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  • MBL  (1)
  • anabolism  (1)
  • Blackwell Publishing Ltd  (2)
  • American Chemical Society
  • 2020-2024  (2)
  • 1990-1994
  • 1975-1979
  • 1
    Publication Date: 2023-12-12
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Infrared spectroscopy in the visible to near‐infrared (vis–NIR) and mid‐infrared (MIR) regions is a well‐established approach for the prediction of soil properties. Different data fusion and training approaches exist, and the optimal procedures are yet undefined and may depend on the heterogeneity present in the set and on the considered scale. The objectives were to test the usefulness of partial least squares regressions (PLSRs) for soil organic carbon (SOC), total carbon (C〈sub〉t〈/sub〉), total nitrogen (N〈sub〉t〈/sub〉) and pH using vis–NIR and MIR spectroscopy for an independent validation after standard calibration (use of a general PLSR model) or using memory‐based learning (MBL) with and without spiking for a national spectral database. Data fusion approaches were simple concatenation of spectra, outer product analysis (OPA) and model averaging. In total, 481 soils from an Austrian forest soil archive were measured in the vis–NIR and MIR regions, and regressions were calculated. Fivefold calibration‐validation approaches were carried out with a region‐related split of spectra to implement independent validations with n ranging from 47 to 99 soils in different folds. MIR predictions were generally superior over vis–NIR predictions. For all properties, optimal predictions were obtained with data fusion, with OPA and spectra concatenation outperforming model averaging. The greatest robustness of performance was found for OPA and MBL with spiking with 〈italic toggle="no"〉R〈/italic〉〈sup〉2〈/sup〉 ≥ 0.77 (N), 0.85 (SOC), 0.86 (pH) and 0.88 (C〈sub〉t〈/sub〉) in the validations of all folds. Overall, the results indicate that the combination of OPA for vis–NIR and MIR spectra with MBL and spiking has a high potential to accurately estimate properties when using large‐scale soil spectral libraries as reference data. However, the reduction of cost‐effectiveness using two spectrometers needs to be weighed against the potential increase in accuracy compared to a single MIR spectroscopy approach.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: ddc:631.4 ; data fusion ; independent validation ; infrared spectroscopy ; MBL ; nitrogen ; outer product analysis ; pH ; soil organic carbon ; spiking ; total carbon
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-03-18
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Temperature and soil moisture are known to control pesticide mineralization. Half‐life times (DT〈sub〉50〈/sub〉) derived from pesticide mineralization curves generally indicate longer residence times at low soil temperature and moisture but do not consider potential changes in the microbial allocation of pesticide‐derived carbon (C). We aimed to determine carbon use efficiency (CUE, formation of new biomass relative to total C uptake) to better understand microbial utilization of pesticide‐derived C under different environmental conditions and to support the conventional description of degradation dynamics based on mineralization. We performed a microcosm experiment at two MCPA (2‐methyl‐4‐chlorophenoxyacetic acid) concentrations (1 and 20 mg kg〈sup〉−1〈/sup〉) and defined 20°C/pF 1.8 as optimal and 10°C/pF 3.5 as limiting environmental conditions. After 4 weeks, 70% of the initially applied MCPA was mineralized under optimal conditions but MCPA mineralization reached less than 25% under limiting conditions. However, under limiting conditions, an increase in CUE was observed, indicating a shift towards anabolic utilization of MCPA‐derived C. In this case, increased C assimilation implied C storage or the formation of precursor compounds to support resistance mechanisms, rather than actual growth since we did not find an increase in the 〈italic toggle="no"〉tfdA〈/italic〉 gene relevant to MCPA degradation. We were able to confirm the assumption that under limiting conditions, C assimilation increases relative to mineralization and that C redistribution, may serve as an explanation for the difference between mineralization and MCPA dissipation‐derived degradation dynamics. In addition, by introducing CUE to the temperature‐ and moisture‐dependent degradation of pesticides, we can capture the underlying microbial constraints and adaptive mechanisms to changing environmental conditions.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Changing environmental conditions alter the MCPA degradation dynamics and the allocation of pesticide‐derived carbon to anabolic or catabolic metabolism.〈boxed-text position="anchor" content-type="graphic" id="ejss13417-blkfxd-0001" xml:lang="en"〉 〈graphic position="anchor" id="jats-graphic-1" xlink:href="urn:x-wiley:13510754:media:ejss13417:ejss13417-toc-0001"〉 〈/graphic〉 〈/boxed-text〉〈/p〉
    Description: Collaborative Research Center 1253 CAMPOS (DFG)
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: DFG Priority Program 2322 “Soil System”
    Description: Ellrichshausen Foundation
    Description: Research Training Group “Integrated Hydrosystem modeling”
    Description: https://doi.org/10.5281/zenodo.5081655
    Keywords: ddc:631.4 ; anabolism ; carbon use efficiency ; catabolism ; effect of soil moisture and temperature ; gene‐centric process model ; MCPA biodegradation
    Language: English
    Type: doc-type:article
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