Mike Badzmierowski

Dr. Mike Badzmierowski

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 August 2019 in Agronomy
Verified
Journal Article
Open access
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MBMike Badzmierowski
Mike Badzmierowski
David McCall.David McCall.
David McCall.
GEGregory Evanylo
Gregory Evanylo
Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband reflectance data for a cheaper cost. Spectral reflectance data have been used to create vegetation indices such as the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (RVI) to assess crop growth, density, and fertility. Other indices such as the water band index (WBI) (narrowband index) and green-to-red ratio index (GRI) (both broadband and narrowband index) have been proposed to predict soil moisture status in turfgrass systems. The objective of this study was to compare the value of multispectral and hyperspectral radiometers to assess soil volumetric water content (VWC) and tall fescue (Festuca arundinacea Schreb.) responses. The multispectral radiometer VI had the strongest relationships to turfgrass quality, biomass, and tissue N accumulation during the trial period (April 2017–August 2018). Soil VWC had the strongest relationship to WBI (r = 0.60), followed by GRI and NDVI (both r = 0.54) for the 0% evapotranspiration (ET). Nonlinear regression showed strong relationships at high water stress periods in each year for WBI (r = 0.69–0.79), GRI (r = 0.64–0.75), and NDVI (r = 0.58–0.79). Broadband index data collected using a mobile multispectral sensor is a cheaper alternative to hyperspectral radiometry and can provide better spatial coverage.

19 March 2021 in Environmental Evidence
Verified
Journal Article
Open access
PDF file
MBMike Badzmierowski
Mike Badzmierowski
GEGregory K. Evanylo
Gregory K. Evanylo
WDW. Lee Daniels
W. Lee Daniels
KHKathryn C. Haering
Kathryn C. Haering
Background: Human wastewater biosolids, hereafter referred to as biosolids, are produced in significant quantities around the world and often applied to an extensive land mass including agricultural fields, forests, mine lands, and urban areas. Land-application of biosolids has been reported in peer-reviewed and non-peer-reviewed work to change soil organic carbon stocks in varying amounts. Determining the potential of soil organic carbon (SOC) stock change and sequestration from biosolids land application is critical for biosolids producers and users to gain access to carbon credit markets. Our review question is, "what is the impact of biosolids application on long-term soil carbon sequestration rates?” We look to explore this main question with the follow-up, "does biosolids processing methods and characteristics, application method, soil properties, land management and other modifiers affect rates of carbon accumulation from land-applied biosolids?" Methods: Searches will be conducted using online databases (i.e., Web of Science Core Collection, CAB Abstracts, Scopus, ProQuest Dissertations & Theses Global), search engines (Google Scholar and Microsoft Academic), and specialist websites to find primary field studies and grey literature of biosolids land-application effects on soil organic carbon stocks. We will use English search terms and predefined inclusion criteria of: (1) a field study of at least 24 months that reports soil organic carbon/matter (SOC/SOM) concentrations/stocks; (2) has two types of treatments: (i) a control (non-intervention AND/OR synthetic fertilizer) AND (ii) a biosolids-based amendment; and (3) information of amendment properties and application dates and rates to estimate the relative contribution of the applied materials to SOC changes. We will screen results in two stages: (1) title and abstract and (2) full text. A 10% subset will be screened by two reviewers for inclusion at the title and abstract level and use a kappa analysis to ensure agreement of at least 0.61. All results in the full text stage will be dual screened. Data will be extracted by one person and reviewed by a second person. Critical appraisal will be used to assess studies’ potential bias and done by two reviewers. A meta-analysis using random effects models will be conducted if sufficient data of high enough quality are extracted.

1 May 2019 in Crop Science
Verified
Journal Article
Closed access
PDF file
MBMike Badzmierowski
Mike Badzmierowski
GEGregory K. Evanylo
Gregory K. Evanylo
EEErik H. Ervin
Erik H. Ervin
ABAdam Boyd
Adam Boyd
CBCarlyle Brewster
Carlyle Brewster

29 September 2021 in Agronomy
Verified
Journal Article
Open access
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TRTravis Leon Roberson
Travis Leon Roberson
MBMike Badzmierowski
Mike Badzmierowski
Ryan StewartRyan Stewart
Ryan Stewart
EEErik H. Ervin
Erik H. Ervin
SAShawn D. Askew
Shawn D. Askew
David McCall.David McCall.
David McCall.
The need for water conservation continues to increase as global freshwater resources dwindle. Turfgrass mangers are adapting to these concerns by implementing new tools to reduce water consumption. Time-domain reflectometer (TDR) soil moisture sensors can decrease water usage when scheduling irrigation, but nonuniformity across unsampled locations creates irrigation inefficiencies. Remote sensing data have been used to estimate soil moisture stress in turfgrass systems through the normalized difference vegetation index (NDVI). However, numerous stressors other than moisture constraints impact NDVI values. The water band index (WBI) is an alternative index that uses narrowband, near-infrared light reflectance to estimate moisture limitations within the plant canopy. The green-to-red ratio index (GRI) is a vegetation index that has been proposed as a cheaper alternative to WBI as it can be measured using digital values of visible light instead of relying on more costly hyperspectral reflectance measurements. A replicated 2 × 3 factorial experimental design was used to repeatedly measure turf canopy reflectance and soil moisture over time as soils dried. Pots of ‘007’ creeping bentgrass (CBG) and ‘Latitude 36’ hybrid bermudagrass (HBG) were grown on three soil textures: United States Golf Association (USGA) 90:10 sand, loam, and clay. Reflectance data were collected hourly between 07:00 and 19:00 using a hyperspectral radiometer and volumetric water content (VWC) data were collected continuously using an embedded soil moisture sensor from soil saturation until complete turf necrosis by drought stress. The WBI had the strongest relationship to VWC (r = 0.62) compared to GRI (r = 0.56) and NDVI (r = 0.47). The WBI and GRI identified significant moisture stress approximately 28 h earlier than NDVI (p = 0.0010). Those metrics also predicted moisture stress prior to fifty percent visual estimation of wilt (p = 0.0317), with lead times of 12 h (WBI) and 9 h (GRI). By contrast, NDVI provided 2 h of prediction time. Nonlinear regression analysis showed that WBI and GRI can be useful for predicting moisture stress of CBG and HBG grown on three different soil textures in a controlled environment.

8 March 2020 in Crop Science
Verified
Journal Article
Closed access
PDF file
MBMike Badzmierowski
Mike Badzmierowski
GEGregory K. Evanylo
Gregory K. Evanylo
EEErik H. Ervin
Erik H. Ervin