The determination of plant nutrient content is crucial for evaluating crop nutrient removal, enhancing nutrient use efficiency, and optimizing yields. Nutrient conventional monitoring involves colorimetric analyses in the laboratory; however, this approach is labor-intensive, costly, and time-consuming. The visible and near-infrared spectroscopy (VNIR) or hyperspectral non-imaging sensors have been an emerging technology that has been proved its potential for rapid detection of plant nutrient deficiency and nutrient status monitoring. However, most researches in this respect have focused primarily on nitrogen and few studies were conducted to understand the specificity of measuring phosphorus using this technique. In this study, we investigated the potential of leaf spectral reflectance in the visible and near-infrared spectral region to predict phosphorus status in winter wheat leaves. The research was conducted in a long-term experiment, which was installed in 1896 at the Gembloux Agro-Bio Tech faculty. The trial includes various fertilization modalities ensuring phosphorus contrast and variability in data acquired. The spectra acquisition and leaves biomass sampling were done synchronously at different stages of the wheat growth cycle. The reflectance measurements were done on the youngest fully expanded leaf using the ASD FieldSpec4 Spectroradiometer. All spectra were recorded between 350 nm and 2 500 nm and output at a 1 nm interval. The collected data were divided into training and validation sets. Results from partial least squares regression (PLSR) with cross-validation (CV) and 3 components were: the root mean square error and the determination coefficient of cross-validation (RMSECV and R2) were respectively 0.99 mg/g and 0.70. The obtained model predicted leaf phosphorus status of the validation dataset with RMSE of prediction (RMSEP) and R2 of prediction of 1.07 mg/g and 0.66, respectively, and the ratio of standard deviation to RMSEP (RPD) were 1.73. The validation results showed that the generated PLS predictive model has some potential to detect phosphorus status in wheat fresh leaves and that using Vis-NIR spectroscopy is a practical option to measure leaf phosphorus concentrations.
