Low-Input Estimation of Site-Specific Lime Demand Based on Apparent Soil Electrical Conductivity and In Situ Determined Topsoil pH

Cossel, Moritz von; Druecker, Harm; Hartung, Eberhard

doi:10.3390/s19235280

Cited by 9 publications

(2 citation statements)

References 47 publications

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“…Soil pH plays an important role in plant growth by controlling the chemical forms of the different nutrients and influencing the chemical reactions they undergo (Von Cossel et al, 2019). The optimal soil pH for seedling growth and yield of switchgrass is 6.3–8.1.…”

Section: Methodsmentioning

confidence: 99%

Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

et al. 2021

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With a large marginal land area, the Loess Plateau in China holds great potential for biomass production and environmental improvement. Identifying suitable locations for biomass production on marginal land is important for decision‐makers from the viewpoint of land‐use planning. However, there is limited information on the suitability of marginal land within the Loess Plateau for biomass production. Therefore, this study aims to evaluate the suitability of the promising perennial energy crop switchgrass (Panicum virgatum L.) on marginal land across the Loess Plateau. A fuzzy logical model was developed and validated based on field trials on the Loess Plateau and applied to the marginal land of this region, owing to its ability of dealing with the continuous nature of soil, landscape variations, and uncertainties of the input data. This study identified that approximately 12.8–20.8 Mha of the Loess Plateau as available marginal land, of which 2.8–4.7 Mha is theoretically suitable for switchgrass cultivation. These parts of the total marginal land are mainly distributed in northeast and southwest of the Loess Plateau. The potential yield of switchgrass ranges between 44 and 77 Tg. This study showed that switchgrass can grow on a large proportion of the marginal land of the Loess Plateau and therefore offers great potential for biomass provision. The spatial suitability maps produced in this study provide information to farmers and policymakers to enable a more sustainable development of biomass production on the Loess Plateau. In addition, the fuzzy‐theory‐based model developed in this study provided a good framework for evaluating the suitability of marginal land.

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Section: Methodsmentioning

confidence: 99%

Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

et al. 2021

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“…Kuang et al (2014) utilized an on-the-go visible and near-infrared (visNIR) spectroscopy sensor to map the within-field variation of organic carbon, pH and clay content for LR determination. Von Cossel et al (2019) deployed low-input sensor-based soil mapping of electromagnetic induction (EMI) (EM38 MK I; Geonics, Canada) in combination with in situ and ex situ pH measurements to determine the soil's LR. Bönecke et al (2020) applied an on-the-go multi-sensor approach using the Veris Mobile Sensor Platform and the Geophilus Electricus (Geophilus GmbH, Germany) proximal soil sensing system (Lück and Rühlmann, 2013).…”

Section: Introductionmentioning

confidence: 99%

Direct prediction of site-specific lime requirement of arable fields using the base neutralizing capacity and a multi-sensor platform for on-the-go soil mapping

Vogel

Bönecke

Kling³

et al. 2021

Precision Agric

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Liming agricultural fields is necessary for counteracting soil acidity and is one of the oldest operations in soil fertility management. However, the best management practice for liming in Germany only insufficiently considers within-field soil variability. Thus, a site-specific variable rate liming strategy was developed and tested on nine agricultural fields in a quaternary landscape of north-east Germany. It is based on the use of a proximal soil sensing module using potentiometric, geoelectric and optical sensors that have been found to be proxies for soil pH, texture and soil organic matter (SOM), which are the most relevant lime requirement (LR) affecting soil parameters. These were compared to laboratory LR analysis of reference soil samples using the soil’s base neutralizing capacity (BNC). Sensor data fusion utilizing stepwise multi-variate linear regression (MLR) analysis was used to predict BNC-based LR (LRBNC) for each field. The MLR models achieved high adjusted R2 values between 0.70 and 0.91 and low RMSE values from 65 to 204 kg CaCO3 ha−1. In comparison to univariate modeling, MLR models improved prediction by 3 to 27% with 9% improvement on average. The relative importance of covariates in the field-specific prediction models were quantified by computing standardized regression coefficients (SRC). The importance of covariates varied between fields, which emphasizes the necessity of a field-specific calibration of proximal sensor data. However, soil pH was the most important parameter for LR determination of the soils studied. Geostatistical semivariance analysis revealed differences between fields in the spatial variability of LRBNC. The sill-to-range ratio (SRR) was used to quantify and compare spatial LRBNC variability of the nine test fields. Finally, high resolution LR maps were generated. The BNC-based LR method also produces negative LR values for soil samples with pH values above which lime is required. Hence, the LR maps additionally provide an estimate on the quantity of chemically acidifying fertilizers that can be applied to obtain an optimal soil pH value.

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Influence of small-scale spatial variability of soil properties on yield formation of winter wheat

Groß,

Gentsch,

Boy

et al. 2023

Plant Soil

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Background With the increasing development of sophisticated precision farming techniques, high-resolution application maps are frequently discussed as a key factor in increasing yield potential. However, yield potential maps based on multiple soil properties measurements are rarely part of current farming practices. Furthermore, small-scale differences in soil properties have not been taken into account. Methods To investigate the impact of soil property changes at high resolution on yield, a field trial has been divided into a sampling grid of 42 plots. The soil properties in each plot were determined at three soil depths. Grain yield and yield formation of winter wheat were analyzed at two sites. Results Multiple regression analyses of soil properties with yield measures showed that the soil contents of organic carbon, silt, and clay in the top and subsoil explained 45–46% of the variability in grain yield. However, an increasing clay content in the topsoil correlated positively with grain yield and tiller density. In contrast, a higher clay content in the subsoil led to a decrease in grain yield. A cluster analysis of soil texture was deployed to evaluate whether the soil´s small-scale differences caused crucial differences in yield formation. Significant differences in soil organic carbon, yield, and yield formation were observed among clusters in each soil depth. Conclusion These results show that small-scale lateral and vertical differences in soil properties can strongly impact crop yields and should be considered to improve site-specific cropping techniques further.

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Low-Input Estimation of Site-Specific Lime Demand Based on Apparent Soil Electrical Conductivity and In Situ Determined Topsoil pH

Cited by 9 publications

References 47 publications

Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

Direct prediction of site-specific lime requirement of arable fields using the base neutralizing capacity and a multi-sensor platform for on-the-go soil mapping

Influence of small-scale spatial variability of soil properties on yield formation of winter wheat

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