Articles | Volume 10, issue 1
https://doi.org/10.5194/soil-10-321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-10-321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The effect of soil moisture content and soil texture on fast in situ pH measurements with two types of robust ion-selective electrodes
Department of Agromechatronics, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, 14469 Potsdam, Germany
Katja Emmerich
Department of Agromechatronics, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, 14469 Potsdam, Germany
Ingmar Schröter
Eberswalde University for Sustainable Development, Landscape Management and Nature Conservation, Schicklerstraße 5, 16225 Eberswalde, Germany
Eric Bönecke
Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Theodor-Echtermeyer-Weg 1, 14979 Grossbeeren, Germany
Wolfgang Schwanghart
Institute of Environmental Sciences and Geography, University of Potsdam, 14476 Potsdam, Germany
Jörg Rühlmann
Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Theodor-Echtermeyer-Weg 1, 14979 Grossbeeren, Germany
Eckart Kramer
Eberswalde University for Sustainable Development, Landscape Management and Nature Conservation, Schicklerstraße 5, 16225 Eberswalde, Germany
Robin Gebbers
Department of Agromechatronics, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, 14469 Potsdam, Germany
Chair of Agricultural Business Operations, Martin-Luther University Halle-Wittenberg, Karl-Freiherr-von-Fritsch-Strasse 4, 06120 Halle, Germany
Related authors
No articles found.
Wolfgang Schwanghart, Ankit Agarwal, Kristen Cook, Ugur Ozturk, Roopam Shukla, and Sven Fuchs
Nat. Hazards Earth Syst. Sci., 24, 3291–3297, https://doi.org/10.5194/nhess-24-3291-2024, https://doi.org/10.5194/nhess-24-3291-2024, 2024
Short summary
Short summary
The Himalayan landscape is particularly susceptible to extreme events, which interfere with increasing populations and the expansion of settlements and infrastructure. This preface introduces and summarizes the nine papers that are part of the special issue,
Estimating and predicting natural hazards and vulnerabilities in the Himalayan region.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
Short summary
Short summary
The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Boris Gailleton, Philippe Steer, Philippe Davy, Wolfgang Schwanghart, and Thomas Guillaume Adrien Bernard
EGUsphere, https://doi.org/10.5194/egusphere-2024-1239, https://doi.org/10.5194/egusphere-2024-1239, 2024
Short summary
Short summary
We use cutting-edge algorithms and conceptual simplifications to solve the equations describing water flow at the surface of the earth. From quantitative information about rain and elevation, GraphFlood allow the calculation of river width, depth and allow the approximation of erosive power making it a suitable tool for large-scale hazard management or to comprehend the link between rivers and mountains.
Anna-Maartje de Boer, Wolfgang Schwanghart, Jürgen Mey, Basanta Raj Adhikari, and Tony Reimann
Geochronology, 6, 53–70, https://doi.org/10.5194/gchron-6-53-2024, https://doi.org/10.5194/gchron-6-53-2024, 2024
Short summary
Short summary
This study tested the application of single-grain feldspar luminescence for dating and reconstructing sediment dynamics of an extreme mass movement event in the Himalayan mountain range. Our analysis revealed that feldspar signals can be used to estimate the age range of the deposits if the youngest subpopulation from a sample is retrieved. The absence of clear spatial relationships with our bleaching proxies suggests that sediments were transported under extremely limited light exposure.
Jürgen Mey, Wolfgang Schwanghart, Anna-Maartje de Boer, and Tony Reimann
Geochronology, 5, 377–389, https://doi.org/10.5194/gchron-5-377-2023, https://doi.org/10.5194/gchron-5-377-2023, 2023
Short summary
Short summary
This study presents the results of an outdoor flume experiment to evaluate the effect of turbidity on the bleaching of fluvially transported sediment. Our main conclusions are that even small amounts of sediment lead to a substantial change in the intensity and frequency distribution of light within the suspension and that flow turbulence is an important prerequisite for bleaching grains during transport.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
Short summary
Short summary
Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-295, https://doi.org/10.5194/nhess-2022-295, 2023
Manuscript not accepted for further review
Short summary
Short summary
The current socioeconomic development in the Himalayan region leads to a rapid expansion of the road network and an increase in the exposure to landslides. Our study along the NH-7 demonstrates the scale of this challenge as we detect more than one partially or fully road-blocking landslide per road kilometer. We identify the main controlling variables, i.e. slope angle, rainfall amount and lithology. As our approach uses a minimum of data, it can be extended to more complicated road networks.
Benjamin Campforts, Veerle Vanacker, Frédéric Herman, Matthias Vanmaercke, Wolfgang Schwanghart, Gustavo E. Tenorio, Patrick Willems, and Gerard Govers
Earth Surf. Dynam., 8, 447–470, https://doi.org/10.5194/esurf-8-447-2020, https://doi.org/10.5194/esurf-8-447-2020, 2020
Short summary
Short summary
In this contribution, we explore the spatial determinants of bedrock river incision in the tropical Andes. The model results illustrate the problem of confounding between climatic and lithological variables, such as rock strength. Incorporating rock strength explicitly into river incision models strongly improves the explanatory power of all tested models and enables us to clarify the role of rainfall variability in controlling river incision rates.
Dirk Scherler and Wolfgang Schwanghart
Earth Surf. Dynam., 8, 245–259, https://doi.org/10.5194/esurf-8-245-2020, https://doi.org/10.5194/esurf-8-245-2020, 2020
Short summary
Short summary
Drainage divides are believed to provide clues about divide migration and the instability of landscapes. Here, we present a novel approach to extract drainage divides from digital elevation models and to order them in a drainage divide network. We present our approach by studying natural and artificial landscapes generated with a landscape evolution model and disturbed to induce divide migration.
Dirk Scherler and Wolfgang Schwanghart
Earth Surf. Dynam., 8, 261–274, https://doi.org/10.5194/esurf-8-261-2020, https://doi.org/10.5194/esurf-8-261-2020, 2020
Short summary
Short summary
Drainage divides are believed to provide clues about divide migration and the instability of landscapes. Here, we present a novel approach to extract drainage divides from digital elevation models and to order them in a drainage divide network. We present our approach by studying natural and artificial landscapes generated with a landscape evolution model and disturbed to induce divide migration.
Christopher J. Skinner, Tom J. Coulthard, Wolfgang Schwanghart, Marco J. Van De Wiel, and Greg Hancock
Geosci. Model Dev., 11, 4873–4888, https://doi.org/10.5194/gmd-11-4873-2018, https://doi.org/10.5194/gmd-11-4873-2018, 2018
Short summary
Short summary
Landscape evolution models are computer models used to understand how the Earth’s surface changes over time. Although designed to look at broad changes over very long time periods, they could potentially be used to predict smaller changes over shorter periods. However, to do this we need to better understand how the models respond to changes in their set-up – i.e. their behaviour. This work presents a method which can be applied to these models in order to better understand their behaviour.
Wolfgang Schwanghart and Dirk Scherler
Earth Surf. Dynam., 5, 821–839, https://doi.org/10.5194/esurf-5-821-2017, https://doi.org/10.5194/esurf-5-821-2017, 2017
Short summary
Short summary
River profiles derived from digital elevation models are affected by errors. Here we present two new algorithms – quantile carving and the CRS algorithm – to hydrologically correct river profiles. Both algorithms preserve the downstream decreasing shape of river profiles, while CRS additionally smooths profiles to avoid artificial steps. Our algorithms are able to cope with the problems of overestimation and asymmetric error distributions.
Benjamin Campforts, Wolfgang Schwanghart, and Gerard Govers
Earth Surf. Dynam., 5, 47–66, https://doi.org/10.5194/esurf-5-47-2017, https://doi.org/10.5194/esurf-5-47-2017, 2017
Short summary
Short summary
Despite a growing interest in landscape evolution models, accuracy assessment of the numerical methods they are based on has received little attention. We test a higher-order flux-limiting finite-volume method to simulate river incision and tectonic displacement. We show that this scheme significantly influences the evolution of simulated landscapes and the spatial and temporal variability of erosion rates. Moreover, it allows for the simulation of lateral tectonic displacement on a fixed grid.
N. K. Meyer, W. Schwanghart, O. Korup, and F. Nadim
Nat. Hazards Earth Syst. Sci., 15, 985–995, https://doi.org/10.5194/nhess-15-985-2015, https://doi.org/10.5194/nhess-15-985-2015, 2015
Short summary
Short summary
In the past decades the importance of and reliance on all kinds of transport networks has grown extensively making them more vulnerable to any kind of hazard. The linear structure of road networks is especially sensitive to debris flows, a process frequently occurring in the mountainous area of Norway. The paper quantifies the functional risk associated with these processes. The results reveal that the costs related to route closures are strongly related to the information status of drivers.
C. C. Clason, D. W. F. Mair, P. W. Nienow, I. D. Bartholomew, A. Sole, S. Palmer, and W. Schwanghart
The Cryosphere, 9, 123–138, https://doi.org/10.5194/tc-9-123-2015, https://doi.org/10.5194/tc-9-123-2015, 2015
W. Schwanghart and D. Scherler
Earth Surf. Dynam., 2, 1–7, https://doi.org/10.5194/esurf-2-1-2014, https://doi.org/10.5194/esurf-2-1-2014, 2014
Related subject area
Soil sensing
Best performances of visible–near-infrared models in soils with little carbonate – a field study in Switzerland
Delineating the distribution of mineral and peat soils at the landscape scale in northern boreal regions
Improving models to predict holocellulose and Klason lignin contents for peat soil organic matter with mid-infrared spectra
Simon Oberholzer, Laura Summerauer, Markus Steffens, and Chinwe Ifejika Speranza
SOIL, 10, 231–249, https://doi.org/10.5194/soil-10-231-2024, https://doi.org/10.5194/soil-10-231-2024, 2024
Short summary
Short summary
This study investigated the performance of visual and near-infrared spectroscopy in six fields in Switzerland. Spectral models showed a good performance for soil properties related to organic matter at the field scale. However, spectral models performed best in fields with low mean carbonate content because high carbonate content masks spectral features for organic carbon. These findings help facilitate the establishment and implementation of new local soil spectroscopy projects.
Anneli M. Ågren, Eliza Maher Hasselquist, Johan Stendahl, Mats B. Nilsson, and Siddhartho S. Paul
SOIL, 8, 733–749, https://doi.org/10.5194/soil-8-733-2022, https://doi.org/10.5194/soil-8-733-2022, 2022
Short summary
Short summary
Historically, many peatlands in the boreal region have been drained for timber production. Given the prospects of a drier future due to climate change, wetland restorations are now increasing. Better maps hold the key to insights into restoration targets and land-use management policies, and maps are often the number one decision-support tool. We use an AI-developed soil moisture map based on laser scanning data to illustrate how the mapping of peatlands can be improved across an entire nation.
Henning Teickner and Klaus-Holger Knorr
SOIL, 8, 699–715, https://doi.org/10.5194/soil-8-699-2022, https://doi.org/10.5194/soil-8-699-2022, 2022
Short summary
Short summary
The chemical quality of biomass can be described with holocellulose (relatively easily decomposable by microorganisms) and Klason lignin (relatively recalcitrant) contents. Measuring both is laborious. In a recent study, models have been proposed which can predict both quicker from mid-infrared spectra. However, it has not been analyzed if these models make correct predictions for biomass in soils and how to improve them. We provide such a validation and a strategy for their improvement.
Cited articles
Adamchuk, V. I. and Lund, E. D.: On-The-Go Mapping of Soil pH Using Antimony Electrodes, Paper No. 083995, ASABE Annual International Meeting, 29 June–2 July 2008, Rhode Island (USA), https://elibrary.asabe.org/abstract.asp?aid=24748 (last access: 14 May 2024), 2008.
Adamchuk, V. I., Morgan M. T., and Ess, D. R.: An automated sampling system for measuring soil pH, T. ASAE, 42, 885–891, 1999.
Baghdady, N. H. and Sommer, K.: Application of an improved antimony micro-electrode for measuring pH-changes at the soil-root interface of maize, J. Plant Nutr. Soil Sci., 153, 323–326, 1990.
Barron, J. J., Ashton, C., and Geary, L.: The Effects of Temperature on pH Measurement, 57th Annual Meeting of the International Society of Electrochemistry, Edinburgh, UK, https://knowledge.reagecon.com/wp-content/uploads/2019/12/The-Effects-of-Temperature-on-PH-Measurement.pdf (last access: 14 May 2024), 2006.
Bates, R. G.: Electrodes for pH Measurement, J. Electroanal. Chem., 2, 93–109, 1961.
Bönecke, E., Meyer, S., Vogel, S., Schröter, I., Gebbers, R., Kling, C., Kramer, E., Lück, K., Nagel, A., Philipp, G., Gerlach, F., Palme, S., Scheibe, D., Zieger, K., and Rühlmann, J.: Guidelines for precise lime management based on high-resolution soil pH, texture and SOM maps generated from proximal soil sensing data, Precis. Agric., 22, 493–523, https://doi.org/10.1007/s11119-020-09766-8, 2020.
Brouder, S. M., Hofmann, B. S., and Morris, D. K.: Mapping soil pH: accuracy of common soil sampling strategies and estimation techniques, Soil Sci. Soc. Am. J., 69, 427–442, https://doi.org/10.2136/sssaj2005.0427, 2005.
Comer, J.: PH and Ion-Selective Electrodes, in: Instrumental Methods for Quality Assurance in Foods, edited by: Fung, D. Y. C. and Matthews, R. E., Routledge, New York, https://doi.org/10.1201/9780203750711, 1991.
Conkling, B. L. and Blanchar, R. W.: A comparison of pH measurements using the antimony microelectrode and glass electrode, Agron. J., 80, 275–278, 1988.
Davis, L. E.: Measurements of pH with the glass electrode as affected by soi moisture, Soil Sci., 56, 405–422, 1943.
Decker, M., Bause, S., Teichmann, P., Schneider, M., and Vonau, W.: Development of an automatic system for the on-site pH measurement of soil samples, Tech. Mess., 84, 659–671, 2017.
de Souza Silva, F. C. and Molin, J. P.: On-the-go tropical soil sensing for pH determination using ion-selective electrodes, Pesq. Agropec. Bras., 53, 1189–1202, https://doi.org/10.1590/S0100-204X2018001100001, 2018.
Donoghue, J. F.: Phi Scale, in: Encyclopedia of Estuaries, edited by: Encyclopedia of Earth Sciences Series, edited by: Kennish, M. J., Springer, Dordrecht, the Netherlands, https://doi.org/10.1007/978-94-017-8801-4_277, 2016.
Durst, R. A.: Sources of Error in Ion-Selective Electrode Potentiometry, in: Ion-Selective Electrodes in Analytical Chemistry, edited by: Freiser, H., Modern Analytical Chemistry book series, Springer New York, NY, 311–338, https://doi.org/10.1007/978-1-4684-2592-5, 1978.
Eckelmann, W., Sponagel, H., and Grottenthaler, W.: Bodenkundliche Kartieranleitung, 5th Edn., Schweizerbart Science Publishers, Stuttgart, Germany, ISBN 978-3-510-95920-4, 2005.
Epstein, E. and Bloom, A. J.: Mineral Nutrition of Plants: Principles and Perspectives, 2nd Edn., Sinauer Associates, Sunderland, MA, USA, ISBN 0878931724, 2001.
Essington, M. E.: Soil and water chemistry: An integrative approach, 2nd Edn., CRC Press, Boca Raton, FL, USA, https://doi.org/10.1201/b18385, 2015.
Fujimoto, M., Matsumura, Y., and Satake, N.: General Properties of Antimony Microelectrode in Comparison with Glass Microelectrode for pH Measurement, Jpn. J. Physiol., 30, 491–508, 1980.
Gebbers, R., Herbst, R., and Wenkel, K.-O.: Sensitivity analysis of soil nutrient mapping, Proceedings of the 7th Joint International Agricultural Conference, Wageningen, the Netherlands, edited by: Lokhorst, C., Huijsmans, J., and de Louw, R. P. M., Wageningen Academic Publishers, Wageningen, the Netherlands, 513–519, ISBN 978-90-8686-113-2, 2009.
Janetzko, P. and Schmidt, R.: Norddeutsche Jungmoränenlandschaften, in: Handbuch der Bodenkunde, edited by: Blume, H.-P., Stahr, K., Fischer, W., Guggenberger, G., Horn, R., Frede, H.-G., and Felix-Henningsen, P., Wiley-VCH, Weinheim, Germany, https://doi.org/10.1002/9783527678495.hbbk1995008, 2014.
Kahlert, H., Steinhardt, T., Behnert, J., and Scholz, F.: A New Calibration Free pH-Probe for In Situ Measurements of soil pH, Electroanalysis, 16, 2058–2064, 2004.
Keaton, C. M.: A theory explaining the relation of soil-water ratios to the pH values, Soil Sci., 46, 259–266, 1938.
Krbetschek, M. R., Degering, D., and Alexowsky, W.: Infrared radiofluorescence ages (IR-RF) of Lower Saalian sediments from Central and Eastern Germany, Zeitschr. Dtsch. Ges. Geowiss., 159, 133–140, 2008.
Krumbein, W. C.: Size frequency distributions of sediments, J. Sediment Petrol., 4, 65–77, 1934.
Krumbein, W. C.: Size frequency distributions of sediments and the normal phi curve, J. Sediment Petrol., 8, 84–90, 1938.
Matthiesen, H.: In situ measurement of soil pH, J. Archaeol. Sci., 31, 1373–1381, https://doi.org/10.1016/J.JAS.2004.03.005, 2004.
Mengel, K. and Kirkby, E. A.: Principles of Plant Nutrition, 5th Edn., Kluwer Academic Publishers, Dordrecht, the Netherlands, https://doi.org/10.1007/978-94-010-1009-2, 2001.
Merl, T., Rasmussen, M. R., Koch, L. R., Søndergaard, J. V., Bust, F. F., and Koren, K.: Measuring soil pH at in situ like conditions using optical pH sensors (pH-optodes), Soil Biol. Biochem., 175, 108862, https://doi.org/10.1016/j.soilbio.2022.108862, 2022.
Oliviera, I. S. D, Tavares, T. R., Trevisan, R. G., Bersani, V. H. S., and Molin, J. P.: Influence of soil moisture in pH Measurements using ion-selective electrodes, in: ConBAP 2018, Proceedings of the Congresso Brasileiro de Agricultura de Precisão, Curitiba, Paraná, Brazil, 66–73, 2018.
Orellana, G., Cano-Raya, C., López-Gejo, J., and Santos, A. R.: Online Monitoring Sensors, in: Treatise on Water Science, edited by: Wilderer, P., Elsevier, Amsterdam, the Netherlands, 221–261, https://doi.org/10.1016/B978-0-444-53199-5.00059-2, 2011.
Parks, L. R. and Beard, H. C.: The Theory of the Stick Antimony Electrode, J. Phys. Chem., 37, 821–822, 1933.
Patil, S., Ghadi, H., Ramgir, N., Adhikari, A., and Rao, V. R.: Monitoring soil pH variation using Polyaniline/SU-8 composite film based conductometric microsensor, Sens. Actuators B, 286, 583–590, 2019.
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 14 May 2024), 2018.
Robson, A. D.: Soil Acidity and Plant Growth, Academic Press, Sydney, NSW, Australia, https://doi.org/10.1016/B978-0-12-590655-5.X5001-4, 1989.
Ruehlmann, J., Bönecke, E., and Meyer, S.: Predicting the lime demand of arable soils from pH value, soil texture and soil organic matter content, Agronomy, 11, p. 785, https://doi.org/10.3390/agronomy11040785, 2021.
Satopää, V., Albrecht, J., Irwin, D., and Raghavan, B.: Finding a “Kneedle” in a Haystack: Detecting Knee Points in System Behavior, Proceedings of the 31st International Conference on Distributed Computing Systems Workshops, 20–24 June 2011, Minneapolis, MN, USA, IEEE, https://doi.org/10.1109/ICDCSW.2011.20, 2011.
Schaller, G. and Fischer, W.: Die Verwendung von Antimon-Elektroden zur pH-Messung in Böden, J. Plant Nutr. Soil Sci., 144, 197–204, 1981.
Schirrmann, M., Gebbers, R., Kramer, E., and Seidel, J.: Soil pH Mapping with an On-The-Go Sensor, Sensors, 11, 573–598, https://doi.org/10.3390/s110100573, 2011.
Shiozawa, S. and Campell, G. S.: On the caculation of mean particle diameter and standard deviation from sand, silt, and clay fractions, Soil Sci., 152, 427–431, 1991.
Shirazi, M. A., Boersma, L., and Hart, J. W.: A unifying quantitative analysis of soil texture: Improvement of precision and extension of scale, Soil Sci. Soc. Am. J., 52, 181–190, 1988.
Sumner, M. E.: Measurement of soil pH: Problems and solutions, Commun. Soil Sci. Plant Anal., 25, 859–879, 1994.
Thiele-Bruhn, S., Wessel-Bothe, S., and Aust, M.-O.: Time resolved in-situ pH measurement in differently treated, saturated and unsaturated soils, J. Plant Nutr. Soil Sci., 178, 425–432, 2015.
Thomas, G. W.: Soil pH and Soil Acidity, in: Methods of Soil Analysis, Part 3, Chemical Methods, edited by: Sparks, D., Page, A., Helmke, P., Loeppert, R., Soltanpour, P. N., Tabatabai, M. A., Johnston, C. T., and Sumner, M. E., Soil Sci. Soc. Am.-Madinson, WI, USA, 475–490, https://doi.org/10.2136/sssabookser5.3.c16, 1996.
Viscarra Rossel, R. A., Gilbertson, M., Thylén, L., McVey, S., and McBratney, A. B.: Field measurements of soil pH and lime requirement using an on-the-go soil pH and lime requirement measurement system. In Precision agriculture '05, Proceedings of the 5th European Conference on Precision Agriculture, Uppsala, Sweden, edited by: Stafford, J. V., Wageningen Academic Publishers, Wageningen, the Netherlands, 511–520, ISBN 978-90-76998-69-5, 2005.
Viscarra Rossel, R. A. and McBratney, A. B.: Preliminary experiments towards the evaluation of a suitable soil sensor for continuous, “on-the-go” field pH measurements, in: Precision agriculture '97, Vol. II, Technology, IT and management, Proceedings of the 1st European Conference on Precision Agriculture, Warwick, UK, 7–10 September, BIOS Scientific Publishers, Oxford, UK, 493–501, ISBN 978-18-59962-36-7, 1997.
Yuqing, M., Jianrong, C., and Keming, F.: New technologies for detection of pH, J. Biochem. Bioph. Meth., 63, 1–9, 2005.
Zong, S., Zhang, X., Chen, C., Lu, C., Ni, M., Mao, T., and Su, X.: Study on water content compensation method and experimental for soil pH detection sensor, Turk. J. Field Crops, 26, 52–58, 2021.
Short summary
To rapidly obtain high-resolution soil pH data, pH sensors can measure the pH value directly in the field under the current soil moisture (SM) conditions. The influence of SM on pH and on its measurement quality was studied. An SM increase causes a maximum pH increase of 1.5 units. With increasing SM, the sensor pH value approached the standard pH value measured in the laboratory. Thus, at high soil moisture, calibration of the sensor pH values to the standard pH value is negligible.
To rapidly obtain high-resolution soil pH data, pH sensors can measure the pH value directly in...