Digital soil science and beyond

Abstract

Digital convergence is helping us to better understand and study the soil. Fixed and mobile sensors, and wireless communication systems aided by the internet produce cheap and abundant streams of digital soil data that can readily be used for modeling and information generation. Here, we explore the ways in which digital science and technology have affected soil science. We can call this digital soil science and define it as the study of the soil aided by the tools of the digital convergence. To some degree, all of our research and teaching had been enabled, enhanced, and expanded by the digital convergence. We outline how soil science has changed using illustrations of intellectual and technical developments enabled digitally. Digital soil sensors have been widely implemented, and new tools such as cell phones and applications, or metagenomics techniques are becoming available. There are also areas in soil science for which no major obstacles in the digital technologies exist, but which have not been thoroughly investigated-for example, to devise a truly digital soil field description or for building a formal digital quantitative system of soil classification. The soil science community will need to be alert to some of the dangers brought by digital convergence such as the lack of new theory and proprietary (black-box) soil prediction. Finally, we discuss a whole set of digital tools that will, or might, gain the stage in the immediate future and take a stab in the dark on what may lie over the horizon of digital soil science.

Spatial variability and uncertainty of soil nitrogen across the conterminous United States at different depths

“…Upscaling in situ soil measurements is a research area of ongoing development (Wadoux & McBratney, 2021). Traditionally, it has been done using polygon-based approaches where equal values are given to defined categories, such as soil types (Cheng et al, 2019), or by parameterizing process-based models to predict soil N across space and time (Grunwald, 2009).…”

Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm

“…The advancement of knowledge and technology (e.g., wireless sensors, IoT, AI) in digital agriculture could lead to digital twin paradigms of soil in agriculture. The recent development of digital soil mapping techniques may support digital twins by digital representation of knowledge obtained from the soil in virtual entrainment [53]. For instance, digital soil mapping could be used to describe soil variation in digital twins using information from complex soil variation at a specific depth, time, and special locations [52].…”

“…However, few studies focus on the development of digital twin concepts of agriculture soil with higher degree of flexibility as well as considering a wider range of operation than existing simulation models. Soil sensors could constantly measure and record the dynamic condition of arable soil, e.g., water holding capacity, moisture, temperature [53]. These data, along with information from soil structure and simulation techniques, can be transferred to digital twin concepts, and constant feedback from the digital world may advise real-time responses for soil and water management as well as control systems.…”

A more vital soil science future

“…Countless technological advances enable us to observe, measure, model, and monitor soil attributes at accelerating speed (Wadoux & McBratney, 2021). The private sector and industry have entered the soil carbon market, discovered the commercial value of the soil microbiome, and continue to develop technologies to optimize soil water use.…”