Estimating apple leaf SPAD under the flowering stage frost stress using hyperspectral vegetation indices

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Spring frost during the flowering period poses a significant threat to the sustainable development of the apple industry, creating an urgent need for efficient and nondestructive monitoring techniques for frost stress. The soil plant analysis development (SPAD) value, serving as a reliable indicator of chlorophyll content, can directly reflect physiological damage induced by frost. However, a hyperspectral monitoring method specifically for assessing leaf SPAD under frost stress during the apple flowering stage is currently lacking. In this study, apple cultivar ‘Changfu 2’ were subjected to controlled low-temperature treatments (0 °C, −2 °C, and −4 °C for durations of 2, 4, and 6 hours) to obtain leaf hyperspectral reflectance and corresponding SPAD values under varying frost stress conditions. Based on the calibration dataset, all possible two-band normalized difference spectral index, ratio spectral index, and difference spectral index were systematically calculated to develop an optimal estimation model. The results showed that NDSI (R842, R799) demonstrated the best performance for estimating SPAD, with the validation model achieving a coefficient of determination of 0.73, a root mean square error of 3.13, and a residual prediction deviation of 1.05. Compared to a series of published vegetation indices, this newly proposed index NDSI (R842, R799) exhibited superior estimation accuracy can effectively monitor the dynamics of leaf SPAD in apple trees under flowering-stage frost stress.