Evaluation of wheat drought resistance using hyperspectral and chlorophyll fluorescence imaging

Photosynthesis drives crop growth and production, and strongly affects grain yields; therefore, it is an ideal trait for wheat drought resistance breeding. However, studies of the negative effects of drought stress on wheat photosynthesis rates have lacked accurate evaluation methods, as well as high-throughput techniques. We investigated photosynthetic capacity under drought stress in wheat varieties with varying degrees of drought stress resistance using hyperspectral and chlorophyll fluorescence (ChlF) imaging data. We analyzed various morpho-physiological traits involved in wheat drought tolerance, including tiller number, leaf relative water content, and malondialdehyde content, to determine the relationships between drought resistance and hyperspectral and ChlF data. The results showed that the spectral first derivative ratio (FDR) between drought stress and control conditions in the 680-760 nm region was closely related to photosynthetic capacity and drought tolerance and that hyperspectral imaging can be used to monitor ChlF parameters, with bands sensitive to ChlF identified in two spectral regions (539-764 nm and 832-989 nm). The spectral first derivative at 989 nm had the strongest linear relationship with the minimal fluorescence (R² = 0.49). An uninformative variable elimination algorithm indicated that FDRs in the green (504-609 nm), red (724-751 nm), and near-infrared (944-946 nm) light regions had great potential as indices of drought resistance. A support vector machine model based on the FDRs of these characteristic bands identified wheat drought resistance with 97.33% accuracy. These findings provide insight into the application of high-throughput technologies in studying drought resistance and photosynthesis in wheat.