Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming

Phosphorus (P) fertilisation recommendations rely primarily on soil content of plant available P (P-avl) that vary spatially within farm fields. Spatially optimized P fertilisation for precision farming requires reliable, rapid and non-invasive P-avl determination. This laboratory study aimed to test and to compare visible-near infrared (Vis-NIR) and mid-infrared (MIR) spectroscopy for P-avl prediction with emphasis on future application in precision agriculture. After calibration with the conventional calcium acetate lactate (CAL) extraction method, limitations of Vis-NIRS and MIRS to predict P-avl were evaluated in loess topsoil samples from different fields at six localities. Overall calibration with 477 (Vis-NIRS) and 586 (MIRS) samples yielded satisfactory model performance (R-2 0.70 and 0.72; RPD 1.8 and 1.9, respectively). Local Vis-NIRS models yielded better results with R-2 up to 0.93 and RPD up to 3.8. For MIRS, results were comparable. However, an overall model to predict P-avl on independent test data partly failed. Sampling date, pre-crop harvest residues and fertilising regime affected model transferability. Varying transferability could partly be explained after deriving the cellulose absorption index from the Vis-NIR spectra. In 62 (Vis-NIRS) and 67% (MIRS) of all samples, prediction matched the correct P-avl content class. Rapid discrimination between high, optimal and low P classes could be carried out on many samples from single fields thus marking an improvement over the common practice. However, P-avl determination by means of IR spectroscopy is not yet satisfactory for determination of precision fertilizer dosage. For introduction into agricultural practice, a standardized sampling protocol is recommended to help achieve reliable spectroscopic P-avl prediction.