Gamma‐ray spectrometry is an established method in geo‐sciences. This article gives an overview on fundamentals of gamma‐ray spectrometry that are relevant to soil science including basic technical aspects, and discusses influencing factors, inconsistencies, limitations, and open questions related to the method. Gamma‐ray spectrometry relies on counting gamma quanta during radionuclide decay of 40K, 238U, and 232Th, but secular equilibrium for the decay series of U and Th must be given as decays of their respective daughter radionuclides are used for determination. Secular equilibrium for U and Th decay series, however, is not always given leading to, e.g., anomalies in U concentration measurements. For soil science, gamma‐ray spectrometry is of specific value since it does not only detect a signal from the landscape surface, but integrates information over a certain volume. Besides, different spatial scales can be covered using either ground‐based or airborne sensing techniques. Together with other remote sensing methods, gamma signatures can provide completive information for understanding land forming processes and soil properties distributions. At first, signals depend on bedrock composition. The signals are in second order altered by weathering processes leading to more interpretation opportunities and challenges. Due to their physico‐chemical properties, radionuclides behave differently in soils and their properties can be distinguished via the resulting signatures. Hence, gamma signatures of soils are specific for local environments. Processes like soil erosion can superimpose gamma signals from in situ weathering. Soil mappings, available K and texture determination, or peat and soil erosion mapping are possible applications being discussed in this review.

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This article deals with technology transfer from science to agriculture with pearl millet (Pennisetum glaucum (L.)R.Br.) in central Tanzania as example. The major question is which validity recommendations from different types of field experiments have and how geo-information (i.e. soil and landscape position) can lead to more site-specific recommendations. Tied ridging and reduced amounts of placed fertilizer during sowing were tested to increase yields on researcher-managed plots on-station, demonstration plots in villages, and farmer-managed plots on-farm. While on-station trials provided potential yield effects, physical distance to the station and differing conditions led to a higher informational value of village plots that mirror the context of local farmers. The treatments often resulted in significant yield increase. Soil and relief information and distance to settlements (i.e. gradient of management intensity) are key factors for data variability in on-farm trials. Unexplained variability is introduced through leaving degrees of freedom with respect to management to the farmer. Apart from soil and physiographic information, the latter should be part of a detailed data collection procedure in agronomic trials in large numbers addressing Sub-Saharan smallholder farming. Balanced data sets with dispersed trials on crucial soil and relief units are essential for future research.