Projects

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Creating high-resolution genetic maps by high-throughput...

Publications

Sapkota, S., Martinez, D., Underhill, A., Chen, L. L., Gadoury, D., Cadle-Davidson, L., & Hwang, C. F. (2025). A Device for Computer Vision Analysis of Fungal Features Outperforms Quantitative Manual Microscopy by Experts in Discerning a Host Resistance Locus. Phytopathology.

Gambhir, N., Paul, A., Qiu, T., Combs, D. B., Hosseinzadeh, S., Underhill, A., … & Gold, K. M. (2024). Non-destructive monitoring of foliar fungicide efficacy with hyperspectral sensing in grapevine. Phytopathology114(2), 464-473.

Reisch, B. I., Cadle-Davidson, L., Ikeogu, U., Sacks, G. L., Londo, J. P., & Martinson, T. E. (2023). Contributions of the VitisGen2 project to grapevine breeding and genetics. Vitis62.

Bierman, A., LaPlumm, T., Cadle-Davidson, L., Gadoury, D., Martinez, D., Sapkota, S., & Rea, M. (2019). A high-throughput phenotyping system using machine vision to quantify severity of grapevine powdery mildew. Plant Phenomics.

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