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This review evaluates advances in RNA interference (RNAi) strategies, specifically spray-induced gene silencing (SIGS) and host-induced gene silencing (HIGS), to control Phytophthora infestans in potato. It highlights the use of nanocarriers to improve the stability, delivery, and uptake of double-stranded RNA at the potato–oomycete interface. The authors discuss system-level optimization and regulatory considerations necessary for translating RNAi-based nanobiopesticides into sustainable late blight management.
This study demonstrates the use of UAV-based multispectral imaging combined with machine learning to accurately predict late blight severity across over 3,200 potato breeding clones and genebank accessions. A framework integrating K-means clustering and Kernel Ridge Regression outperformed standard vegetation index models in tracking disease progression. The approach provides a scalable, high-throughput phenotyping tool to replace labor-intensive visual assessments in potato resistance breeding programs.
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If you find this platform helpful for your research, please cite:
An AI-powered Knowledge Hub for Potato Functional Genomics, Plant Commun., 10.1016/j.xplc.2026.101730