摘要
The nutritional status of rubber trees(Hevea brasiliensis)is inseparable from the production of natural rubber.Nitrogen(N)and potassium(K)levels in rubber leaves are 2 crucial criteria that reflect the nutritional status of the rubber tree.Advanced hyperspectral technology can evaluate N and K statuses in leaves rapidly.However,high bias and uncertain results will be generated when using a small size and imbalance dataset to train a spectral estimaion model.A typical solution of laborious long-term nutrient stress and high-intensive data collection deviates from rapid and flexible advantages of hyperspectral tech.Therefore,a less intensive and streamlined method,remining information from hyperspectral image data,was assessed.
基金
supported by the High-level Talent Project of Natural Science Foundation of Hainan Province(No.321RC468)
the Key R&D project of Hainan Province(ZDYF2022GXJS008)
the National Natural Science Foundation of China(No.32060413)
the Innovation Research Team Project of Natural Science Foundation of Hainan Province(No.320CXTD431).
