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Douglas L Karlen - One of the best experts on this subject based on the ideXlab platform.
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Soil Quality response to long term tillage and crop rotation practices
Soil & Tillage Research, 2013Co-Authors: Douglas L Karlen, Cynthia A Cambardella, John L Kovar, Thomas S ColvinAbstract:Abstract Soil Quality is influenced by inherent and anthropogenic factors. This study was conducted to provide multiple groups guidance on how to achieve and maintain improved Soil Quality/health. Our hypothesis was that tillage intensity was the primary anthropogenic factor degrading Soil Quality, and our objective was to prove that hypothesis through an intensive 2005 sampling of a central Iowa, USA field study. Chisel plow, disk tillage, moldboard plow, ridge-till and no-till treatments, used for 31 years in a two-year, corn ( Zea mays L.)/soybean [ Glycine max (L.) Merr.] (C/S) rotation or for 26 years of continuous corn (CC) production, were evaluated by measuring 23 potential Soil Quality indicators. Soil samples from 0 to 5- and 5 to 15-cm depth increments were collected from 158 loam or clay loam sampling sites throughout the 10-ha study site. Nine of the indicators were evaluated by depth increment using the Soil Management Assessment Framework (SMAF) which has scoring functions for 13 Soil biological, chemical, and physical measurements and can be used to compute individual indicator indices and an overall Soil Quality index (SQI). Water-stable aggregation (WSA), total organic carbon (TOC), microbial biomass carbon (MBC), and potentially mineralizable nitrogen (PMN) were all significantly lower for the 0 to 5-cm and generally lower for 5 to 15-cm increments after long-term moldboard plowing and its associated secondary tillage operations. This presumably reflected greater physical breakup and oxidation of above- and below-ground plant residues. Bray-P concentrations in moldboard plow plots were also significantly lower at both depth increments. Between Soil texture groups, significant differences were found for WSA, Bray-P, TOC and MBC at both depth increments and for both cropping systems. When combined into an overall SQI, both Soil texture groups were functioning at 82–85% of their potential at 0–5-cm and at 75% of their potential at the 5–15-cm depth. Our hypothesis that moldboard plowing would have the greatest negative effect on Soil Quality indicators was verified. Based on this assessment, we recommend that to achieve and maintain good Soil health, producers should strive to adopt less aggressive tillage practices.
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crop rotation effects on Soil Quality at three northern corn soybean belt locations
Agronomy Journal, 2006Co-Authors: Douglas L Karlen, Cynthia A Cambardella, Susan S Andrews, Eric G Hurley, D W Meek, Michael Duffy, Antonio P MallarinoAbstract:Do extended crop rotations that include forages improve Soil Quality and are they profitable? Our objectives were to determine (i) how crop rotation affected Soil Quality indicators, (ii) if those indicator changes were reflected in Soil Quality index (SQI) ratings when scored and combined using the Soil Management Assessment Framework, and (iii) how SQI values compared with profitability. Soil samples were collected from three long-term studies in Iowa and one in Wisconsin. Bulk density (BD), Soil pH, water-stable macroaggregation, total organic C, total N, microbial biomass C, extractable Pand K, and penetration resistance were measured. The indicator data were scored using nonlinear curves reflecting performance of critical Soil functions (e.g., nutrient cycling, water partitioning and storage, and plant root growth). Profit was calculated by subtracting costs of production from potential income based on actual crop yields and the 20-yr average nongovernment-supported commodity prices. Extended rotations had a positive effect on Soil Quality indicators. Total organic C was the most sensitive indicator, showing significant measured and scored differences at all locations, while BD showed significant differences at only one location (Kanawha). The lowest SQI values and 20-yr average profit were associated with continuous corn, while extended rotations that included at least 3 yr of forage crops had the highest SQI values. We suggest that future conservation policies and programs reward more diverse and extended crop rotations, as is being done through the Conservation Security Program.
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growers perceptions and acceptance of Soil Quality indices
Geoderma, 2003Co-Authors: Susan S Andrews, C B Flora, J P Mitchell, Douglas L KarlenAbstract:Abstract Soil Quality (SQ) assessment tools may facilitate adaptive management decisions that promote sustainable agricultural practices. However, without input from the target audience, these decision tools' potential for adoption remains unknown. In an effort to consider the end-user in SQ index development, we examined farmer reactions to index outcomes and uses for Soil Quality information. We calculated SQ indices for side-by-side comparisons of alternative (organic amendment) and conventional practices in the San Joaquin Valley, CA. The indices integrated chemical, biological, and physical data collected over 3 years in a participatory, on-farm demonstration project. In a focus group format, we asked the participating farmers about their perceptions of SQ in the study fields. We then asked the farmers to compare their perceptions with the calculated SQ indices by rating the amount of agreement between the two on a scale from 1 to 10, with 10 being excellent agreement. The survey results showed a mean of 8 and standard deviation=1 ( N =12). When we presented all participants with a variety of output options for Soil Quality indicator information, they were asked to rate each for usefulness and understandability. The apparent disparity among their preferences (high ratings for the most and the least integrated data) was explained by the suggestion of several farmers that it would be most useful to have access to several forms of the information. Participants also discussed how they would most likely use the tools and what information would be needed for them to change a management practice. A demonstrated link between Soil Quality and economics was the most discussed need. In response to the farmers' emphasis on economic outcomes, we compared our SQ index with yield results (as one component of net revenue) for participating fields. Pearson correlation coefficients showed statistically significant correlations between yield and SQ index outcomes. Correlations were stronger within subsets of the data grouped by crop or Soil suborder. With further refinement and site specificity, a SQ index that is acceptable to its target audience could become a useful adaptive management tool to help maintain or increase the efficiency of sustainable farming practices.
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identification of regional Soil Quality factors and indicators i central and southern high plains
Soil Science Society of America Journal, 2000Co-Authors: John J Brejda, Douglas L Karlen, Thomas B Moorman, Thanh H DaoAbstract:Appropriate indicators for assessing Soil Quality on a regional scale using the National Resource Inventory (NRI) are unknown. Our objectives were to (i) identify Soil Quality factors present at a regional scale, (ii) determine which factors vary significantly with land use, and (iii) select Soil attributes within these factors that can be used as Soil Quality indicators for regional-scale assessment. Ascalon (fine-loamy, mixed, superactive, mesic Aridic Argiustoll) and Amarillo (fine-loamy, mixed, thermic Aridic Paleustalf) Soils were sampled from a statistically representative subset of NRI sample points within the Central and Southern High Plains Major Land Resource Areas (MLRA) and analyzed for 20 Soil attributes. Factor analysis was used to identify Soil Quality factors, and discriminant analysis was used to identify the factors and indicators most sensitive to land use within each MLRA. In the Central High Plains, five Soil Quality factors were identified, with the organic matter and color factors varying significantly with land use. Discriminant analysis selected total organic C (TOC) and total N as the most sensitive indicators of Soil Quality at a regional scale. In the Southern High Plains, six factors were identified, with water stable aggregate (WSA) content, TOC, and Soil salinity varying significantly with land use. Discriminant analysis selected TOC and WSA content as the most sensitive indicators of Soil Quality in the Southern High Plains. Total organic C was the only indicator that consistently showed significant differences between land uses in both regions.
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identification of regional Soil Quality factors and indicators ii northern mississippi loess hills and palouse prairie
Soil Science Society of America Journal, 2000Co-Authors: John J Brejda, Douglas L Karlen, Jeffrey L Smith, Deborah L AllanAbstract:Diversity of Soil series present in a region may hinder identification of Soil Quality factors and indicators at a regional scale. Our objectives were (i) to identify Soil Quality factors for a diverse population of Soils at the regional scale, (ii) to determine which factors vary significantly with land use, (iii) to select indicators from these factors that can be used with the National Resource Inventory (NRI) for monitoring Soil Quality, and (iv) to compare these results to a similar study involving only a single Soil series. One hundred eighty-six points representing 75 Soil series in the Northern Mississippi Valley Loess Hills and 149 points representing 58 Soil series in Palouse and Nez Perce Prairies were sampled from a statistically representative subset of NRI sample points and analyzed for 20 Soil attributes. Factor analysis was used to identify Soil Quality factors and discriminant analysis was used to identify factors and indicators most sensitive to land use within each region. In the Northern Mississippi Valley Loess Hills, five Soil Quality factors were identified. Discriminant analysis selected potentially mineralizable N (PMN), microbial biomass C (MBC), water stable aggregates (WSA), and total organic C (TOC) as the most discriminating attributes between land uses. In the Palouse and Nez Perce Prairies, six factors were identified. Discriminant analysis selected TOC and total N as the most discriminating attributes between land uses. The Soil Quality factors were similar among three of the four regions, but TOC was the only indicator common to all regions for distinguishing among land uses.
Kenneth A Sudduth - One of the best experts on this subject based on the ideXlab platform.
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biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, 13C nuclear magnetic resonance (13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter (r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance (r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
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Biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, ^13C nuclear magnetic resonance (^13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter ( r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance ( r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R^2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
Robert J Kremer - One of the best experts on this subject based on the ideXlab platform.
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Biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, ^13C nuclear magnetic resonance (^13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter ( r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance ( r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R^2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
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biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, 13C nuclear magnetic resonance (13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter (r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance (r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
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developing weed suppressive Soils through improved Soil Quality management
Soil & Tillage Research, 2003Co-Authors: Robert J KremerAbstract:Manipulating Soil microbial communities using Soil and crop management practices is a basic strategy in developing sustainable agricultural systems. Sustainable farming is based, in part, on the efficient management of Soil microorganisms to improve Soil Quality. However, the identification of biological indicators of Soil Quality that can be used to predict weed suppression in Soils has received little attention. We investigated differences in Soil microbial activity among various crop and Soil management systems to assess: (i) the microbiological characteristics of these Soils; (ii) determine whether any relationships existed that might be used in the development of weed suppression. Soil enzyme activity, water-stable aggregates, and the proportions of weed-suppressive bacteria were compared among seven cropping systems and one native-prairie ecosystem in mid-Missouri, USA. Assays of Soil enzymes (fluorescein diacetate hydrolase, dehydrogenase, phosphatase) revealed that organic and integrated cropping systems, and the native-prairie ecosystem had the highest levels of Soil activity. Weed rhizospheres from these same ecosystems also had greater proportions of bacterial isolates characterized as “growth suppressive” to green foxtail (Setaria viridis [L.] Beauv.) and field bindweed (Convolvulus arvensis L.): 15 and 10%, respectively. The proportion of water-stable Soil aggregates was the greatest in Soils with the highest organic matter and was found to be related to higher enzyme and weed-suppressive activity. Selected biological indicators of Soil Quality were associated with potential weed-suppressive activity in Soil when that Soil was managed for high organic matter content under reduced tillage systems. This research study provides further evidence that Soil Quality and sustainable agricultural practices may be linked to integrated weed management systems for the biological suppression of weeds.
Kristen S Veum - One of the best experts on this subject based on the ideXlab platform.
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biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, 13C nuclear magnetic resonance (13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter (r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance (r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
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Biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, ^13C nuclear magnetic resonance (^13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter ( r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance ( r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R^2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
Randall J Miles - One of the best experts on this subject based on the ideXlab platform.
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biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, 13C nuclear magnetic resonance (13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter (r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance (r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
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Biological indicators of Soil Quality and Soil organic matter characteristics in an agricultural management continuum
Biogeochemistry, 2014Co-Authors: Kristen S Veum, Robert J Kremer, Keith W Goyne, Randall J Miles, Kenneth A SudduthAbstract:Relationships among biological indicators of Soil Quality and organic matter characteristics were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical Soil Quality indicators, dehydrogenase and phenol oxidase activity were measured, ^13C nuclear magnetic resonance (^13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of Soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole Soil were collected. Enzyme activities were positively correlated with several Soil Quality indicators and labile fractions of Soil organic matter ( r = 0.58–0.92), and were negatively correlated with DRIFT indices of decomposition stage and recalcitrance ( r = −0.62 to −0.76). A comparison of vegetative and land management practices was scored using the Soil management assessment framework (SMAF)—a Soil Quality index. Perennial vegetation (i.e., native prairie, restored prairie, and timothy) plots exhibited the greatest Soil Quality (SMAF scores 93.6–98.6 out of 100), followed by no-till and conventionally cultivated plots, with wheat outranking corn. Among fertilization practices, Soil Quality followed the order: manure > inorganic fertilizer > unamended Soil. Finally, in the estimation of Soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R^2 > 0.78, RPD > 2.20). Overall, this study demonstrates the potential utility and versatility of enzymes in modeling and assessing changes in Soil organic carbon fractions and Soil Quality, and emphasizes the benefits of maintaining long-term agricultural experiments.
