al. 2021. Telomere-to-telomere gapless chromosomes of banana using nanopore sequencing. Communications Biology 4:1047 doi: 10.1038/s42003-021-02559-3 |
[27] |
Li G, Tang L, He Y, Xu Y, Bendahmane A, et al. 2023. The haplotype-resolved T2T reference genome highlights structural variation underlying agronomic traits of melon. Horticulture Research 10:uhad182 doi: 10.1093/hr/uhad182 |
[28] |
Lan L, Leng L, Liu W, Ren Y, Reeve W, et al. 2024. The haplotype-resolved telomere-to-telomere carnation (Dianthus caryophyllus) genome reveals the correlation between genome architecture and gene expression. Horticulture Research 11:uhad244 doi: 10.1093/hr/uhad244 |
[29] |
Xu Z, Wang G, Wang Q, Li X, Zhang G, et al. 2023. A near-complete genome assembly of Catharanthus roseus and insights into its vinblastine biosynthesis and high susceptibility to the Huanglongbing pathogen. Plant Communications 4:100661 doi: 10.1016/j.xplc.2023.100661 |
[30] |
Xu M, Gao Q, Jiang M, Wang W, Hu J, et al. 2023. A novel genome sequence of Jasminum sambac helps uncover the molecular mechanism underlying the accumulation of jasmonates. Journal of Experimental Botany 74:1275−90 doi: 10.1093/jxb/erac464 |
[31] |
Tang M, Huang J, Ma X, Du J, Bi Y, et al. 2023. A near-complete genome assembly of Thalia dealbata Fraser (Marantaceae). Frontiers in Plant Science 14:1183361 doi: 10.3389/fpls.2023.1183361 |
[32] |
Nie S, Zhao S, Shi T, Zhao W, Zhang R, et al. 2023. Gapless genome assembly of azalea and multi-omics investigation into divergence between two species with distinct flower color. Horticulture Research 10:uhac241 doi: 10.1093/hr/uhac241 |
[33] |
Li F, Xu S, Xiao Z, Wang J, Mei Y, et al. 2023. Gap-free genome assembly and comparative analysis reveal the evolution and anthocyanin accumulation mechanism of Rhodomyrtus tomentosa. Horticulture Research 10:uhad005 doi: 10.1093/hr/uhad005 |
[34] |
He S, Weng D, Zhang Y, Kong Q, Wang K, et al. 2023. A telomere-to-telomere reference genome provides genetic insight into the pentacyclic triterpenoid biosynthesis in Chaenomeles speciosa. Horticulture Research 10:uhad183 doi: 10.1093/hr/uhad183 |
[35] |
Song A, Su J, Wang H, Zhang Z, Zhang X, et al. 2023. Analyses of a chromosome-scale genome assembly reveal the origin and evolution of cultivated chrysanthemum. Nature Communications 14:2021 doi: 10.1038/s41467-023-37730-3 |
[36] |
An Y, Chen L, Tao L, Liu S, Wei C. 2021. QTL mapping for leaf area of tea plants (Camellia sinensis) based on a high-quality genetic map constructed by whole genome resequencing. Frontiers in Plant Science 12:705285 doi: 10.3389/fpls.2021.705285 |
[37] |
Wu Y, Wang Y, Fan X, Zhang Y, Jiang J, et al. 2023. QTL mapping for berry shape based on a high-density genetic map constructed by whole-genome resequencing in grape. Horticultural Plant Journal 9:729−42 doi: 10.1016/j.hpj.2022.11.005 |
[38] |
Qin M, Li L, Singh J, Sun M, Bai B, et al. 2022. Construction of a high-density bin-map and identification of fruit quality-related quantitative trait loci and functional genes in pear. Horticulture Research 9:uhac141 doi: 10.1093/hr/uhac141 |
[39] |
Yang S, Fresnedo-Ramírez J, Sun Q, Manns DC, Sacks GL, et al. 2016. Next generation mapping of enological traits in an F2 interspecific grapevine hybrid family. PLoS ONE 11:e0149560 doi: 10.1371/journal.pone.0149560 |
[40] |
Wang H, Yan A, Sun L, Zhang G, Wang X, et al. 2020. Novel stable QTLs identification for berry quality traits based on high-density genetic linkage map construction in table grape. BMC Plant Biology 20:411 doi: 10.1186/s12870-020-02630-x |
[41] |
Wang Z, He D, Gao W, Li M, Wu X, Lv J. 2022. Integrated transcriptomic and metabolomic analyses of 'Guifei' mango fruit flavor in an endospermic genotype and a mutated genotype without endosperm. Scientia Horticulturae 303:111189 doi: 10.1016/j.scienta.2022.111189 |
[42] |
Zhang B, Chen W, Li X, Ren W, Chen L, et al. 2021. Map-based cloning and promoter variation analysis of the lobed leaf gene BoLMI1a in ornamental kale (Brassica oleracea L. var. acephala). BMC Plant Biology 21:456 doi: 10.1186/s12870-021-03223-y |
[43] |
Cheng B, Wan H, Han Y, Yu C, Luo L, et al. 2021. Identification and QTL analysis of flavonoids and carotenoids in tetraploid roses based on an ultra-high-density genetic map. Frontiers in Plant Science 12:682305 doi: 10.3389/fpls.2021.682305 |
[44] |
Song B, Ning W, Wei D, Jiang M, Zhu K, et al. 2023. Plant genome resequencing and population genomics: current status and future prospects. Molecular Plant 16:1252−68 doi: 10.1016/j.molp.2023.07.009 |
[45] |
Dong Y, Duan S, Xia Q, Liang Z, Dong X, et al. 2023. Dual domestications and origin of traits in grapevine evolution. Science 379:892−901 doi: 10.1126/science.add8655 |
[46] |
Leroy T, Albert E, Thouroude T, Baudino S, Caissard JC, et al. 2024. Dark side of the honeymoon: reconstructing the Asian x European rose breeding history through the lens of genomics. bioRxiv doi: 10.1101/2023.06.22.546162 |
[47] |
Zhang Z, Liu Y, Yang T, Wu S, Sun H, et al. 2023. Haplotype-resolve genome assembly and resequencing provide insights into the origin and domestication of modern rose. bioRxiv doi: 10.1101/2023.06.02.543351 |
[48] |
Wei K, Wang X, Hao X, Qian Y, Li X, et al. 2022. Development of a genome-wide 200K SNP array and its application for high-density genetic mapping and origin analysis of Camellia sinensis. Plant Biotechnology Journal 20:414−16 doi: 10.1111/pbi.13761 |
[49] |
Wang R, Xing S, Bourke PM, Qi X, Lin M, et al. 2023. Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit. Plant Biotechnology Journal 21:369−80 doi: 10.1111/pbi.13958 |
[50] |
Koning-Boucoiran CFS, Esselink GD, Vukosavljev M, van't Westende WPC, Gitonga VW, et al. 2015. Using RNA-Seq to assemble a rose transcriptome with more than 13, 000 full-length expressed genes and to develop the WagRhSNP 68k Axiom SNP array for rose (Rosa L.). Frontiers in Plant Science 6:249 doi: 10.3389/fpls.2015.00249 |
[51] |
Hamilton JP, Hansey CN, Whitty BR, Stoffel K, Massa AN, et al. 2011. Single nucleotide polymorphism discovery in elite north american potato germplasm. BMC Genomics 12:302 doi: 10.1186/1471-2164-12-302 |
[52] |
You Q, Yang X, Peng Z, Islam MS, Sood S, et al. 2019. Development of an Axiom Sugarcane100K SNP array for genetic map construction and QTL identification. Theoretical and Applied Genetics 132:2829−45 doi: 10.1007/s00122-019-03391-4 |
[53] |
Li N, He Q, Wang J, Wang B, Zhao J, et al. 2023. Super-pangenome analyses highlight genomic diversity and structural variation across wild and cultivated tomato species. Nature Genetics 55:852−60 doi: 10.1038/s41588-023-01340-y |
[54] |
Shi J, Tian Z, Lai J, Huang X. 2023. Plant pan-genomics and its applications. Molecular Plant 16:168−86 doi: 10.1016/j.molp.2022.12.009 |
[55] |
Liu F, Zhao J, Sun H, Xiong C, Sun X, et al. 2023. Genomes of cultivated and wild Capsicum species provide insights into pepper domestication and population differentiation. Nature Communications 14:5487 doi: 10.1038/s41467-023-41251-4 |
[56] |
Gao L, Gonda I, Sun H, Ma Q, Bao K, et al. 2019. The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor. Nature Genetics 51:1044−51 doi: 10.1038/s41588-019-0410-2 |
[57] |
Zhou Y, Zhang Z, Bao Z, Li H, Lyu Y, et al. 2022. Graph pangenome captures missing heritability and empowers tomato breeding. Nature 606:527−34 doi: 10.1038/s41586-022-04808-9 |
[58] |
Huang Y, He J, Xu Y, Zheng W, Wang S, et al. 2023. Pangenome analysis provides insight into the evolution of the orange subfamily and a key gene for citric acid accumulation in citrus fruits. Nature Genetics 55:1964−75 doi: 10.1038/s41588-023-01516-6 |
[59] |
Liu H, Wang X, Liu S, Huang Y, Guo Y, et al. 2022. Citrus Pan-Genome to Breeding Database (CPBD): a comprehensive genome database for citrus breeding. Molecular Plant 15:1503−05 doi: 10.1016/j.molp.2022.08.006 |
[60] |
Song J, Guan Z, Hu J, Guo C, Yang Z, et al. 2020. Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus. Nature Plants 6:34−45 doi: 10.1038/s41477-019-0577-7 |
[61] |
Sun X, Jiao C, Schwaninger H, Chao CT, Ma Y, et al. 2020. Phased diploid genome assemblies and pan-genomes provide insights into the genetic history of apple domestication. Nature Genetics 52:1423−32 doi: 10.1038/s41588-020-00723-9 |
[62] |
Hübner S, Bercovich N, Todesco M, Mandel JR, Odenheimer J, et al. 2019. Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance. Nature Plants 5:54−62 doi: 10.1038/s41477-018-0329-0 |
[63] |
Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, et al. 2016. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nature Genetics 48:481−87 doi: 10.1038/ng.3538 |
[64] |
Lanctot A. 2022. The time is ripe for eQTLs: transcriptomic identification of a tomato fruit ripening regulator. Plant Physiology 190:182−84 doi: 10.1093/plphys/kiac287 |
[65] |
Peng L, Li Y, Tan W, Wu S, Hao Q, et al. 2023. Combined genome-wide association studies and expression quantitative trait locus analysis uncovers a genetic regulatory network of floral organ number in a tree peony (Paeonia suffruticosa Andrews) breeding population. Horticulture Research 10:uhad110 doi: 10.1093/hr/uhad110 |
[66] |
Zhang L, Yu Y, Shi T, Kou M, Sun J, et al. 2020. Genome-wide analysis of expression quantitative trait loci (eQTLs) reveals the regulatory architecture of gene expression variation in the storage roots of sweet potato. Horticulture Research 7:90 doi: 10.1038/s41438-020-0314-4 |
[67] |
Tang S, Zhao H, Lu S, Yu L, Zhang G, et al. 2021. Genome- and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus. Molecular Plant 14:470−87 doi: 10.1016/j.molp.2020.12.003 |
[68] |
Tan Z, Peng Y, Xiong Y, Xiong F, Zhang Y, et al. 2022. Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus. Genome Biology 23:233 doi: 10.1186/s13059-022-02801-z |
[69] |
Zhang Y, Zhang H, Zhao H, Xia Y, Zheng X, et al. 2022. Multi-omics analysis dissects the genetic architecture of seed coat content in Brassica napus. Genome Biology 23:86 doi: 10.1186/s13059-022-02647-5 |
[70] |
Szymański J, Bocobza S, Panda S, Sonawane P, Cárdenas PD, et al. 2020. Analysis of wild tomato introgression lines elucidates the genetic basis of transcriptome and metabolome variation underlying fruit traits and pathogen response. Nature Genetics 52:1111−21 doi: 10.1038/s41588-020-0690-6 |
[71] |
Yuan P, Xu C, He N, Lu X, Zhang X, et al. 2023. Watermelon domestication was shaped by stepwise selection and regulation of the metabolome. Science China Life Sciences 66:579−94 doi: 10.1007/s11427-022-2198-5 |
[72] |
Cao K, Wang B, Fang W, Zhu G, Chen C, et al. 2022. Combined nature and human selections reshaped peach fruit metabolome. Genome Biology 23:146 doi: 10.1186/s13059-022-02719-6 |
[73] |
Lin Q, Chen J, Liu X, Wang B, Zhao Y, et al. 2023. A metabolic perspective of selection for fruit quality related to apple domestication and improvement. Genome Biology 24:95 doi: 10.1186/s13059-023-02945-6 |
[74] |
Gitonga VW, Stolker R, Koning-Boucoiran CFS, Aelaei M, Visser RGF, et al. 2016. Inheritance and QTL analysis of the determinants of flower color in tetraploid cut roses. Molecular Breeding 36:143 doi: 10.1007/s11032-016-0565-9 |
[75] |
Schulz DF, Schott RT, Voorrips RE, Smulders MJM, Linde M, et al. 2016. Genome-wide association analysis of the anthocyanin and carotenoid contents of rose petals. Frontiers in Plant Science 7:1798 doi: 10.3389/fpls.2016.01798 |
[76] |
Kosová K, Vítámvás P, Klíma M, Prášil IT. 2019. Breeding drought-resistant crops: G×E interactions, proteomics and pQTLS. Journal of Experimental botany 70:2605−08 doi: 10.1093/jxb/erz116 |
[77] |
Mergner J, Kuster B. 2022. Plant proteome dynamics. Annual Review of Plant Biology 73:67−92 doi: 10.1146/annurev-arplant-102620-031308 |
[78] |
Jiang L, Li B, Liu S, Wang H, Li C, et al. 2019. Characterization of proteome variation during modern maize breeding. Molecular & Cellular Proteomics 18:263−76 doi: 10.1074/mcp.RA118.001021 |
[79] |
Zhou Q, Fu Z, Liu H, Wang J, Guo Z, et al. 2021. Mining novel kernel size-related genes by pQTL mapping and multi-omics integrative analysis in developing maize kernels. Plant Biotechnology Journal 19:1489−91 doi: 10.1111/pbi.13634 |
[80] |
Liu Z, Yang B, Huang R, Suo H, Zhang Z, et al. 2022. Transcriptome- and proteome-wide association of a recombinant inbred line population revealed twelve core QTLs for four fruit traits in pepper (Capsicum annuum L.). Horticulture Research 9:uhac015 doi: 10.1093/hr/uhac015 |
[81] |
Liu X, Zhu K, Xiao J. 2023. Recent advances in understanding of the epigenetic regulation of plant regeneration. aBIOTECH 4:31−46 doi: 10.1007/s42994-022-00093-2 |
[82] |
Gahlaut V, Zinta G, Jaiswal V, Kumar S. 2020. Quantitative epigenetics: a new avenue for crop improvement. Epigenomes 4:25 doi: 10.3390/epigenomes4040025 |
[83] |
Johannes F, Porcher E, Teixeira FK, Saliba-Colombani V, Simon M, et al. 2009. Assessing the impact of transgenerational epigenetic variation on complex traits. PLoS Genetics 5:e1000530 doi: 10.1371/journal.pgen.1000530 |
[84] |
Cortijo S, Wardenaar R, Colomé-Tatché M, Gilly A, Etcheverry M, et al. 2014. Mapping the epigenetic basis of complex traits. Science 343:1145−48 doi: 10.1126/science.1248127 |
[85] |
Long Y, Xia W, Li R, Wang J, Shao M, et al. 2011. Epigenetic QTL mapping in Brassica napus. Genetics 189:1093−102 doi: 10.1534/genetics.111.131615 |
[86] |
Guo H, Cao P, Wang C, Lai J, Deng Y, et al. 2023. Population analysis reveals the roles of DNA methylation in tomato domestication and metabolic diversity. Science China Life Sciences 66:1888−902 doi: 10.1007/s11427-022-2299-5 |
[87] |
Han Y, Lu M, Yue S, Li K, Dong M, et al. 2022. Comparative methylomics and chromatin accessibility analysis in Osmanthus fragrans uncovers regulation of genic transcription and mechanisms of key floral scent production. Horticulture Research 9:uhac096 doi: 10.1093/hr/uhac096 |
[88] |
Tang M, Xue W, Li X, Wang L, Wang M, et al. 2022. Mitotically heritable epigenetic modifications of CmMYB6 control anthocyanin biosynthesis in chrysanthemum. New Phytologist 236:1075−88 doi: 10.1111/nph.18389 |
[89] |
French A, Ubeda-Tomás S, Holman TJ, Bennett MJ, Pridmore T. 2009. High-throughput quantification of root growth using a novel image-analysis tool. Plant Physiology 150:1784−95 doi: 10.1104/pp.109.140558 |
[90] |
Campbell ZC, Acosta-Gamboa LM, Nepal N, Lorence A. 2018. Engineering plants for tomorrow: how high-throughput phenotyping is contributing to the development of better crops. Phytochemistry Reviews 17:1329−43 doi: 10.1007/s11101-018-9585-x |
[91] |
Yang W, Feng H, Zhang X, Zhang J, Doonan JH, et al. 2020. Crop phenomics and high-throughput phenotyping: past decades, current challenges, and future perspectives. Molecular Plant 13:187−214 doi: 10.1016/j.molp.2020.01.008 |
[92] |
van der Heijden G, Song Y, Horgan G, Polder G, Dieleman A, et al. 2012. SPICY: towards automated phenotyping of large pepper plants in the greenhouse. Functional Plant Biology 39:870−77 doi: 10.1071/FP12019 |
[93] |
Knoch D, Abbadi A, Grandke F, Meyer RC, Samans B, et al. 2020. Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola. Plant Biotechnology Journal 18:68−82 doi: 10.1111/pbi.13171 |
[94] |
Zhang G, Zhou J, Peng Y, Tan Z, Zhang Y, et al. 2023. High-throughput phenotyping-based quantitative trait loci mapping reveals the genetic architecture of the salt stress tolerance of Brassica napus. Plant, Cell & Environment 46:549−66 doi: 10.1111/pce.14485 |
[95] |
Li-Marchetti C, Le Bras C, Chastellier A, Relion D, Morel P, et al. 2017. 3D phenotyping and QTL analysis of a complex character: rose bush architecture. Tree Genetics & Genomes 13:112 doi: 10.1007/s11295-017-1194-0 |
[96] |
da Silva Souza J, Pedrosa LM, de Almeida Moreira BR, do Rêgo ER, Unêda-Trevisoli SH. 2022. The more fractal the architecture the more intensive the color of flower: a superpixel-wise analysis towards high-throughput phenotyping. Agronomy 12:1342 doi: 10.3390/agronomy12061342 |
[97] |
Zhang C, Craine WA, McGee RJ, Vandemark GJ, Davis JB, et al. 2020. Image-based phenotyping of flowering intensity in cool-season crops. Sensors 20:1450 doi: 10.3390/s20051450 |
[98] |
Cembrowska-Lech D, Krzemińska A, Miller T, Nowakowska A, Adamski C, et al. 2023. An integrated multi-omics and artificial intelligence framework for advance plant phenotyping in horticulture. Biology 12:1298 doi: 10.3390/biology12101298 |