Journal Paper Digests

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Journal Paper Digests 2023 #8

  • An identified agronomic interpretation for potassium permanganate oxidizable carbon
  • A simple method to determine the reactivity of calcium carbonate in soils
  • Revisiting laboratory methods for measuring soil water retention curves
  • Estimating lime requirements for tropical soils: Model comparison and development
  • Upscaling soil moisture from point scale to field scale: Toward a general model
  • A field evaluation of the SoilVUE10 soil moisture sensor

A field evaluation of the SoilVUE10 soil moisture sensor

The U.S. Climate Reference Network (USCRN) has been engaged in ground-based soil water and soil temperature observations since 2009. As a nationwide climate network, the network stations are distributed across vast complex terrains. Due to the expansive distribution of the network and the related variability in soil properties, obtaining site-specific calibrations for sensors is a significant and costly endeavor. Presented here are three commercial-grade electromagnetic sensors, with built-in thermistors to measure both soil water and soil temperature, including the SoilVUE10 Time Domain Reflectometry (TDR) probe (hereafter called SP) (Campbell Scientific, Inc.), 50 MHz coaxial impedance dielectric sensor (model HydraProbe, Stevens Water Monitoring Systems, Inc.) (hereafter called HP), and the TDR-315L Probe (model TDR-315L, Acclima, Inc.) (hereafter called AP), which were evaluated in a relatively nonconductive loam soil in Oak Ridge, TN, from 2021 to 2022. The HP manufacturer-supplied calibration equation for loam soils was used in this study. While volumetric water content data from HP and AP were 82-99% of respective gravimetric observations at 10 cm, data from SP were only 65-81% of respective gravimetric observations in the top 20-cm soil horizon, where soil water showed relatively large spatial variability. The poor performance of the SP is likely due to poor contact between SP sensor electrodes and soil and the presence of soil voids caused by the installation method used, which itself may have caused soil disturbance.

Upscaling soil moisture from point scale to field scale: Toward a general model

Field-scale soil moisture measurements are valuable but rarely available because the resolution of most satellite soil moisture products is too coarse, while most in situ sensors provide only point-scale data. Previous upscaling approaches for such data are mostly site-specific, and none are suitable to upscale data from the thousands of stations in existing monitoring networks. To help fill this gap, this research aims to develop a more broadly applicable upscaling approach using data from the Marena, Oklahoma, In Situ Sensor Testbed and a cosmic-ray neutron rover. Rover survey data were used to measure average soil moisture for the similar to 64-ha field on 12 dates in 2019-2020. Statistical modeling was used to identify the soil, terrain, and vegetation properties influencing the relationships between the field-scale rover data and point-scale in situ data from six monitoring sites. Site-specific linear upscaling models estimated the field average soil moisture with root mean squared error (RMSE) values ranging from 0.007 to 0.017 cm(3) cm(-3), but such models are not transferrable between sites. To create a more general model, Least Absolute Shrinkage and Selection Operator regression was used with a leave-one-out cross-validation approach to identify the key predictors for upscaling. The resulting parsimonious model required only the point-scale observations and sand content data and achieved RMSE values ranging from 0.006 to 0.031 cm(3) cm(-3) for the six monitoring sites. The texture-based model demonstrated reasonable accuracy and is a promising step toward a general model that could be broadly applied for upscaling point-scale in situ monitoring stations.

Estimating lime requirements for tropical soils: Model comparison and development

Acid tropical soils may become more productive when treated with agricultural lime, but optimal lime rates have yet to be determined in many tropical regions. In these regions, lime rates can be estimated with lime requirement models based on widely available soil data. We reviewed seven of these models and introduced a new model (LiTAS). We evaluated the models’ ability to predict the amount of lime needed to reach a target change in soil chemical properties with data from four soil incubation studies covering 31 soil types. Two foundational models, one targeting acidity saturation and the other targeting base saturation, were more accurate than the five models that were derived from them, while the LiTAS model was the most accurate. The models were used to estimate lime requirements for 303 African soil samples. We found large differences in the estimated lime rates depending on the target soil chemical property of the model. Therefore, an important first step in formulating liming recommendations is to clearly identify the soil property of interest and the target value that needs to be reached. While the LiTAS model can be useful for strategic research, more information on acidity-related problems other than aluminum toxicity is needed to comprehensively assess the benefits of liming.

Revisiting laboratory methods for measuring soil water retention curves

Traditional laboratory methods for measuring soil water retention curves (SWRCs) typically consist of suction tables, pressure cells, and pressure plate apparatus (i.e., traditional methods). However, technological advancement has resulted in newer methods based on precision mini-tensiometers and dew point water potential meters (i.e., modern methods). This study investigated the discrepancy between SWRCs measured using traditional and modern methods in three soil textures. Our results showed that SWRCs from both traditional and modern methods were similar at the wet end (i.e., matric potentials 0 to -10 kPa) and at the dry end (-500 to -1,500 kPa) of the SWRC, with an average mean absolute difference (MAD) across all three soils of 0.033 and 0.017 cm(3) cm(-3), respectively. The largest discrepancy between methods was consistently observed at moderate tensions of -33 and -70 kPa for the three soils, with an average MAD of 0.059 cm(3) cm(-3) for -33 kPa and a MAD of 0.083 cm(3) cm(-3) for -70 kPa. Plant available water capacity differed by up to 20% between the traditional and modern methods in a clay loam soil. While previous studies have mostly focused on the dry end of the SWRC, our study suggests that additional research comparing traditional and modern methods is required at moderate (-70 and -500 kPa) tension levels.

An identified agronomic interpretation for potassium permanganate oxidizable carbon

The absence of clear empirical relationships between soil health and agronomic outcomes remains an obstacle to widespread adoption of soil health assessments in row crop systems. The objectives of this research were to (1) determine whether soil health indicators are connected to corn (Zea mays L.) productivity and (2) establish interpretive benchmarks for soil health indicators in Missouri. The objectives were accomplished by collecting corn grain yield at 446 monitoring sites (37 m(2)) in 84 commercial production fields in 2018-2020. Soil health and soil fertility samples were collected prior to planting at each site. These data, along with site-specific soil and weather data, were modeled using traditional stepwise regression and nonparametric random forest (RF) and conditional inference forest (CIF) approaches. Root-mean-square errors were similar (1.4-1.5 Mg ha(-1)) with distinct R-2 improvements over stepwise regression for both CIF (R-2 = 0.45) and RF (R-2 = 0.46) algorithms. Only seasonal rainfall and potassium permanganate oxidizable carbon (POXC) were included as top factors governing grain productivity in each model approach, thus demonstrating a regionally robust empirical relationship between POXC and grain productivity. Partial dependency analysis and two decision tree approaches identified 415 mg POXC kg(-1) as a threshold for maximum grain productivity, providing a framework for regional interpretation of on-farm soil health assessments. Little evidence was found connecting grain productivity with autoclaved citrate extractable protein and soil respiration. These findings underscore the power of POXC as an emerging soil health indicator to assess and quantify soil management effects on grain productivity.

A simple method to determine the reactivity of calcium carbonate in soils

Determination of soil carbonate is important for numerous chemical and physical soil processes in arid and semi-arid zones. Here, we modify a conventional method to more easily determine active CaCO3 (ACC) fraction in soils. Unlike the conventional method where the oxalate used up after reaction with carbonate is determined by titration with KMnO4, the proposed method uses the difference between total carbonate analyzed before and after reaction with oxalate to determine ACC. The method compared well to the conventional approach; the procedure was faster, did not require KMnO4, and appeared to be unaffected by exchangeable Ca. The proposed method is well-suited for samples across a wide range of total carbonate.

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