Inversion of SPAD Value in Yellowed Leaves of ‘Kuerle Xiangli’ (Pyrus sinkiangensis Yu) Using Multispectral Images from Drones

SPAD values serve as a key physiological indicator for assessing the health status of ‘Kuerle Xiangli’ leaves and for monitoring the occurrence of chlorosis. Rapid, non-destructive acquisition of their spatial distribution provides crucial support for precision orchard management and the scientific correction of leaf yellowing. This study selected six ‘Kuerle Xiangli’ experimental orchards in Tiemenguan City, Bayingolin Mongol Autonomous Prefecture, Xinjiang, as the research area. Using multi-spectral imagery from a DJI Mavic 3 drone and ground-measured SPAD values, four inversion models, RF, XGBoost, SVR, and PLSR, were constructed. Model inputs included vegetation indices (VIs), texture features, and a combination of both. By comparing the accuracy of the different models, the optimal SPAD inversion model for yellowing leaves of ‘Kuerle Xiangli’ was selected and validated in the field. Finally, a spatial distribution map of SPAD values was generated based on the optimal model. The results indicate the following: (1) Feature selection and the fusion of multi-source features significantly enhanced inversion performance. Compared to models using a single feature type, the Random Forest (RF) model that integrated 6 vegetation indices (CIRE, NDRE, LCI, REOSAVI, GNDVI, and NDWI) with 26 texture features performed best. It achieved an R2 = 0.9179, RMSE = 1.9970 and MAE = 1.2284 on the training set, and an R2 = 0.8161, RMSE = 3.4702, and MAE = 2.6799 on the validation set. The model also maintained good performance during field validation in an independent orchard (R2 = 0.7329, RMSE = 1.5823, MAE = 1.3377). (2) The spatial distribution map of SPAD values generated by the optimal model clearly delineates the SPAD ranges and yellowing status across the six orchards. The overall SPAD range across all orchards was 15.7 to 45.7. The order of yellowing severity was LLJ (80.5%) > YHC (68.1%) > LGQ (52.9%) > NKS (46.8%) > LCX (36.4%) > LGL (34.1%).