Keywords: paralog processing, ascorbate, image-based phenotyping, ionomics

Latest 7 Papers

PlantCV v4: Image analysis software for high-throughput plant phenotyping

Authors: Schuhl, H., Brown, K. E., Sheng, H., Bhatt, P. K., Gutierrez, J., Schneider, D., Casto, A. L., Acosta-Gamboa, L., Ballenger, J. G., Barbero, F., Braley, J., Brown, A. M., Chavez, L., Cunningham, S., Dilhara, M., Dimech, A. M., Duenwald, J. G., Fischer, A., Gordon, J. M., Hendrikse, C., Hernandez, G. L., Hodge, J. G., Huber, M., Hurr, B. M., Jarolmasjed, S., Medina Jimenez, K., Kenney, S., Konkel, G., Kutschera, A., Lama, S., Lohbihler, M., Lorence, A., Luebbert, C., Ly, N., Manching, H. K., Marrano, A., Meerdink, S., Miklave, N. M., Mudrageda, P., Murphy, K. M., Peery, J. D., Pierik, R., Polyd

Date: 2025-11-20 · Version: 1

DOI: 10.1101/2025.11.19.689271

Model Organism: General

PlantCV image-based phenotyping fluorescence imaging thermal imaging hyperspectral imaging

Integrating image-based phenotyping and GWAS to map tolerance to Spittlebug nymphs in interspecific Urochloa grasses

Authors: Espitia-Buitrago, P., Perea, C., Mejia-Medina, J. C., Hernandez, L. M., Castiblanco, V., Ryan, C., De Vega, J. J., Jauregui, R. N.

Date: 2025-11-05 · Version: 1

DOI: 10.1101/2025.11.03.686394

Model Organism: Urochloa spp.

Urochloa spittlebug tolerance GWAS QTL image-based phenotyping

Phylogenomic challenges in polyploid-rich lineages: Insights from paralog processing and reticulation methods using the complex genus Packera (Asteraceae: Senecioneae)

Authors: Moore-Pollard, E. R., Ellestad, P., Mandel, J.

Date: 2025-10-13 · Version: 2

DOI: 10.1101/2025.09.14.676143

Model Organism: Multi-species

phylogenomic discordance polyploidy paralog processing Packera historical biogeography

Phenotypic scoring of Canola Blackleg severity using machine learning image analysis

Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.

Date: 2025-07-22 · Version: 1

DOI: 10.1101/2025.07.17.665372

Model Organism: Multi-species

blackleg disease canola (Brassica spp.)deep learning image-based phenotyping disease severity scoring

Zinc deficiency induces spatially distinct responses in roots and impacts ZIP12-dependent zinc homeostasis in Arabidopsis

Authors: Thiebaut, N., Persson, D. P., Sarthou, M., Stevenne, P., Bosman, B., Carnol, M., Fanara, S., Verbruggen, N., Hanikenne, M.

Date: 2025-06-30 · Version: 1

DOI: 10.1101/2025.06.26.661794

Model Organism: Arabidopsis thaliana

zinc deficiency root apical meristem ZIP12 transcriptomics ionomics

Arabidopsis lines with modified ascorbate concentrations reveal a link between ascorbate and auxin biosynthesis

Authors: Fenech, M., Zulian, V., Moya-Cuevas, J., Arnaud, D., Morilla, I., Smirnoff, N., Botella, M. A., Stepanova, A. N., Alonso, J. M., Martin-Pizarro, C., Amorim-Silva, V.

Date: 2025-05-16 · Version: 1

DOI: 10.1101/2025.05.15.654287

Model Organism: Arabidopsis thaliana

ascorbate Arabidopsis thaliana auxin biosynthesis redox homeostasis transcriptomics

Genetic control of the leaf ionome in pearl millet and correlation with root and agromorphological traits

Authors: Nakombo-Gbassault, P., Arenas, S., Affortit, P., Faye, A., Flis, P., Sine, B., Moukouanga, D., Gantet, P., Kosh Komba, E., Kane, N., Bennett, M., Wells, D., Cubry, P., Bailey, E., Vigouroux, Y., Grondin, A., Laplaze, L.

Date: 2025-02-03 · Version: 1

DOI: 10.1101/2025.01.30.635630

Model Organism: Pennisetum glaucum

ionomics nutrient acquisition pearl millet GWAS candidate genes