Comparing the handheld Stenon FarmLab soil sensor with a Vis-NIR multi-sensor soil sensing platform

Understanding within-field variability is essential for optimizing crop yields, enhancing resource efficiency, and reducing environmental impacts in agriculture. Precision soil maps are crucial tools for achieving these goals. This study assessed the accuracy and practicality of the Stenon FarmLab, a handheld real-time soil sensor, by comparing its measurements to high-resolution soil maps generated using a Vis-NIR on-line multi-sensor platform. The experiment was conducted on a potato field in northeast Germany, with on-line sensing completed in August 2022 and Stenon sampling conducted monthly from November 2022 to September 2023. Calibration and validation of the Vis-NIR on-line multi-sensor data were performed using laboratory analyses and partial least squares regression. The R²-values varied across soil properties, ranging from 0.68 to 0.97 for calibration and 0.64 to 0.88 for validation, with mean R²-values of 0.81 and 0.72, respectively. Based on this, high-resolution soil property and nutrient maps were generated using ordinary kriging, effectively capturing spatial heterogeneity. The Stenon FarmLab showed significant variability in measurement accuracy and consistency. Temporal trends in mineralized nitrogen (N_min), soil organic carbon (SOC), and pH were deemed implausible, as they could not be explained by natural soil processes or management practices. Correlation analyses between the two systems for stable soil properties resulted in R²-values of 0.29 for SOC, 0.41 for pH, and 0.50 for soil texture. While the Stenon FarmLab provides a rapid and convenient method for in-field soil analysis, this study revealed significant limitations in the accuracy of its measurements for most soil parameters.