Integrating image‐based phenotyping and marker‐assisted selection to optimize the selection of potato clones for chipping and resistance to viruses X and Y

Abstract Potato ( Solanum tuberosum L.) is the most important non‐cereal crop for global food security. To meet the demands of the processing, potato clones with good frying quality and industrial yield and resistance to major viral diseases are required. This study aimed to integrate image‐based phenotyping and marker‐assisted selection to optimize the selection of potato clones for potato chip processing and virus resistance. A total of 39 clones were evaluated in comparison with the cultivar Atlantic at two locations in Minas Gerais, Brazil. The trials were conducted during the 2022 and 2023 winter seasons. Agronomic traits included total tuber yield and dry matter content, while image‐based phenotyping quantified chips color through the L * axis of the CIELAB color system. The data were subjected to individual and multi‐environment analyses of variance. All clones were compared with the cultivar Atlantic using Dunnett's test, based on the means of the multi‐environment analysis. Clones were also tested for molecular markers linked to the Ry adg and Rx 1 alleles, which provide resistance to potato virus Y and potato virus X, respectively. The clone CCF25‐08 exhibited high tuber yield and dry matter content with simultaneous resistance to both viral diseases, suggesting it is a promising candidate as a parental line or for release as a new cultivar. The integration of image‐based phenotyping and marker‐assisted selection proved effective for the colorimetric differentiation of chips and the identification of virus‐resistant clones. This approach can improve experimental accuracy in potato breeding programs by reducing subjectivity in evaluations and accelerating the development of potato clones suitable for the processing.