PEF-MODFLOW: A framework for preliminary soil profile horizon delineation based on soil color captured by smartphone images

Yang, Jiawei; Shen, Feilong; Wang, Tianwei; Wu, Lingyun; Li, Zhaoxia; Li, Nian; Dai, Lilong; Liang, Jinghui; Zhang, Jian

doi:10.1016/j.envsoft.2022.105423

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…Additionally, it is possible to directly distinguish the presence and semi-quantitative detection of the analyte by the naked eye [ 39 ] A smart sensor with cellulose-based material was developed for the detection of 2,4,6-trinitrotoluene, using potassium hydroxide/ethanol reagent adsorbed onto a cellulose cotton swab. A red colour was observed immediately after exposure to the analyte A simple and cheap method for 2,4,6-trinitrotoluene determination [ 45 ] As (III) Application of field test kits and smartphone-based optical sensing Easy procedure for As determination [ 46 ] Optical colorimetric and smartphone-integrated paper device for As (III) determination using sucrose modified gold nanoparticles as a nanoprobe Smartphone-integrated paper based device is rapid and portable for monitoring of arsenic at the sample source [ 47 ] Colorimetric detection protocol utilizing aptamers, gold nanoparticles, and NaCl coupled with smartphone detection With the android application on the device to run the experiment, the whole process from sample preparation to detection is completed within 3 h without the necessity of skilled personnel [ 48 ] Hg Strategy for highly sensitive, selective, and colorimetric detection of mercury based on analyte-induced enhancement of the photocatalytic activity of TiO 2 –Au nanospheres toward degradation of methylene blue A rapid, simple, sensitive, and specific detection approach was developed for quantitation of Hg 2+ or CH 3 Hg + [ 49 ] Fe Developed platform consisted of two cuvettes, a digital imaging device, and white paper as a diffuser Ease of accessibility, simplicity, sensitivity, and cost-effectiveness of our approach [ 50 ] Basic chemical and physical soil properties Soil colour Images taking by smartphone Soil colour captured by smartphone image for soil profile horizon delineation [ 51 ] Anew soil colour ...…”

Section: Soil Contamination Monitoringmentioning

confidence: 99%

Analytical applications of smartphones for agricultural soil analysis

Vakh

2023

Anal Bioanal Chem

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Soil is one of the most important farming resources. Appropriate managing of its quality promotes productive and sustainable agriculture. The valuable farm practice in soil quality managing is based on regular soil analysis with the aim of determining the exact amount of nutrients or other chemical, physical, and biological soil properties. Soil analysis usually requires sample collection at the desired sampling depth followed by sample delivery to chemical laboratories. However, laboratory analyses are resource-intensive and costly, and require a lot of time, effort, and equipment. A low-cost, fast, and effective alternative for soil quality control is the application of smartphones to perform chemical analyses directly in the field or on the farm. In this paper, an overview of recent developments on smartphone-based methodologies for agricultural purposes and portable evaluation of soil quality and its properties is presented. The discussion focuses on recent applications of smartphone-based devices for the determination of basic soil parameters, content of organic matter, mineral fertilizers, and organic or inorganic pollutants. Obvious advantages of using smartphones, such as convenience and simplicity of use, and the main shortcomings, such as relatively poor precision of the results obtained, are also discussed. The general trend shows the huge interest from researchers to move the technology into the field with the aim of providing cost-effective and rapid soil analysis. This paper can broaden the understanding of using smartphones for chemical analysis of soil samples, as it is a relatively new area and is expected to be developed rapidly. Graphical Abstract

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Section: Soil Contamination Monitoringmentioning

confidence: 99%

Analytical applications of smartphones for agricultural soil analysis

Vakh

2023

Anal Bioanal Chem

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“…In the application of the CST, the diagnostic horizon is a specific soil horizon with quantitatively defined properties, which can finally determine the soil type. However, identifying and delineating diagnostic horizons in field soil surveys requires considerable effort to collect samples and measure the physical and chemical data of the soil samples [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Toward Field Soil Surveys: Identifying and Delineating Soil Diagnostic Horizons Based on Deep Learning and RGB Image

2022

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The diagnostic horizon in a soil is reflective of the environment in which it developed and the inherent characteristics of the material, therefore quantitative approaches to horizon delineation should focus on the diagnostic horizon. Moreover, it can enable the exchange and transfer of soil information between different taxonomic systems. This study aims to explore the use of deep learning and RGB images to train a soil diagnostic horizon identification model that can help field workers determine soil horizon information quickly, efficiently, easily, and cost-effectively. A total of 331 soil profile images of the main soil categories (five soil orders, including Primosols, Ferrosols, Argosols, Anthrosols, and Cambosols) from Hubei and Jiangxi Provinces were used. Each soil profile image was preprocessed and augmented to 10 images and then inputted into the UNet++ architecture. The mean intersection over union and pixel accuracy of the model were 71.24% and 82.66%, respectively. Results show that the model could accurately identify and delineate the soil diagnostic horizons. Moreover, the model performance varied considerably due to the definition of the horizon and whether the diagnostic conditions applied to a wide range of visual features on RGB images, the number of samples, and the soil characteristics of the study area.

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