Does Drone Data Allow the Assessment of Phosphorus and Potassium in Soil Based on Field Experiments with Winter Rye?

Abstract

The evaluation of the nutrient content in the soil, such as potassium and phosphorus, is very important, especially in precision agriculture, where the fertilizer rate should be adjusted to field variability in terms of nutrient content. Soil chemical analysis is time-consuming and expensive, and dense soil sampling is not always possible. In recent years, remote sensing methods have been used to assess the within-field variability of soil and crop nutritional status. The main aim of this study was to evaluate the relationship between UAV-derived spectral reflectance for winter rye in a long-term experiment for different fertilization with phosphorus and potassium. The study was conducted in 2022 in two field experiments in which winter rye was cultivated in monoculture and with crop rotation. The experiments were located in central Poland in Skierniewice. Statistical analyses were performed using univariate and multivariate methods, e.g., analysis of correlation, regression, and principal component analysis (PCA). The effect of phosphorus and potassium fertilization on the UAV-derived spectral reflectance of winter rye was weak, weaker in comparison to the effect of nitrogen fertilization. The effect of phosphorus and potassium fertilization on spectral reflectance was stronger in the experiment with monoculture than in the experiment with crop rotation. On the basis of correlation coefficients and PCA, negative relationships were proven between available soil potassium and spectral reflectance in the range of blue, green, and red bands and positive with red edge and near-infrared bands. The first principal component (PC1) was very strongly correlated with almost all spectral bands, either positively or negatively. The correlation of potassium and phosphorus content was very weak with PC1 in the experiment with crop rotation, while in the experiment with rye monoculture, the correlation was slightly stronger, indicating a stronger effect of nutrient deficiency in monoculture.

Keywords

• unmanned aerial vehicle—UAV
• nutrient deficiency
• fertilization
• multivariate analysis