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For: Bhat JA, Yu D, Bohra A, Ganie SA, Varshney RK. Features and applications of haplotypes in crop breeding. Commun Biol 2021;4:1266. [PMID: 34737387 DOI: 10.1038/s42003-021-02782-y] [Cited by in Crossref: 16] [Cited by in F6Publishing: 18] [Article Influence: 16.0] [Reference Citation Analysis]
Number Citing Articles
1 Liang Z, Myers ZA, Petrella D, Engelhorn J, Hartwig T, Springer NM. Mapping responsive genomic elements to heat stress in a maize diversity panel. Genome Biol 2022;23:234. [DOI: 10.1186/s13059-022-02807-7] [Reference Citation Analysis]
2 Hore TK, Inabangan-asilo MA, Wulandari R, Latif MA, Nihad SAI, Hernandez JE, Gregorio GB, Dalisay TU, Diaz MGQ, Ch. B, Swamy BPM. Introgression of tsv1 improves tungro disease resistance of a rice variety BRRI dhan71. Sci Rep 2022;12:18820. [DOI: 10.1038/s41598-022-23413-4] [Reference Citation Analysis]
3 Akhmetova MM, Rubel MS, Afanasenko OS, Kolpashchikov DM. Barley haplotyping using biplex deoxyribozyme nanomachine. Sensors and Actuators Reports 2022. [DOI: 10.1016/j.snr.2022.100132] [Reference Citation Analysis]
4 Yoosefzadeh-najafabadi M, Rajcan I, Eskandari M. Optimizing genomic selection in soybean: An important improvement in agricultural genomics. Heliyon 2022. [DOI: 10.1016/j.heliyon.2022.e11873] [Reference Citation Analysis]
5 Seyum EG, Bille NH, Abtew WG, Munyengwa N, Bell JM, Cros D. Genomic selection in tropical perennial crops and plantation trees: a review. Mol Breeding 2022;42. [DOI: 10.1007/s11032-022-01326-4] [Reference Citation Analysis]
6 Sawangkaew N, Jamboonsri W, Arikit S, Wanchana S, Toojinda T, Darwell CT. Evaluating haplotype associations for brown planthopper resistance in rice using the HAPLOANNOTATOR bioinformatics tool.. [DOI: 10.21203/rs.3.rs-2090719/v1] [Reference Citation Analysis]
7 Khan MHU, Wang S, Wang J, Ahmar S, Saeed S, Khan SU, Xu X, Chen H, Bhat JA, Feng X. Applications of Artificial Intelligence in Climate-Resilient Smart-Crop Breeding. IJMS 2022;23:11156. [DOI: 10.3390/ijms231911156] [Reference Citation Analysis]
8 Lorenzo CD, Debray K, Herwegh D, Develtere W, Impens L, Schaumont D, Vandeputte W, Aesaert S, Coussens G, De Boe Y, Demuynck K, Van Hautegem T, Pauwels L, Jacobs TB, Ruttink T, Nelissen H, Inzé D. BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize. Plant Cell 2022:koac243. [PMID: 36066192 DOI: 10.1093/plcell/koac243] [Reference Citation Analysis]
9 Bhat JA, Adeboye KA, Ganie SA, Barmukh R, Hu D, Varshney RK, Yu D. Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.). Front Genet 2022;13. [DOI: 10.3389/fgene.2022.953833] [Reference Citation Analysis]
10 Devasirvatham V, Tan DKY. Key Determinants of the Physiological and Fruit Quality Traits in Sweet Cherries and Their Importance in a Breeding Programme. Horticulturae 2022;8:694. [DOI: 10.3390/horticulturae8080694] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
11 Liang Z, Myers ZA, Petrella D, Engelhorn J, Hartwig T, Springer NM. Mapping Responsive Genomic Elements to Heat Stress in a Maize Diversity Panel.. [DOI: 10.1101/2022.06.23.497238] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Zenda T, Wang N, Dong A, Zhou Y, Duan H. Reproductive-Stage Heat Stress in Cereals: Impact, Plant Responses and Strategies for Tolerance Improvement. IJMS 2022;23:6929. [DOI: 10.3390/ijms23136929] [Reference Citation Analysis]
13 Feng X, Hafeez Ullah Khan M. Soybean Molecular Design Breeding. Plant Breeding - New Perspectives [Working Title] 2022. [DOI: 10.5772/intechopen.105422] [Reference Citation Analysis]
14 Chakraborty A, Viswanath A, Malipatil R, Semalaiyappan J, Shah P, Ronanki S, Rathore A, Singh SP, Govindaraj M, Tonapi VA, Thirunavukkarasu N. Identification of Candidate Genes Regulating Drought Tolerance in Pearl Millet. IJMS 2022;23:6907. [DOI: 10.3390/ijms23136907] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
15 Thomson MJ, Biswas S, Tsakirpaloglou N, Septiningsih EM. Functional Allele Validation by Gene Editing to Leverage the Wealth of Genetic Resources for Crop Improvement. Int J Mol Sci 2022;23:6565. [PMID: 35743007 DOI: 10.3390/ijms23126565] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
16 Darwell CT, Wanchana S, Ruanjaichon V, Siangliw M, Thunnom B, Aesomnuk W, Toojinda T. riceExplorer: Uncovering the Hidden Potential of a National Genomic Resource Against a Global Database. Front Plant Sci 2022;13:781153. [DOI: 10.3389/fpls.2022.781153] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
17 Pal N, Kumar Saini D, Kumar S. Breaking Yield Ceiling in Wheat: Progress and Future Prospects. Wheat [Working Title] 2022. [DOI: 10.5772/intechopen.102919] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
18 Raza A, Tabassum J, Zahid Z, Charagh S, Bashir S, Barmukh R, Khan RSA, Barbosa F Jr, Zhang C, Chen H, Zhuang W, Varshney RK. Advances in "Omics" Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants. Front Plant Sci 2021;12:794373. [PMID: 35058954 DOI: 10.3389/fpls.2021.794373] [Cited by in Crossref: 14] [Cited by in F6Publishing: 15] [Article Influence: 14.0] [Reference Citation Analysis]
19 Bohra A, Tiwari A, Satheesh Naik SJ, Maurya AK, Yadav V, Datta D, Singh F, Varshney RK. Breeding and Genomics of Pigeonpea in the Post-NGS Era. Compendium of Plant Genomes 2022. [DOI: 10.1007/978-3-031-00848-1_15] [Reference Citation Analysis]
20 Bohra A, Bansal KC, Graner A. The 3366 chickpea genomes for research and breeding. Trends Plant Sci 2021:S1360-1385(21)00323-X. [PMID: 34865982 DOI: 10.1016/j.tplants.2021.11.017] [Reference Citation Analysis]