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      The potential for using smartphones as portable soil nutrient analyzers on suburban farms in central East China

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          Abstract

          Soil testing is frequently conducted to specify nutrient supply recommendations. By adjusting fertilizer type and application rates, farmers can achieve desired crop yields with lower production costs and are thereby less likely to contribute to eutrophication of nearby waterbodies. However, traditional methods of soil testing can be costly, time-consuming and are often impractical in rural and resource-poor regions in China, where rapid population growth and consequent food demand must be balanced against potential environment risks. Smartphones are nearly ubiquitous and offer a ready capability for providing additional support for existing extension advice. In this study, we used an Android-based smartphone application, in conjunction with commercially-available Quantofix test strips, to analyze soil samples with a goal of providing specific fertilizer recommendations. The app transforms the smartphone into a portable reflectometer, relating the reaction color of the test strips to the concentration of soil nutrients available. A 6-month long field study involving two growing seasons of vegetables was conducted in a suburban area of Nanjing, Jiangsu Province of China to evaluate the accuracy and precision of smartphone-mediated soil analysis. Results obtained via the smartphone correlated well with the yield response of the common green vegetable Ipomoea aquatica (water spinach) and could be applied in calculations of necessary off-farm inputs throughout the open-field vegetable growing season. Together, the smartphone and test strip in combination were shown to offer an acceptable screening tool for soil nutrient concentration assessment with the potential to result in substantial monetary savings and reduction of nutrient loss to the environment.

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          Most cited references21

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          Fertiliser availability in a resource-limited world: Production and recycling of nitrogen and phosphorus

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            A Review of Methods for Sensing the Nitrogen Status in Plants: Advantages, Disadvantages and Recent Advances

            Nitrogen (N) plays a key role in the plant life cycle. It is the main plant mineral nutrient needed for chlorophyll production and other plant cell components (proteins, nucleic acids, amino acids). Crop yield is affected by plant N status. Thus, the optimization of nitrogen fertilization has become the object of intense research due to its environmental and economic impact. This article focuses on reviewing current methods and techniques used to determine plant N status. Kjeldahl digestion and Dumas combustion have been used as reference methods for N determination in plants, but they are destructive and time consuming. By using spectroradiometers, reflectometers, imagery from satellite sensors and digital cameras, optical properties have been measured to estimate N in plants, such as crop canopy reflectance, leaf transmittance, chlorophyll and polyphenol fluorescence. High correlation has been found between optical parameters and plant N status, and those techniques are not destructive. However, some drawbacks include chlorophyll saturation, atmospheric and soil interference, and the high cost of instruments. Electrical properties of plant tissue have been used to estimate quality in fruits, and water content in plants, as well as nutrient deficiency, which suggests that they have potential for use in plant N determination.
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              Applying the right statistics: analyses of measurement studies.

              The study of measurement error, observer variation and agreement between different methods of measurement are frequent topics in the imaging literature. We describe the problems of some applications of correlation and regression methods to these studies, using recent examples from this literature. We use a simulated example to show how these problems and misinterpretations arise. We describe the 95% limits of agreement approach and a similar, appropriate, regression technique. We discuss the difference vs. mean plot, and the pitfalls of plotting difference against one variable only. We stress that these are questions of estimation, not significance tests, and show how confidence intervals can be found for these estimates. Copyright 2003 ISUOG. Published by John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                r.sakrabani@cranfield.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 November 2019
                11 November 2019
                2019
                : 9
                : 16424
                Affiliations
                [1 ]ISNI 0000 0001 0679 2190, GRID grid.12026.37, School of Water, Energy and Environment, , Cranfield University, Cranfield, ; Bedfordshire, MK43 0AL UK
                [2 ]ISNI 0000 0000 9750 7019, GRID grid.27871.3b, Department of Soil Science and Institute of Resource, , Ecosystem and Environment of Agriculture, Nanjing Agricultural University, ; 1 Weigang, Nanjing, 210095 China
                Author information
                http://orcid.org/0000-0002-8776-7049
                Article
                52702
                10.1038/s41598-019-52702-8
                6848085
                31712568
                d31ba1cd-3445-4e49-af07-8c131d32baeb
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 July 2019
                : 22 October 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000308, British Council;
                Award ID: 352636353
                Award ID: 352636353
                Award ID: 352636353
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000270, RCUK | Natural Environment Research Council (NERC);
                Award ID: NE/M009009/1
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                element cycles,environmental monitoring
                Uncategorized
                element cycles, environmental monitoring

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