Keywords: decoding modules, SNP array, ELF4 function, semantic segmentation, drought stress

Latest 42 Papers

A sublethal drought and rewatering time course reveals intricate patterning of responses in the annual Arabidopsis thaliana

Authors: Fitzek-Campbell, E., Psaroudakis, D., Weisshaar, B., Junker, A., Braeutigam, A.

Date: 2025-07-27 · Version: 1

DOI: 10.1101/2025.07.25.666782

Model Organism: Arabidopsis thaliana

drought stress Arabidopsis thaliana transcriptomics high‑throughput phenotyping biomarker transcripts

Identification of a volatile chemotype associated with resilience to water stress in domesticated varieties of Cotton

Authors: Frost, C., Johnson, S., Pauli, D., Melandri, G.

Date: 2025-07-21 · Version: 1

DOI: 10.1101/2025.07.16.665191

Model Organism: Gossypium hirsutum

volatile organic compounds chemotype drought stress Gossypium hirsutum sesquiterpenes

Contrasting needle physiological strategies to soil nutrient scarcity in radiata pine plantations

Authors: Ruiz de Larrinaga, L., San Miguel-Oti, F., Monasterio, A., Artetxe, U., Munne-Bosch, S., Mesa, T., Moreaux, C., Ortega-Barrueta, U., Sertutxa, U., Pena, L., Ametzaga, I., Yuste, J. C., Esteban, R.

Date: 2025-07-19 · Version: 1

DOI: 10.1101/2025.07.15.664982

Model Organism: Pinus radiata

Pinus radiata soil nutrient scarcity drought stress photosynthetic performance forest management

Integrative Multi-Omics Analysis Reveals Stress-Specific Molecular Architectures in Soybean under Drought and Rust Infection

Authors: Husein, G., Castro-Moretti, F. R., Prado, M., Amorim, L., Mazzafera, P., Canales, J., Monteiro-Vitorello, C. B.

Date: 2025-07-08 · Version: 1

DOI: 10.1101/2025.07.07.663534

Model Organism: Glycine max

Asian soybean rust drought stress transcriptomics metabolomics co-expression network

Drought stress modulates the molecular response of Arabidopsis plants to root-knot nematode infection

Authors: Refaiy, A., Lilley, C. J., Atkinson, N. J., Urwin, P. E.

Date: 2025-06-09 · Version: 1

DOI: 10.1101/2025.06.05.658137

Model Organism: Arabidopsis thaliana

combined biotic and abiotic stress drought stress root‑knot nematode (Meloidogyne incognita)RNA‑Seq transcriptomics Arabidopsis thaliana

Endophytes induce systemic spatial reprogramming of metabolism in poplar roots under drought

Authors: Aufrecht, J. A., Velickovic, D., Tournay, R., Couvillion, S. P., Balasubramanian, V. K., Winkler, T., Herrera, D., Stanley, R., Doty, S., Ahkami, A. H.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.02.657501

Model Organism: General

beneficial endophytes drought stress root metabolome chemical imaging machine learning

Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning

Authors: Tietze, H., Abdelhakim, L., Pleskacova, B., Kurtz-Sohn, A., Fridman, E., Nikoloski, Z., Panzarova, K.

Date: 2025-06-02 · Version: 1

DOI: 10.1101/2025.05.29.656856

Model Organism: Hordeum vulgare

high‑throughput phenotyping drought stress temporal modeling Barley (Hordeum vulgare)RGB imaging

Chiral monoterpene dynamics of shoots and roots of Norway spruce in response to drought

Authors: Daber, L. E., Kreuzwieser, J., Meischner, M., Williams, J., Werner, C.

Date: 2025-05-03 · Version: 1

DOI: 10.1101/2025.05.02.651829

Model Organism: Picea abies

chiral monoterpenes drought stress Norway spruce de novo synthesis tissue‑specific emissions

Iron retention coupled with trade-offs in localized symbiotic effects confers tolerance to combined iron deficiency and drought in soybean

Authors: Hasan, M. R., Thapa, A., Kabir, A. H.

Date: 2025-03-24 · Version: 2

DOI: 10.1101/2025.01.02.631154

Model Organism: Glycine max

soybean (Glycine max)iron deficiency drought stress root microbiome multi‑omics

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping

PreviousPage 3 of 5Next