Predicting plant-related and leaf-related parameters of winter wheat using vegetation index: Should phenological correction be applied across growth stages?

Most existing plant-related and leaf-related parameters models of winter wheat vary across growing seasons, but it is an open question whether a unified statistical model can be developed to predict plant-related and leaf-related parameters using VI across multiple growing seasons, or whether the phenological correction is necessary for each parameter across multiple growing seasons. To explore this question, we measured two plant-related parameters and four leaf-related parameters over five growth stages during the 2017–2021 growing seasons. A hierarchical linear model (HLM) automatically adapts the relationship between VIs and their corresponding parameter across growing seasons and assesses the contribution of phenological variables by applying a sensitivity analysis. The estimates of VI–plant-related parameters [aboveground dry biomass (AGB) and plant nitrogen concentration (PNC)] were scattered over a given growing season, unlike the relationship between VI–leaf-related parameters [leaf dry biomass (LGB), leaf nitrogen concentration (LNC), leaf area index (LAI) and soil and plant analysis development (SPAD)]. In contrast, the AGB, PNC, LGB, LNC, LAI, and SPAD HLM models are stable and can be popularized across growing seasons, with the determination coefficient R 2 ranging from 0.84 to 0.86, 0.79 to 0.87, 0.70 to 0.71, 0.68 to 0.86, 0.75 to 0.81, and 0.68 to 0.70, respectively, and the root mean square error ranging from 0.13 to 0.50 t/ha, 0.01 to 0.07%, 0.01 to 0.03 t/ha, 0.02 to 0.03%, 0.02 to 0.07, and 0.47 to 0.69, respectively. The sensitivity index of the phenological information in the AGB and PNC models was 0.56–0.78 and 0.66–0.72, respectively, whereas that in the LGB, LNC, LAI, and SPAD models was 0.01–0.06, 0.01–0.10, 0.02–0.06, and 0.00–0.01, respectively. Although phenological effects have little effect on leaf-related indicators, HLM has a strong potential for application to other crops and regions.