Bioscience Methods 2025, Vol.16, No.2, 100-107 http://bioscipublisher.com/index.php/bm 107 Nawae W., Naktang C., Charoensri S., U-Thoomporn S., Narong N., Chusri O., Tangphatsornruang S., and Pootakham W., 2023, Resequencing of durian genomes reveals large genetic variations among different cultivars, Frontiers in Plant Science, 14: 1137077. https://doi.org/10.3389/fpls.2023.1137077 Peixoto M., Coelho I., Leach K., Bhering L., and Resende M., 2023, Simulation based decision making and implementation of tools in hybrid crop breeding pipelines, Crop Science, 64(1): 110-125. https://doi.org/10.1002/csc2.21139 Rembe M., Zhao Y., Jiang Y., and Reif J., 2018, Reciprocal recurrent genomic selection: an attractive tool to leverage hybrid wheat breeding, Theoretical and Applied Genetics, 132: 687-698. https://doi.org/10.1007/s00122-018-3244-x Renzi J., Coyne C., Berger J., Von Wettberg E., Nelson M., Ureta S., Hernández F., Smýkal P., and Brus J., 2022, How could the use of crop wild relatives in breeding increase the adaptation of crops to marginal environments, Frontiers in Plant Science, 13: 886162. https://doi.org/10.3389/fpls.2022.886162 Richards R., Rebetzke G., Watt M., Condon A., Spielmeyer W., and Dolferus R., 2010, Breeding for improved water productivity in temperate cereals: phenotyping, quantitative trait loci, markers and the selection environment, Functional Plant Biology, 37: 85-97. https://doi.org/10.1071/FP09219 Salgotra R., and Stewart C., 2020, Functional markers for precision plant breeding, International Journal of Molecular Sciences, 21(13): 4792. https://doi.org/10.3390/ijms21134792 Sankaran S., Khot L., Espinoza C., Jarolmasjed S., Sathuvalli V., Vandemark G., Miklas P., Carter A., Pumphrey M., Knowles N., and Pavek M., 2015, Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: a review, European Journal of Agronomy, 70: 112-123. Tang R., Wei S., Tang J., Aridas N., and Talip M., 2024, A method for durian precise fertilization based on improved radial basis neural network algorithm, Frontiers in Plant Science, 15: 1387977. https://doi.org/10.3389/fpls.2024.1387977 Tiwari J., Yerasu S., Rai N., Singh D., Singh A., Karkute S., Singh P., and Behera T., 2022, Progress in marker-assisted selection to genomics-assisted breeding in tomato, Critical Reviews in Plant Sciences, 41: 321-350. Wang Y.F., and Zhang L.M., 2024, Gene-driven future: breakthroughs and applications of marker-assisted selection in tree breeding, Molecular Plant Breeding, 15(3): 132-143. Xu Y., Lu Y., Xie C., Gao S., Wan J., and Prasanna B., 2012, Whole-genome strategies for marker-assisted plant breeding, Molecular Breeding, 29: 833-854. Yue G., 2013, Recent advances of genome mapping and marker‐assisted selection in aquaculture, Fish and Fisheries, 15: 376-396. Zhang F., and Batley J., 2020, Exploring the application of wild species for crop improvement in a changing climate, Current Opinion in Plant Biology, 56: 218-222. https://doi.org/10.1016/j.pbi.2019.12.013 Zhang H., Zhang J., Lang Z., Botella J., and Zhu J., 2017, Genome editing-principles and applications for functional genomics research and crop improvement, Critical Reviews in Plant Sciences, 36: 291-309. Zhou J., Luan X., Liu Y., Wang L., Wang J., Yang S., Liu S., Zhang J., Liu H., and Yao D., 2023, Strategies and methods for improving the efficiency of CRISPR/Cas9 gene editing in plant molecular breeding, Plants, 12(7): 1478. https://doi.org/10.3390/plants12071478
RkJQdWJsaXNoZXIy MjQ4ODYzNA==