Rapid assessment of soil nutrients under continuous Gastrodia elata cropping using near- and mid-infrared...

To enable rapid and non-destructive quantitative assessment of soil nutrients in Gastrodia elata continuous-cropping fields, soils with different cultivation histories were collected from a G. elata experimental site in Bijie, Guizhou, China, including never planted (WZZ), continuous cropping for one year (LZ1), continuous cropping for two years (LZ2), and G. elata-konjac rotation (TMLuZ). Reference concentrations of soil organic matter (SOM), total nitrogen (TN), alkali-hydrolyzable nitrogen (HN), total phosphorus (TP), available phosphorus (AP), total potassium (TK), and available potassium (AK) were determined, and near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectra were acquired. Spectral preprocessing was performed, followed by variable selection using uninformative variable elimination (UVE) and competitive adaptive reweighted sampling (CARS). Partial least squares regression (PLSR) and random forest (RF) models were developed for single-modality spectra, and three fusion schemes-data-level, feature-level, and decision-level-were further designed. Model performance was evaluated on an independent validation set using R_V², RMSE_V, and RPIQ_V, with RPIQ_V=1.4 as the usability threshold. The results demonstrated substantial differences in predictability among nutrient indicators. SOM, TN, and TK achieved stable performance on the independent validation set. The best SOM model was obtained from the NIR single-modality approach (PLSR, R_V²=0.939, RPIQ_V=4.87), while data-level fusion yielded comparable accuracy (PLSR, R_V²=0.936, RPIQ_V=4.75). The best results for TN and TK were both achieved using the ATR-MIR single-modality strategy (TN: RF, R_V²=0.866, RPIQ_V=4.10; TK: PLSR, R_V²=0.849, RPIQ_V=4.08). HN and AK reached a moderate prediction level (HN: RPIQ_V=2.42; AK: RPIQ_V=2.33). In contrast, TP and AP did not meet the usability threshold under any strategy (best RPIQ_V for TP = 1.16; for AP = 0.81). Overall, single-modality NIR and ATR-MIR models can provide a rapid quantitative screening route for SOM, TN, and TK in continuous-cropping fields, whereas the benefits of fusion were indicator-dependent. Phosphorus-related indicators still require further optimization.