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Kristen S. Veum
USDA-Agriculture Research Service, Cropping Systems and Water Quality Research Unit, 269 Agricultural Engineering Bldg., University of Missouri, Columbia, MO 65211, United States

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Journal article
Published: 15 March 2021 in Soil Security
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Soil security is a multifaceted framework that considers soil as an integral part of addressing societal concerns towards global environmental challenges. Soil health assessments are tools that can be used to integrate knowledge about and social interest in soil resource sustainability. Appropriate interpretation of soil health assessments require robust databases of soil properties and their variation across large regional areas. This analysis explored field-scale spatial and temporal variation in 16 soil health indicators used in common soil health assessments at Soil Health Partnership (SHP) locations throughout the Midwestern U.S. from 2014–2019. Relationships among management, environment, and measured soil properties were examined using various combinations of correlation, principal component analysis (PCA), and multiple regression. Specifically, variability was evaluated using 1) the temporal average of indicator lab test values, 2) the temporal and spatial coefficient of variation (CV), and 3) corn (Zea mays) and soybean (Glycine max) yield variation. Solvita® had the highest spatial and temporal CV, while organic matter (OM), autoclaved citrate extractable protein (ACE), and pH had the lowest spatial and temporal CV values. The PCA analysis identified climate, soil texture, organic C and N pools, and soil water availability as factors that accounted for variation in soil health indicator values. Multiple regression showed that climate variables and field conditions strongly affect corn and soybean yield variation. Solvita, OM, and available water content improved corn and soybean yield variation estimates. These results show that considering spatial and temporal variation when monitoring soil health changes may improve soil health assessment interpretation.

ACS Style

Bradley S. Crookston; Matt A. Yost; Maria Bowman; Kristen Veum; Grant Cardon; Jeanette Norton. Soil health spatial-temporal variation influence soil security on Midwestern, U.S. farms. Soil Security 2021, 3, 100005 .

AMA Style

Bradley S. Crookston, Matt A. Yost, Maria Bowman, Kristen Veum, Grant Cardon, Jeanette Norton. Soil health spatial-temporal variation influence soil security on Midwestern, U.S. farms. Soil Security. 2021; 3 ():100005.

Chicago/Turabian Style

Bradley S. Crookston; Matt A. Yost; Maria Bowman; Kristen Veum; Grant Cardon; Jeanette Norton. 2021. "Soil health spatial-temporal variation influence soil security on Midwestern, U.S. farms." Soil Security 3, no. : 100005.

Papers on original research
Published: 04 March 2021 in Soil Science Society of America Journal
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The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site‐specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. SHAPE was developed using 14,680 soil organic carbon (SOC) observations from across the United States and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model‐based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0 to 100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with four case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator. This article is protected by copyright. All rights reserved

ACS Style

Márcio R. Nunes; Kristen S. Veum; Paul A. Parker; Scott H. Holan; Douglas L. Karlen; Joseph P. Amsili; Harold M. van Es; Skye A. Wills; Cathy A. Seybold; Thomas B. Moorman. The soil health assessment protocol and evaluation applied to soil organic carbon. Soil Science Society of America Journal 2021, 85, 1196 -1213.

AMA Style

Márcio R. Nunes, Kristen S. Veum, Paul A. Parker, Scott H. Holan, Douglas L. Karlen, Joseph P. Amsili, Harold M. van Es, Skye A. Wills, Cathy A. Seybold, Thomas B. Moorman. The soil health assessment protocol and evaluation applied to soil organic carbon. Soil Science Society of America Journal. 2021; 85 (4):1196-1213.

Chicago/Turabian Style

Márcio R. Nunes; Kristen S. Veum; Paul A. Parker; Scott H. Holan; Douglas L. Karlen; Joseph P. Amsili; Harold M. van Es; Skye A. Wills; Cathy A. Seybold; Thomas B. Moorman. 2021. "The soil health assessment protocol and evaluation applied to soil organic carbon." Soil Science Society of America Journal 85, no. 4: 1196-1213.

Journal article
Published: 24 February 2021 in Applied Soil Ecology
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Soil health changes induced by prairie reconstruction (cultivated fields to tallgrass prairie) were assessed in Central Missouri within sites representing a chronosequence of 0, 2, 3, 4, 6, 9, 10, 11, 12, and 13-yr post-reconstruction. In addition, a nearby remnant native prairie, two long-term reconstructed prairies (~25 and ~57-yr post-reconstruction), and a biofuel prairie 9-yr post-reconstruction were evaluated for comparative purposes. From 0 to 8-yr, prairie reconstruction increased soil aggregation, total soil organic carbon (SOC), total nitrogen (TN), active C and N (permanganate oxidizable C and total protein), and mineralizable C and N (soil respiration and potentially mineralizable nitrogen), becoming more similar to levels in the remnant prairie. Further, four enzymes involved in the cycling of C (β-glucosidase), N (β-glucosaminidase), P (acid phosphatase), and S (arylsulfatase) demonstrated amplified activities within samples collected to a depth of 15-cm. Over time, the ratios of active C to SOC and active N to TN declined, reflecting the conversion of active C/N pools into more stable C/N pools due to continued organic inputs and increased microbial activity. In contrast, from 8- to 13-yr post-reconstruction, the number of these same soil health indicators declined, which may be attributed to historical land use, the improvement of prairie reconstruction and management strategies, and ecological processes related to succession. Overall, prairie reconstruction holds great potential for soil health restoration in degraded agricultural landscapes, and further study is needed to understand how historical land use and prairie reconstruction practices affect soil health and ecological resilience.

ACS Style

Chenhui Li; Kristen S. Veum; Keith W. Goyne; Márcio R. Nunes; Veronica Acosta-Martinez. A chronosequence of soil health under tallgrass prairie reconstruction. Applied Soil Ecology 2021, 164, 103939 .

AMA Style

Chenhui Li, Kristen S. Veum, Keith W. Goyne, Márcio R. Nunes, Veronica Acosta-Martinez. A chronosequence of soil health under tallgrass prairie reconstruction. Applied Soil Ecology. 2021; 164 ():103939.

Chicago/Turabian Style

Chenhui Li; Kristen S. Veum; Keith W. Goyne; Márcio R. Nunes; Veronica Acosta-Martinez. 2021. "A chronosequence of soil health under tallgrass prairie reconstruction." Applied Soil Ecology 164, no. : 103939.

Journal article
Published: 28 September 2020 in Environmental and Sustainability Indicators
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The Soil Management Assessment Framework (SMAF) was developed to collectively assess biological, chemical, and physical soil health changes due to management practices. SMAF scoring curves were designed to be site-specific but were never validated at national scale. Our goal was to verify the national effectiveness of SMAF for detecting changes induced by conservation practices. Data from 456 articles representing the U.S. was compiled as input for a SMAF analysis. Soil organic-C (SOC), microbial biomass-C (MBC), β-glucosidase activity (BG), macroaggregate stability (AS), bulk density (BD), pH, soil-test P and K indices and an overall soil quality index (SQI) were computed. Measured, scored, and SQI values were used to evaluate tillage intensity [conventional (CT), reduced tillage (RT), no-till (NT), and zero disturbance (perennial systems; PER)] and soil cover [annual cropping systems without cover crops (ANCC), annual cropping systems with cover crops (ACC), and year-round soil cover (perennial systems; PER)]. Reducing tillage intensity and increasing soil cover increased topsoil SOC, MBC, BG, and AS values (measured and scored). SMAF scoring curves were sensitive to agronomic practice effects on soil function. The highest SQI values were associated with perennial systems (zero soil disturbance) and year-round living roots. Within annual cropping systems, cover cropping, and NT demonstrated better soil biological and physical functioning. However, SMAF scores underestimated the effects for SOC and BG and overestimated the effects for AS, suggesting the algorithms for those indicators should be reevaluated and improved. Overall, this national assessment confirmed the utility of SMAF and highlighted benefits of conservation practices.

ACS Style

Márcio R. Nunes; Douglas L. Karlen; Kristen S. Veum; Thomas B. Moorman. A SMAF assessment of U.S. tillage and crop management strategies. Environmental and Sustainability Indicators 2020, 8, 100072 .

AMA Style

Márcio R. Nunes, Douglas L. Karlen, Kristen S. Veum, Thomas B. Moorman. A SMAF assessment of U.S. tillage and crop management strategies. Environmental and Sustainability Indicators. 2020; 8 ():100072.

Chicago/Turabian Style

Márcio R. Nunes; Douglas L. Karlen; Kristen S. Veum; Thomas B. Moorman. 2020. "A SMAF assessment of U.S. tillage and crop management strategies." Environmental and Sustainability Indicators 8, no. : 100072.

Journal article
Published: 15 July 2020 in Sustainability
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Soil organic carbon (SOC) influences several soil functions, making it one of the most important soil health indicators. Its quantity is determined by anthropogenic and inherent factors that must be understood to improve SOC management and interpretation. Topsoil (≤15 cm) SOC response to tillage depth and intensity, cover crops, stover removal, manure addition, and various cropping systems was assessed using 7610 observations from eight U.S. regions. Overall, including cover crops, reducing tillage depth and intensity increased SOC. The positive effects of cover crops were more noticeable in South Central, Northwest, and Midwest regions. Removing high rates (>65%) of crop residue decreased SOC in Midwestern and Southeastern soils. Depending on region, applying manure increased SOC by 21 to 41%, compared to non-manured soils. Diversified cropping systems (e.g., those utilizing small mixed vegetables, perennials, or dairy-based systems) had the highest topsoil SOC content, while more intensive annual row crops and large-scale single vegetable production systems, had the lowest. Among inherent factors, SOC increased as precipitation increased, but decreased as mean annual temperature increased. Texture influenced SOC, showing higher values in fine-texture than coarse-texture soils. Finally, this assessment confirmed that SOC can be a sensitive soil health indicator for evaluating conservation practices.

ACS Style

Márcio Nunes; Harold Van Es; Kristen Veum; Joseph Amsili; Douglas Karlen. Anthropogenic and Inherent Effects on Soil Organic Carbon across the U.S. Sustainability 2020, 12, 5695 .

AMA Style

Márcio Nunes, Harold Van Es, Kristen Veum, Joseph Amsili, Douglas Karlen. Anthropogenic and Inherent Effects on Soil Organic Carbon across the U.S. Sustainability. 2020; 12 (14):5695.

Chicago/Turabian Style

Márcio Nunes; Harold Van Es; Kristen Veum; Joseph Amsili; Douglas Karlen. 2020. "Anthropogenic and Inherent Effects on Soil Organic Carbon across the U.S." Sustainability 12, no. 14: 5695.

Article
Published: 28 June 2020 in Agronomy Journal
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Anaerobic potentially mineralizable nitrogen (PMN) combined with preplant nitrate test (PPNT) or pre‐sidedress nitrate test (PSNT) may improve corn (Zea mays L.) N management. Forty‐nine corn N response studies were conducted across the U.S. Midwest to evaluate the capacity of PPNT and PSNT to predict grain yield, N uptake, and economic optimal N rate (EONR) when adjusted by soil sampling depth, soil texture, temperature, PMN, and initial NH4–N from PMN analysis. Pre‐plant soil samples were obtained for PPNT (0‐ to 30‐, 30‐ to 60‐, 60‐ to 90‐cm depths) and PMN (0‐ to 30‐cm depth) before corn planting and N fertilization. In‐season soil samples were obtained at the V5 corn development stage for PSNT (0‐ to 30‐, 30‐ to 60‐cm depths) at 0 kg N ha−1 at‐planting rate and for PMN when 0 and 180 kg N ha−1 was applied at planting. Grain yield, N uptake, and EONR were best predicted when separating soils by texture or sites by annual growing degree‐days and including PMN and initial NH4–N with either NO3–N test. Using PSNT (mean R2 = .30)‐instead of PPNT (mean R2 = .19)‐based models normally increased predictability of corn agronomic variables by a mean of 11%. Including PMN and initial NH4–N with PPNT or PSNT only marginally improved predictability of grain yield, N uptake, and EONR (R2 increase ≤ .33; mean R2 = .35). Therefore, including PMN with PPNT or PSNT is not suggested as a tool to improve N fertilizer management in the U.S. Midwest.

ACS Style

Jason D. Clark; Fabián G. Fernández; Kristen S. Veum; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Newell R. Kitchen; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John F. Shanahan. Soil‐nitrogen, potentially mineralizable‐nitrogen, and field condition information marginally improves corn nitrogen management. Agronomy Journal 2020, 112, 4332 -4343.

AMA Style

Jason D. Clark, Fabián G. Fernández, Kristen S. Veum, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Daniel E. Kaiser, Newell R. Kitchen, Carrie A. M. Laboski, Emerson D. Nafziger, Carl J. Rosen, John E. Sawyer, John F. Shanahan. Soil‐nitrogen, potentially mineralizable‐nitrogen, and field condition information marginally improves corn nitrogen management. Agronomy Journal. 2020; 112 (5):4332-4343.

Chicago/Turabian Style

Jason D. Clark; Fabián G. Fernández; Kristen S. Veum; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Newell R. Kitchen; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John F. Shanahan. 2020. "Soil‐nitrogen, potentially mineralizable‐nitrogen, and field condition information marginally improves corn nitrogen management." Agronomy Journal 112, no. 5: 4332-4343.

Papers on original research
Published: 25 June 2020 in Soil Science Society of America Journal
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Fatty acid methyl ester (FAME) profiling for characterizing microbial community composition typically is conducted via phospholipid fatty acid (PLFA) or ester‐linked fatty acid methyl ester (EL‐FAME) methods. As soil health assessments aim to be utilized across the nation and globe, the robust measurement and interpretation of microbial communities across a range of soils and environments will be necessary. This study compared PLFA and EL‐FAME methods for detecting and interpreting profiles of microbial community composition in croplands across a wide geographic area using a total of 172 soil samples from 14 states representing a wide range of soil properties. Overall, PLFA and EL‐FAME provided comparable biomarkers in terms of microbial community composition. The Spearman's Rank correlation test showed positive correlations (r = 0.37‐0.71) between PLFA and EL‐FAME methods for absolute abundance of total FAME and individual microbial groups including fungi [saprophytic fungi (SF), arbuscular mycorrhizal fungi (AMF), and general fungi (F)] and all bacterial groups [Gram positive (GMP), Gram negative (GMN), and Actinobacteria]. In both methods, a common set of fatty acids were influential in differentiating samples. The main differences in biomarker abundances between the two methods were that fungal and Actinobacteria biomarkers [e.g., 16:1ω5c (AMF), 18:1ω9c (F), 18:3ω6c (F), and 10Me16:0 (Actinobacteria)] were more abundant or critical in EL‐FAME profiling (large variation among soil samples and sensitive to soil properties), but bacterial biomarkers such as i 15:0 (GMP), 16:1ω7c (GMN), 18:1ω7c (GMN), and cy19:0ω7c (GMN) were more dominant and responsive to soil properties in PLFA profiling. The practical advantages of EL‐FAME are lower cost and simpler methodology. Although both methods produced similar microbial profile abundances for important microbial markers, PLFA was more sensitive to the wide range of soil chemical properties in this sample set including pH, clay content, soil organic matter, and active carbon. This article is protected by copyright. All rights reserved

ACS Style

Chenhui Li; Amanda Cano; Veronica Acosta‐Martinez; Kristen S. Veum; Jennifer Moore‐Kucera. A comparison between fatty acid methyl ester profiling methods (PLFA and EL‐FAME) as soil health indicators. Soil Science Society of America Journal 2020, 84, 1153 -1169.

AMA Style

Chenhui Li, Amanda Cano, Veronica Acosta‐Martinez, Kristen S. Veum, Jennifer Moore‐Kucera. A comparison between fatty acid methyl ester profiling methods (PLFA and EL‐FAME) as soil health indicators. Soil Science Society of America Journal. 2020; 84 (4):1153-1169.

Chicago/Turabian Style

Chenhui Li; Amanda Cano; Veronica Acosta‐Martinez; Kristen S. Veum; Jennifer Moore‐Kucera. 2020. "A comparison between fatty acid methyl ester profiling methods (PLFA and EL‐FAME) as soil health indicators." Soil Science Society of America Journal 84, no. 4: 1153-1169.

Papers on original research
Published: 19 May 2020 in Soil Science Society of America Journal
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Soil microbes drive biological functions that mediate chemical and physical processes necessary for plants to sustain growth. Laboratory soil respiration has been proposed as one universal soil health indicator representing these functions, potentially informing crop and soil management decisions. Research is needed to test the premise that soil respiration is helpful for profitable in‐season nitrogen (N) rate management decisions in corn (Zea mays L). The objective of this research was two‐fold, 1) determine if the amount of N applied at the time of planting effected soil respiration, and 2) to evaluate the relationship of soil respiration to corn yield response to fertilizer N application. A total of 49 N response trials were conducted across eight states over three growing seasons (2014 – 2016). The 4‐day Comprehensive Assessment of Soil Health (CASH) soil respiration method was used to quantify soil respiration. Averaged over all sites, N fertilization did not impact soil respiration, but at four sites soil respiration decreased as N fertilizer rate applied at‐planting increased. Across all site‐years, soil respiration was moderately related to the economical optimum N rate (EONR) (r2 = 0.21). However, when analyzed by year, soil respiration was more strongly related to EONR in 2016 (r2 = 0.50) and poorly related for the first two years (r2 < 0.20). These results illustrate the factors influencing the ability of laboratory soil respiration to estimate corn N response, including growing‐season weather, and the potential of fusing soil respiration with other soil and weather measurements for improved N fertilizer recommendations. This article is protected by copyright. All rights reserved

ACS Style

G. Mac Bean; Newell R. Kitchen; Kristen S. Veum; James J. Camberato; Richard B. Ferguson; Fabian G. Fernandez; David W. Franzen; Carrie A.M. Laboski; Emerson D. Nafziger; John E. Sawyer; Matt Yost. Relating four‐day soil respiration to corn nitrogen fertilizer needs across 49 U.S. Midwest fields. Soil Science Society of America Journal 2020, 84, 1195 -1208.

AMA Style

G. Mac Bean, Newell R. Kitchen, Kristen S. Veum, James J. Camberato, Richard B. Ferguson, Fabian G. Fernandez, David W. Franzen, Carrie A.M. Laboski, Emerson D. Nafziger, John E. Sawyer, Matt Yost. Relating four‐day soil respiration to corn nitrogen fertilizer needs across 49 U.S. Midwest fields. Soil Science Society of America Journal. 2020; 84 (4):1195-1208.

Chicago/Turabian Style

G. Mac Bean; Newell R. Kitchen; Kristen S. Veum; James J. Camberato; Richard B. Ferguson; Fabian G. Fernandez; David W. Franzen; Carrie A.M. Laboski; Emerson D. Nafziger; John E. Sawyer; Matt Yost. 2020. "Relating four‐day soil respiration to corn nitrogen fertilizer needs across 49 U.S. Midwest fields." Soil Science Society of America Journal 84, no. 4: 1195-1208.

Journal article
Published: 06 May 2020 in Agronomy Journal
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ACS Style

Jason D. Clark; Fabián G. Fernández; Kristen S. Veum; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Newell R. Kitchen; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John F. Shanahan. Adjusting corn nitrogen management by including a mineralizable‐nitrogen test with the preplant and presidedress nitrate tests. Agronomy Journal 2020, 112, 3050 -3064.

AMA Style

Jason D. Clark, Fabián G. Fernández, Kristen S. Veum, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Daniel E. Kaiser, Newell R. Kitchen, Carrie A. M. Laboski, Emerson D. Nafziger, Carl J. Rosen, John E. Sawyer, John F. Shanahan. Adjusting corn nitrogen management by including a mineralizable‐nitrogen test with the preplant and presidedress nitrate tests. Agronomy Journal. 2020; 112 (4):3050-3064.

Chicago/Turabian Style

Jason D. Clark; Fabián G. Fernández; Kristen S. Veum; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Newell R. Kitchen; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John F. Shanahan. 2020. "Adjusting corn nitrogen management by including a mineralizable‐nitrogen test with the preplant and presidedress nitrate tests." Agronomy Journal 112, no. 4: 3050-3064.

Article
Published: 20 March 2020 in Agronomy Journal
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Soil biological activity is a key feature of healthy soil. The flush of CO2 during the first few days after rewetting of a dried soil is a rapid indicator of soil biological health, but variations in approach require testing and calibration. A 3‐d incubation method (25°C, 50% water‐filled pore space, acid titration) was compared with a 4‐d incubation method (∼20°C, capillary wetted, electrical conductivity) from two long‐term field experiments in Missouri (silt loam soils) and North Carolina (sandy loam and loamy sand soils). The two methods were related (p < .001) to each other (r2 = .93, n = 211 for Missouri soils and r2 = .68, n = 126 for North Carolina soils), but results differed in absolute value in an unexpected manner. Differences in incubation time (3 vs. 4 d), temperature (∼20 vs. 25°C), and water delivery (50% water‐filled pore space vs. capillary wetting) were major factors affecting relationships between methods. Time and temperature were predictable and scalable factors, but water delivery approach likely caused random variations specific to soil type. Both methods were able to discern depth stratification of soil biological activity, but subtle differences due to landscape position and soil texture were detected only with the 3‐d method. We suggest that greater standardization of soil biological activity protocols based on key factors of soil moisture, temperature, and time of incubation be adopted to improve reliability and value to stakeholders.

ACS Style

Alan J. Franzluebbers; Kristen S. Veum. Comparison of two alkali trap methods for measuring the flush of CO 2. Agronomy Journal 2020, 112, 1279 -1286.

AMA Style

Alan J. Franzluebbers, Kristen S. Veum. Comparison of two alkali trap methods for measuring the flush of CO 2. Agronomy Journal. 2020; 112 (2):1279-1286.

Chicago/Turabian Style

Alan J. Franzluebbers; Kristen S. Veum. 2020. "Comparison of two alkali trap methods for measuring the flush of CO 2." Agronomy Journal 112, no. 2: 1279-1286.

Papers on original research
Published: 06 February 2020 in Soil Science Society of America Journal
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Understanding the variables that affect the anaerobic potentially mineralizable N (PMNan) test should lead to a standard procedure of sample collection and incubation length, improving PMNan as a tool in corn (Zea mays L) N management. We evaluated the effect of soil sample timing [preplant and V5 corn development stage (V5)], N fertilization (0 and 180 kg ha−1) and incubation length (7, 14, and 28 d) on PMNan (0–30 cm) across a range of soil properties and weather conditions. Soil sample timing, N fertilization, and incubation length affected PMNan differently based on soil and weather conditions. Preplant vs. V5 PMNan tended to be greater at sites that received 9.7:1; otherwise, V5 PMNan tended to be greater than preplant PMNan. The PMNan tended to be greater in unfertilized vs. fertilized soil in sites with clay content >9.5%, total C <24.2 g kg−1, soil organic matter (SOM) <3.9 g kg−1, or C:N ratios <11.0:1; otherwise, PMNan tended to be greater in fertilized vs. unfertilized soil. Longer incubation lengths increased PMNan at all sites regardless of sampling methods. Since PMNan is sensitive to many factors (sample timing, N fertilization, incubation length, soil properties, and weather conditions), it is important to follow a consistent protocol to compare PMNan among sites and potentially use PMNan to improve corn N management. This article is protected by copyright. All rights reserved

ACS Style

Jason D. Clark; Kristen S. Veum; Fabián G. Fernández; Newell R. Kitchen; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John Shanahan. Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen. Soil Science Society of America Journal 2020, 84, 627 -637.

AMA Style

Jason D. Clark, Kristen S. Veum, Fabián G. Fernández, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Daniel E. Kaiser, Carrie A. M. Laboski, Emerson D. Nafziger, Carl J. Rosen, John E. Sawyer, John Shanahan. Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen. Soil Science Society of America Journal. 2020; 84 (2):627-637.

Chicago/Turabian Style

Jason D. Clark; Kristen S. Veum; Fabián G. Fernández; Newell R. Kitchen; James J. Camberato; Paul R. Carter; Richard B. Ferguson; David W. Franzen; Daniel E. Kaiser; Carrie A. M. Laboski; Emerson D. Nafziger; Carl J. Rosen; John E. Sawyer; John Shanahan. 2020. "Soil sample timing, nitrogen fertilization, and incubation length influence anaerobic potentially mineralizable nitrogen." Soil Science Society of America Journal 84, no. 2: 627-637.

Article
Published: 01 January 2020 in Agronomy Journal
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Sustainable vegetative management plays a significant role in improving soil quality in degraded agricultural landscapes by enhancing soil microbial biomass. This study investigated the effects of grass buffers (GBs), biomass crops (BCs), grass waterways (GWWs), and agroforestry buffers (ABs) on soil microbial biomass and soil organic C (SOC) compared with continuous with corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation (row crop [RC]) on claypan soils. The RC, AB, GB, GWW, and BC treatments were established in 1991, 1997, 1997, 1997, and 2012, respectively, and are located at Greenley Memorial Research Center in Missouri. Soil samples were collected in May 2018 from the 0‐ to 10‐cm depth at summit, backslope, and footslope landscape positions. Within AB treatment, soils were collected from the 50‐cm and 150‐cm tree distance. Total microbial biomass and biomass of gram‐positive bacteria, gram‐negative bacteria, actinomycetes, rhizobia, fungi, arbuscular mycorrhizae, saprophytes, and protozoa were determined by phospholipid fatty acid (PLFA) analysis. Results showed that soil microbial biomass and SOC across all microbial groups were significantly higher (P < .01) under perennial vegetation treatments compared with RC. The footslope position exhibited the highest total microbial biomass compared with the summit and backslope positions. The sampling distance of 50 cm from the tree base demonstrated 16% greater total microbial biomass and 15% higher SOC compared with 150 cm. These findings highlight the influence of landscape on soil biological properties and show that perennial vegetation systems have the potential to increase soil microbial biomass and enhance agricultural sustainability in degraded RC systems.

ACS Style

Salah M. Alagele; Stephen H. Anderson; Ranjith P. Udawatta; Kristen S. Veum; Lalith M. Rankoth. Long‐term perennial management and cropping effects on soil microbial biomass for claypan watersheds. Agronomy Journal 2020, 112, 815 -827.

AMA Style

Salah M. Alagele, Stephen H. Anderson, Ranjith P. Udawatta, Kristen S. Veum, Lalith M. Rankoth. Long‐term perennial management and cropping effects on soil microbial biomass for claypan watersheds. Agronomy Journal. 2020; 112 (2):815-827.

Chicago/Turabian Style

Salah M. Alagele; Stephen H. Anderson; Ranjith P. Udawatta; Kristen S. Veum; Lalith M. Rankoth. 2020. "Long‐term perennial management and cropping effects on soil microbial biomass for claypan watersheds." Agronomy Journal 112, no. 2: 815-827.

Research letter
Published: 01 January 2020 in Agricultural & Environmental Letters
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Soil health indicator values vary based on parent material, native vegetation, and other soil forming factors; therefore, useful interpretations require consideration of inherent soil characteristics. Our objective was to evaluate the distribution of soil health indicators across soil and climate gradients throughout the state of Missouri through a statewide cover crop cost‐share program. Soil samples (0–7 cm) were collected from 5,300 agricultural fields and analyzed for several soil health indicators. Comparisons were made among six regions in the state based on Major Land Resource Area and county boundaries. Results varied for soil organic carbon (C), active C, potentially mineralizable nitrogen, water stable aggregates, and cation exchange capacity by region and corresponded with soil forming factors. Interpretation of soil health indicators must account for regional factors, recognizing that areas with different inherent values have a different potential for soil health.

ACS Style

Stacy M. Zuber; Kristen S. Veum; Robert L. Myers; Newell R. Kitchen; Stephen H. Anderson. Role of inherent soil characteristics in assessing soil health across Missouri. Agricultural & Environmental Letters 2020, 5, 1 .

AMA Style

Stacy M. Zuber, Kristen S. Veum, Robert L. Myers, Newell R. Kitchen, Stephen H. Anderson. Role of inherent soil characteristics in assessing soil health across Missouri. Agricultural & Environmental Letters. 2020; 5 (1):1.

Chicago/Turabian Style

Stacy M. Zuber; Kristen S. Veum; Robert L. Myers; Newell R. Kitchen; Stephen H. Anderson. 2020. "Role of inherent soil characteristics in assessing soil health across Missouri." Agricultural & Environmental Letters 5, no. 1: 1.

Review article
Published: 23 August 2019 in Soil and Tillage Research
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Global interest in soil health has increased exponentially during the past decade, with many different government, non-government, and private sector groups striving to develop monitoring and assessment protocols. This brief review focuses on developments in the United States (U.S.) with some references to activities in other countries. It also documents how the soil health concept evolved and projects what is needed to scientifically advance monitoring and assessment with a particular focus on activities in the U.S. Recommendations emphasize improving the Soil Management Assessment Framework (SMAF) and/or Comprehensive Assessment of Soil Health (CASH) assessment tools, developing protocols for national soil health monitoring, identifying and calibrating better indicators of soil biological, chemical, and physical health, and developing sensors and other tools for more rapid and in-situ assessments. Collectively, these and other research and technology transfer activities will help achieve what we suggest should be a universal goal – striving for healthy soils, healthy landscapes, and vibrant economies.

ACS Style

Douglas L. Karlen; Kristen S. Veum; Kenneth A Sudduth; John F. Obrycki; Márcio R. Nunes. Soil health assessment: Past accomplishments, current activities, and future opportunities. Soil and Tillage Research 2019, 195, 104365 .

AMA Style

Douglas L. Karlen, Kristen S. Veum, Kenneth A Sudduth, John F. Obrycki, Márcio R. Nunes. Soil health assessment: Past accomplishments, current activities, and future opportunities. Soil and Tillage Research. 2019; 195 ():104365.

Chicago/Turabian Style

Douglas L. Karlen; Kristen S. Veum; Kenneth A Sudduth; John F. Obrycki; Márcio R. Nunes. 2019. "Soil health assessment: Past accomplishments, current activities, and future opportunities." Soil and Tillage Research 195, no. : 104365.

Journal article
Published: 15 June 2019 in Agriculture
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Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018, irrespective of CC and no cover crop (NCC) treatments. In CC treatment, β-glucosaminidase activity was significantly greater at 0–10 cm depth in 2016 and at 10–20 and 20–30 cm in 2018. In contrast, dehydrogenase activity was significantly greater in NCC in 2018. Soil pH and organic matter (OM) content were found to be significantly greater in CC. Overall, CC have mixed effects on soil enzyme activities and positive effects on soil OM compared to NCC. This study highlights the short-term influence of CC and illustrates the high spatial and temporal variability of soil enzymes under farmer-managed fields.

ACS Style

Lalith M. Rankoth; Ranjith P. Udawatta; Kristen S. Veum; Shibu Jose; Salah Alagele. Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation. Agriculture 2019, 9, 125 .

AMA Style

Lalith M. Rankoth, Ranjith P. Udawatta, Kristen S. Veum, Shibu Jose, Salah Alagele. Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation. Agriculture. 2019; 9 (6):125.

Chicago/Turabian Style

Lalith M. Rankoth; Ranjith P. Udawatta; Kristen S. Veum; Shibu Jose; Salah Alagele. 2019. "Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation." Agriculture 9, no. 6: 125.

Journal article
Published: 01 March 2019 in Agronomy Journal
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Phospholipid fatty acid (PLFA) analysis is an increasingly popular method for estimating microbial biomass and assessing microbial community structure in soils. In particular, there is a strong interest in the use of PLFA microbial group ratios as benchmarks for soil health assessment and interpretation. Due to the sensitivity of PLFA biomarkers, the recommended procedure for sample handling involves immediate analysis of fresh, field-moist soil, immediate lyophilization with freezer storage, or storage at –80°C. This protocol may not be practical under all circumstances, yet the effects of handling and storage conditions, and the implications for interpretation of PLFA biomarkers, are not fully understood. The primary objective of this study was to evaluate the effects of multiple sample handling and storage conditions on quantification and interpretation of PLFA biomarkers. A suite of soil properties were measured on 17 prairie soil samples, including PLFA analysis. Multiple processing and handling procedures were evaluated by splitting the soil samples and comparing PLFA profiles from (i) fresh soil, (ii) soil stored air-dry for 7 and 14 d, (iii) soil stored field-moist at room temperature for 7 and 14 d, and (iv) soil oven-dried for 24 h at 105°C. All handling and storage procedures resulted in significant losses of PLFA biomarkers relative to fresh, lyophilized samples and microbial groups were disproportionately affected, leading to significant shifts in biomarker ratios. Overall, this study highlights the sensitivity of PLFA biomarkers, the importance of proper sample handling for PLFA analysis, and the potential for error and misinterpretation of PLFA data. Copyright © 2019. . © 2019 The author(s).

ACS Style

Kristen S. Veum; Todd Lorenz; Robert J. Kremer. Phospholipid Fatty Acid Profiles of Soils under Variable Handling and Storage Conditions. Agronomy Journal 2019, 111, 1090 -1096.

AMA Style

Kristen S. Veum, Todd Lorenz, Robert J. Kremer. Phospholipid Fatty Acid Profiles of Soils under Variable Handling and Storage Conditions. Agronomy Journal. 2019; 111 (3):1090-1096.

Chicago/Turabian Style

Kristen S. Veum; Todd Lorenz; Robert J. Kremer. 2019. "Phospholipid Fatty Acid Profiles of Soils under Variable Handling and Storage Conditions." Agronomy Journal 111, no. 3: 1090-1096.

Journal article
Published: 27 February 2019 in Sensors
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Optical diffuse reflectance spectroscopy (DRS) has been used for estimating soil physical and chemical properties in the laboratory. In-situ DRS measurements offer the potential for rapid, reliable, non-destructive, and low cost measurement of soil properties in the field. In this study, conducted on two central Missouri fields in 2016, a commercial soil profile instrument, the Veris P4000, acquired visible and near-infrared (VNIR) spectra (343–2222 nm), apparent electrical conductivity (ECa), cone index (CI) penetrometer readings, and depth data, simultaneously to a 1 m depth using a vertical probe. Simultaneously, soil core samples were obtained and soil properties were measured in the laboratory. Soil properties were estimated using VNIR spectra alone and in combination with depth, ECa, and CI (DECS). Estimated soil properties included soil organic carbon (SOC), total nitrogen (TN), moisture, soil texture (clay, silt, and sand), cation exchange capacity (CEC), calcium (Ca), magnesium (Mg), potassium (K), and pH. Multiple preprocessing techniques and calibration methods were applied to the spectral data and evaluated. Calibration methods included partial least squares regression (PLSR), neural networks, regression trees, and random forests. For most soil properties, the best model performance was obtained with the combination of preprocessing with a Gaussian smoothing filter and analysis by PLSR. In addition, DECS improved estimation of silt, sand, CEC, Ca, and Mg over VNIR spectra alone; however, the improvement was more than 5% only for Ca. Finally, differences in estimation accuracy were observed between the two fields despite them having similar soils, with one field demonstrating better results for all soil properties except silt. Overall, this study demonstrates the potential for in-situ estimation of profile soil properties using a multi-sensor approach, and provides suggestions regarding the best combination of sensors, preprocessing, and modeling techniques for in-situ estimation of profile soil properties.

ACS Style

Xiaoshuai Pei; Kenneth A. Sudduth; Kristen S. Veum; Minzan Li. Improving In-Situ Estimation of Soil Profile Properties Using a Multi-Sensor Probe. Sensors 2019, 19, 1011 .

AMA Style

Xiaoshuai Pei, Kenneth A. Sudduth, Kristen S. Veum, Minzan Li. Improving In-Situ Estimation of Soil Profile Properties Using a Multi-Sensor Probe. Sensors. 2019; 19 (5):1011.

Chicago/Turabian Style

Xiaoshuai Pei; Kenneth A. Sudduth; Kristen S. Veum; Minzan Li. 2019. "Improving In-Situ Estimation of Soil Profile Properties Using a Multi-Sensor Probe." Sensors 19, no. 5: 1011.

Journal article
Published: 10 November 2018 in Sensors
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In situ, diffuse reflectance spectroscopy (DRS) profile soil sensors have the potential to provide both rapid and high-resolution prediction of multiple soil properties for precision agriculture, soil health assessment, and other applications related to environmental protection and agronomic sustainability. However, the effects of soil moisture, other environmental factors, and artefacts of the in-field spectral data collection process often hamper the utility of in situ DRS data. Various processing and modeling techniques have been developed to overcome these challenges, including external parameter orthogonalization (EPO) transformation of the spectra. In addition, Bayesian modeling approaches may improve prediction over traditional partial least squares (PLS) regression. The objectives of this study were to predict soil organic carbon (SOC), total nitrogen (TN), and texture fractions using a large, regional dataset of in situ profile DRS spectra and compare the performance of (1) traditional PLS analysis, (2) PLS on EPO-transformed spectra (PLS-EPO), (3) PLS-EPO with the Bayesian Lasso (PLS-EPO-BL), and (4) covariate-assisted PLS-EPO-BL models. In this study, soil cores and in situ profile DRS spectrometer scans were obtained to ~1 m depth from 22 fields across Missouri and Indiana, USA. In the laboratory, soil cores were split by horizon, air-dried, and sieved (<2 mm) for a total of 708 samples. Soil properties were measured and DRS spectra were collected on these air-dried soil samples. The data were randomly split into training (n = 308), testing (n = 200), and EPO calibration (n = 200) sets, and soil textural class was used as the categorical covariate in the Bayesian models. Model performance was evaluated using the root mean square error of prediction (RMSEP). For the prediction of soil properties using a model trained on dry spectra and tested on field moist spectra, the PLS-EPO transformation dramatically improved model performance relative to PLS alone, reducing RMSEP by 66% and 53% for SOC and TN, respectively, and by 76%, 91%, and 87% for clay, silt, and sand, respectively. The addition of the Bayesian Lasso further reduced RMSEP by 4–11% across soil properties, and the categorical covariate reduced RMSEP by another 2–9%. Overall, this study illustrates the strength of the combination of EPO spectral transformation paired with Bayesian modeling techniques to overcome environmental factors and in-field data collection artefacts when using in situ DRS data, and highlights the potential for in-field DRS spectroscopy as a tool for rapid, high-resolution prediction of soil properties.

ACS Style

Kristen S. Veum; Paul A. Parker; Kenneth A. Sudduth; Scott H. Holan. Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization. Sensors 2018, 18, 3869 .

AMA Style

Kristen S. Veum, Paul A. Parker, Kenneth A. Sudduth, Scott H. Holan. Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization. Sensors. 2018; 18 (11):3869.

Chicago/Turabian Style

Kristen S. Veum; Paul A. Parker; Kenneth A. Sudduth; Scott H. Holan. 2018. "Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization." Sensors 18, no. 11: 3869.

Journal article
Published: 22 March 2018 in Soil Science Society of America Journal
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Precise nutrient management across claypan soil landscapes requires an understanding of how diversity in management practices impacts soil properties and nutrient buffering. Therefore, a study was performed at the Central Mississippi River Basin site of the USDA Long-Term Agroecosystem Network from 2010 to 2016 to determine how depth to claypan (DTC), cropping system (CS), and landscape position (LP) affect soil properties, and whether accounting for these factors could improve fertility management. Treatments consisted of five CS {MTCS, mulch till corn (Zea mays L.)–soybean [Glycine max (L.) Merr.]; NTCS, no-till corn–soybean; NTCSW, no-till corn–soybean–wheat (Triticum aestivum L.)–cover crop; CCRP, cool season conservation reserve program; and HAY, cool and warm-season hay} and three LP (summit, backslope, and footslope), each with a distinct DTC. Soil test P (STP) was 9 kg P ha–1 greater on footslopes than summits. Soil test K (STK) and soil organic matter content (SOM) were greatest on backslopes and averaged 384 kg K ha–1 and 20 g kg–1, respectively, Soil test P was ≥49% and STK was ≥10% lower in NTCSW than in MTCS or NTCS. However, crop diversity in NTCSW maintained STP and increased SOM 2 g kg–1 over MTCS. Soil test P, pHs, and SOM were similar between CCRP and HAY, while STK in CCRP was greater at all LP. Lastly, deeper DTC caused greater P buffering and less K buffering than shallower DTC. These results indicate that eroded sideslopes with shallow DTC likely need more or more frequent P and less K than other LP. Copyright © 2018. . Copyright © by the Soil Science Society of America, Inc.

ACS Style

Lance S. Conway; Matt A. Yost; Newell R. Kitchen; Kenneth A. Sudduth; Kristen S. Veum. Cropping System, Landscape Position, and Topsoil Depth Affect Soil Fertility and Nutrient Buffering. Soil Science Society of America Journal 2018, 82, 382 -391.

AMA Style

Lance S. Conway, Matt A. Yost, Newell R. Kitchen, Kenneth A. Sudduth, Kristen S. Veum. Cropping System, Landscape Position, and Topsoil Depth Affect Soil Fertility and Nutrient Buffering. Soil Science Society of America Journal. 2018; 82 (2):382-391.

Chicago/Turabian Style

Lance S. Conway; Matt A. Yost; Newell R. Kitchen; Kenneth A. Sudduth; Kristen S. Veum. 2018. "Cropping System, Landscape Position, and Topsoil Depth Affect Soil Fertility and Nutrient Buffering." Soil Science Society of America Journal 82, no. 2: 382-391.

Journal article
Published: 01 November 2017 in Geoderma
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Kristen S. Veum; Kenneth A. Sudduth; Robert J. Kremer; Newell R. Kitchen. Sensor data fusion for soil health assessment. Geoderma 2017, 305, 53 -61.

AMA Style

Kristen S. Veum, Kenneth A. Sudduth, Robert J. Kremer, Newell R. Kitchen. Sensor data fusion for soil health assessment. Geoderma. 2017; 305 ():53-61.

Chicago/Turabian Style

Kristen S. Veum; Kenneth A. Sudduth; Robert J. Kremer; Newell R. Kitchen. 2017. "Sensor data fusion for soil health assessment." Geoderma 305, no. : 53-61.