PGT_2026v17n3

Plant Gene and Trait 2026, Vol.17, No.3, 182-196 http://genbreedpublisher.com/index.php/pgt 195 Chen J.B., Guo Y.F., Hu H.C., Fang C.L., Wang L.R., Hu L.L., Lin Z.H., Zhang D.Y.D., Yang Z.Y., and Wu Y.Y., 2025, Regulation of cell metabolism and changes in berry shape of Shine Muscat grapevines under the influence of different treatments with the plant growth regulators gibberellin A3 and N-(2-chloro-4-pyridyl)-N′-phenylurea, Horticulturae, 11(10): 1160. https://doi.org/10.3390/horticulturae11101160 Choi S., Ban S., and Choi C., 2023, The impact of plant growth regulators and floral cluster thinning on the fruit quality of ‘Shine Muscat’ grape, Horticulturae, 9(3): 392. https://doi.org/10.3390/horticulturae9030392 Dauelsberg P., Matus J.T., Poupin M.J., Leiva-Ampuero A., Godoy F., Vega A., and Arce-Johnson P., 2011, Effect of pollination and fertilization on the expression of genes related to floral transition, hormone synthesis and berry development in grapevine, Journal of Plant Physiology, 168(14): 1667-1674. https://doi.org/10.1016/j.jplph.2011.03.006 De Oliveira G.A., Francisco F.R., De Moura Y., Niederauer G., Fritsche-Neto R., De Souza A.P., and Furlan M., 2026, Genome-wide association study in a diverse grapevine collection provides insights into the genetic basis of berry size and cluster architecture traits, PLOS One, 21(3): e0343491. https://doi.org/10.1101/2025.09.24.678328 De Sousa Moreira L., Clark M., Tabb A., Karn A., Londo J., Zou C., Sun Q., Van Zyl S., Prins B., DeLong J., Burhans A., Yang H., and Naegele R., 2024, Identification of novel quantitative trait loci associated with table grape fruit quality characteristics in a segregating population and transferability of existing quality markers, Journal of the American Society for Horticultural Science, 149(1): 50-60. https://doi.org/10.21273/JASHS05334-23 Dhakad A.K., Patel V.B., Singh S.K., Verma M.K., Mishra G.P., Mhetre V., Kumar C., Singh R., Rajkumar S., and Gaikwad K., 2024, Pollen biology and metaxenic studies on early maturing grape (Vitis vinifera) genotypes, The Indian Journal of Agricultural Sciences, 94(10): 1094-1099. https://doi.org/10.56093/ijas.v94i10.141725 Dobrei A., and Sala F., 2025, Morphological parameters in grape bunches and berries evaluation through multivariate analysis: case study on the ‘Feteasca Regala’ cultivar, Life Science and Sustainable Development, 6(1): 0jpjmz10. https://doi.org/10.58509/0jpjmz10 Du W., and Liu P., 2023, Instance segmentation and berry counting of table grape before thinning based on AS-SwinT, Plant Phenomics, 5: 0085. https://doi.org/10.34133/plantphenomics.0085 García-Abadillo J., Barba P., Carvalho T., Sosa-Zuñiga V., Lozano R., Carvalho H.F., Garcia-Rojas M., Salazar E., and Sánchez J.I., 2024, Dissecting the complex genetic basis of pre-and post-harvest traits in Vitis vinifera L. using genome-wide association studies, Horticulture Research, 11(2): uhad283. https://doi.org/10.1093/hr/uhad283 Gharate P., Somkuwar R., Kumar A., Nilima G., Kakade P., and Karande P., 2025, Morphological and fruit variability of grape (Vitis vinifera L.) germplasm under subtropical condition, Plant Science Today, 12(sp1): 1-7. https://doi.org/10.14719/pst.7521 Güler E., and Karadeniz T., 2023, Discrimination of an untouched autochthonous grapevine (Vitis vinifera L.) population by morphological markers and multivariate analyses, Erwerbs-Obstbau, 65: 2075-2084. https://doi.org/10.1007/s10341-023-00926-4 Herzog K., Kicherer A., Malagol N., Trapp O., and Töpfer R., 2025, High-throughput phenotyping in grapevine breeding research: technologies and applications, OENO One, 59(3): 7-11. https://doi.org/10.20870/oeno-one.2025.59.3.8458 Imbernón-Mulero A., Maestre-Valero J.F., Martínez-Álvarez V., García-García F., Jódar-Conesa F.J., and Gallego-Elvira B., 2023, Evaluation of an autonomous smart system for optimal management of fertigation with variable sources of irrigation water, Frontiers in Plant Science, 14: 1149956. https://doi.org/10.3389/fpls.2023.1149956 Jewan S.Y.Y., Gautam D., Sparkes D.L., Singh A., Billa L., Cogato A., Murchie E.H., and Pagay V., 2024, Integrating hyperspectral, thermal, and ground data with machine learning algorithms enhances the prediction of grapevine yield and berry composition, Remote Sensing, 16(23): 4539. https://doi.org/10.3390/rs16234539 Khalil U., Rajwana I.A., Razzaq K., Brecht J.K., and Sarkhosh A., 2023, The impact of fruit thinning on size and quality of fresh-market muscadine berries, Journal of the Science of Food and Agriculture, 104(4): 2198-2203. https://doi.org/10.1002/jsfa.13105 Kim E., Lee C.H., Park S.M., Hong S.J., Kim S.H., and Kim G., 2023, A shine muscat grape berry detection and grape cluster compactness estimation for assessment of grape quality based on instance segmentation methods, Journal of the ASABE, 66(5): 1175-1185. https://doi.org/10.13031/ja.15503 Lee L., Reynolds A., Dorin B., and Shemrock A., 2025, A feasibility study on utilizing remote sensing data to monitor grape yield and berry composition for selective harvesting, Plants, 14(1): 88. https://doi.org/10.3390/plants14010088 Liu Z.J., Wang N., Su Y., Long Q.M., Peng Y.L., Guan S., Zhang F., Cao S., Wang X., Ge M.Q., Xue H., Ma Z.Y. Liu W.W., Xu X.D., Li C.C., Cao X.J., Ahmad B., Su X.G., Liu Y.T., Huang G.Z., Du M.R., Liu Z.Y., Gan Y., Sun L., Fan X.C., Zhang C., Zhong H.X., Leng X., Ren Y.P., Dong T.Y., Pei D., Wu X.Y., Jin Z.X., Wang Y.W., Liu C.H., Chen J.F., Gaut B.S., Huang S.W., Fang J.G., Xiao H., and Zhou Y.F., 2024, Grapevine pangenome facilitates trait genetics and genomic breeding, Nature Genetics, 56: 2804-2814. https://doi.org/10.1038/s41588-024-01967-5

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