Five decades of hand‐feel soil texture estimation: Accuracy, challenges, and improvements

Abstract Soil texture refers to the proportion of fine soil particles with diameters less than 2 mm, classified into particle size categories that define the soil texture class. Hand‐feel estimation in the field is widely used by soil scientists and technicians during pedological surveys to characterize soil horizons. This study evaluates the accuracy of such field estimations in Italy, considering variables such as surveyor experience, soil taxonomy order, soil moisture, and organic carbon content. Data were compared with international studies to contextualize the findings. To enhance estimation accuracy, a calibration method was developed, integrating reference parameters such as ribbon length and strength, sieving samples of known particle size, and sand‐counting grids. The approach employs a regression model linking these field parameters to laboratory‐measured particle size fractions. The method was first tested with university students and then applied to 105 heterogeneous samples to build a calibration dataset, used to estimate the particle size fractions of new samples. Historical data indicate that soil texture estimates based on traditional hand‐feel flowcharts are often inaccurate, regardless of the surveyor's experience. In contrast, the proposed method improved student estimation accuracy by 20% compared with the conventional approach. Using the calibration dataset, the method achieved an average score of 90/100 compared to 85 for the traditional approach, demonstrating superior accuracy and greater precision, with results consistently closer to the true value and less sensitive to external factors. Moreover, it enables the quantitative estimation of clay and sand fractions, rather than relying solely on categorical texture classes.