Keywords: paralog processing, deep learning, ascorbate, spatial transcriptomics, image‑based phenotyping

Latest 21 Papers

Deep learning of fossil pollen morphology reveals 25,000 years of ecological change in East African grasslands

Authors: Adaime, M.-E., Kong, S., Urban, M. A., Street-Perrott, F. A., Verschuren, D., Punyasena, S. W.

Date: 2026-01-22 · Version: 3

DOI: 10.1101/2024.09.23.612957

Model Organism: General

deep learning grass pollen morphology C3/C4 plant ratios paleo‑vegetation reconstruction super‑resolution microscopy

Reconstructing coniferous tree crown shape from incomplete point clouds using deep learning

Authors: Bornand, A., Abegg, M., Morsdorf, F., Puliti, S., Astrup, R., Rehush, N.

Date: 2026-01-21 · Version: 1

DOI: 10.64898/2026.01.18.700158

Model Organism: General

deep learning point cloud reconstruction alpha‑shape coniferous tree crowns geometry-aware transformer

Regulation of spikelet number during wheat spike development

Authors: Li, C., Li, K., Zhang, C., Dubcovsky, J.

Date: 2026-01-08 · Version: 1

DOI: 10.64898/2026.01.07.698073

Model Organism: Triticum aestivum

spikelet number per spike wheat inflorescence development florigen (FT1)spatial transcriptomics single‑cell analysis

Semi-automated image analysis of root architecture and early root development in faba bean and white clover and genomic estimation of breeding values and correlations

Authors: Nagy, I., Kristensen, P. S., Malinowska, M., Nielsen, L. K., Schiemann, A., Rolund, N., Andersen, S. U., Asp, T.

Date: 2025-12-03 · Version: 1

DOI: 10.64898/2025.12.01.691692

Model Organism: Multi-species

leguminous protein crops climate‑resilient breeding root architecture image‑based phenotyping genomic estimated breeding values

Cross-dataset evaluation of deep learning models for plant pest and disease diagnosis

Authors: Sun, J.

Date: 2025-11-03 · Version: 2

DOI: 10.1101/2024.10.07.617111

Model Organism: Solanum lycopersicum

deep learning cross-dataset generalization tomato pest and disease dataset variability model architecture

Spatiotemporal regulation of arbuscular mycorrhizal symbiosis at cellular resolution

Authors: Chancellor, T., Ferreras-Garrucho, G., Akmakjian, G. Z., Montero, H., Bowden, S. L., Hope, M., Wallington, E., Bhattacharya, S., Korfhage, C., Bailey-Serres, J., Paszkowski, U.

Date: 2025-11-02 · Version: 1

DOI: 10.1101/2025.10.31.685811

Model Organism: Oryza sativa

arbuscular mycorrhizal symbiosis spatial transcriptomics TRAP-seq arbuscule development nutrient transport

Hyperspectral Imaging to Quantify Nodules and Detect Biological Nitrogen Fixation in Legumes

Authors: Wang, Y., de Silva, K., Song, D., Kamruzzaman, M., Brooks, M. D.

Date: 2025-10-24 · Version: 3

DOI: 10.1101/2025.07.25.666867

Model Organism: Multi-species

root nodules biological nitrogen fixation hyperspectral imaging deep learning legume species

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

Botanic Spectrum Analyser: A Deep Learning GUI for Plant Image Segmentation in Hyperspectral and RGB Phenotyping

Authors: Walsh, J. J., Gorgu, L., Cavel, E., Poulain, V., Gutierrez, L., Mangina, E., Negrao, S.

Date: 2025-09-17 · Version: 1

DOI: 10.1101/2025.09.14.676080

Model Organism: Multi-species

plant phenotyping image segmentation U‑Net hyperspectral imaging deep learning

Spatial transcriptomics identifies distinct domains regulating yield-related traits of the wheat ear

Authors: Qu, Y., Tan, C., Yang, L., Pasquariello, M., Alabdullah, A. K., Sun, S., Iqbal, M., Salamon, J., Boden, S.

Date: 2025-08-13 · Version: 1

DOI: 10.1101/2025.08.12.670006

Model Organism: Triticum aestivum

spikelet development spatial transcriptomics wheat inflorescence RAMOSA2 ALOG1

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