A qPCR-Machine Learning Framework for Quantifying Species Composition in Mixed Light-Trap Samples of Nilaparvata Planthoppers
State Key Laboratory of Rice Biology and Breeding,
China National Rice Research Institute, Hangzhou 311401, China; College of Agriculture and Biotechnology,
Zhejiang University, Hangzhou 310058, China
Contact:
LIU Shuhua
Supported by:
This
study was
supported by the Zhejiang Provincial Natural Science Foundation of China (Grant Nos. ZCLZ126C1402
and
LGN21C140002), the Agricultural Science and Technology Innovation Program (Grant No. CAAS-CNRRI-2025-02), and the
Central Public-interest Scientific Institution Basal Research Fund (CNRRI) (Grant No. CNRRI NO.5).
YANG Guiying, WANG Cilin, LUO Ju, TANG Jian, LIU Shuhua. A qPCR-Machine Learning Framework for Quantifying Species Composition in Mixed Light-Trap Samples of Nilaparvata Planthoppers[J]. Rice Science.
