Corn and Soybean Response to Wastewater-recycled Phosphorus Fertilizers

The ability to recycle phosphorus (P) from wastewaters could provide a sustainable, continuous source of P that might also help protect surface water quality from P enrichment. The mineral struvite (MgNH4PO4·6H2O) is an understudied material that can be created from Pcontaining wastewater and has been shown to have agricultural fertilizer value. The objective of this study was to evaluate the effects of electrochemically precipitated struvite (ECST), chemically precipitated struvite (Crystal Green; CG), diammonium phosphate (DAP), monoammonium phosphate (MAP), rock phosphate (RP), and triple super phosphate (TSP) on corn (Zea mays) and soybean (Glycine max) response in a 79-day greenhouse pot study. The effects of fertilizer treatment (i.e., ECST, CG, TSP, MAP, DAP, RP, No P/+N, and No P/-N) on select plant and soil properties were evaluated separately by crop (i.e., soybean and corn). Results demonstrated that when a crop response to P fertilization was expected, there were differences in degree of plant response depending on fertilizer-P source. Although soybean plant properties were not, corn plant properties and corn and soybean elemental tissue concentrations differed (P \u3c 0.05) among fertilizer amendments. Total corn dry matter from ECST did not differ from that from RP and TSP and was 1.2 times greater than that from CG. Belowground corn dry matter from ECST was 1.9 times greater than that from CG, TSP, DAP, No P/+N, and No P/-N. Corn cob-plus-husk dry matter from CG and ECST were similar. Corn belowground tissue P concentration from CG did not differ from that from DAP, TSP, and MAP and was 1.4 times larger than that from ECST. Corn cob-plus-husk tissue P concentration from ECST was similar to that from MAP and DAP and was 1.2 times larger than that from CG. Corn stem-plus-leaves tissue P concentration from ECST differed from that from all other treatments and was 1.8 times greater than that from the No P/+N control. Results generated from this study not only provide information on the understudied electrochemically precipitated struvite, but also further reasons why more research should be conducted on not only the implementation of struvite as a fertilizer-P source, but also struvite\u27s potential impact on sustainable food production and the preservation of water resources

Delineating Field Variation Using Apparent Electrical Conductivity in an Ozark Highlands Agroforestry System

Little to no work has been conducted assessing field variability using repeated electromagnetic induction (EMI) apparent electrical conductivity (ECa) surveys in agroforestry (AF) systems within regions similar to the Ozark Highlands. The objectives of this thesis were to identify i) spatiotemporal ECa variability; ii) ECa-derived soil management zones (SMZs); iii) correlations among EMI-ECa and in-situ, sentential-site soil properties; iv) whether fewer, EMI-ECa surveys could be conducted to capture similar ECa variance as mid-monthly EMI-ECa surveys; v) correlations between ECa and forage yield, tree growth, and terrain attributes based on plant (forage and tree) species, and fertility treatments, and ECa-derived SMZs, and vi); and terrain attributes that have the largest contribution to ECa variability at a 20-year-old, 4.25-ha, AF system in the Ozark Highlands of northwest Arkansas. Between August 2020 and July 2021, 12, mid-monthly ECa surveys were conducted and soil-sensor-based volumetric water content and ECa measurement were made and soil samples for gravimetric water content, EC, and pH were collected from various soil depths at fixed locations. Fourteen terrain attributes of the AF site were obtained. Tree diameter at breast height (DBH) and tree height (TH) measurements were made in December 2020 and March 2021, respectively, and total forage yield samples were collected seven times during Summer 2018 and 2019. The overall mean perpendicular geometry (PRP) and horizontal coplanar geometry (HCP) ECa ranged between 1.8 to 18.0 and 3.1 to 25.8 mS m-1, respectively, and the overall mean HCP ECa was 67% greater than the mean PRP ECa. Largest measured ECa occurred within the local drainage way, which has mapped inclusions with aquic soil moisture regimes, or areas of potential groundwater movement, and smallest measured ECa values occurred within areas with decreased effective soil depth and increased coarse fragments. A positive (r2 = 0.4; P \u3c 0.05) linear relationship occurred over time between PRP ECa standard deviation, with a negative linear relationship (r2 = 0.93; P \u3c 0.05) between HCP ECa coefficient of variation across season (i.e., Summer to Spring). The K-means-clustering method was used to delineate three precision SMZs that were reflective of areas with similar ECa and ECa variability. Relationships between ECa and tree properties were generally stronger within the whole-site, averaged across tree property and ECa configuration (| r | = 0.38), than the SMZs, averaged across tree property, ECa configuration, and SMZ (| r | = 0.27). The strength of the SMZs’ terrain-attribute-PRP-ECa relationships were 9 to 205% greater than that for the whole-site. Whole-site, multi-linear regressions showed that Slope Length and Steepness (LS)-Factor (10.5%), Mid-slope (9.4%), and Valley Depth (7.2%) were terrain attributes that had the greatest influence (i.e., largest percent of total sum of squares) on PRP ECa variability, whereas Valley Depth (15.3%), Wetness Index (11.9%), and Mid-slope (11.2%) had the greatest influence on HCP ECa variability. Results of this study show how ECa varies and relates to soil, plant (i.e., DBH and TH and forage yield), and terrain attributes in AF systems with varying topography that could be used to influence AF management

Delineating Field Variation Using Apparent Electrical Conductivity in an Ozark Highlands Agroforestry System

Little to no work has been conducted assessing field variability using repeated electromagnetic induction (EMI) apparent electrical conductivity (ECa) surveys in agroforestry (AF) systems within regions similar to the Ozark Highlands. The objectives of this thesis were to identify i) spatiotemporal ECa variability; ii) ECa-derived soil management zones (SMZs); iii) correlations among EMI-ECa and in-situ, sentential-site soil properties; iv) whether fewer, EMI-ECa surveys could be conducted to capture similar ECa variance as mid-monthly EMI-ECa surveys; v) correlations between ECa and forage yield, tree growth, and terrain attributes based on plant (forage and tree) species, and fertility treatments, and ECa-derived SMZs, and vi); and terrain attributes that have the largest contribution to ECa variability at a 20-year-old, 4.25-ha, AF system in the Ozark Highlands of northwest Arkansas. Between August 2020 and July 2021, 12, mid-monthly ECa surveys were conducted and soil-sensor-based volumetric water content and ECa measurement were made and soil samples for gravimetric water content, EC, and pH were collected from various soil depths at fixed locations. Fourteen terrain attributes of the AF site were obtained. Tree diameter at breast height (DBH) and tree height (TH) measurements were made in December 2020 and March 2021, respectively, and total forage yield samples were collected seven times during Summer 2018 and 2019. The overall mean perpendicular geometry (PRP) and horizontal coplanar geometry (HCP) ECa ranged between 1.8 to 18.0 and 3.1 to 25.8 mS m-1, respectively, and the overall mean HCP ECa was 67% greater than the mean PRP ECa. Largest measured ECa occurred within the local drainage way, which has mapped inclusions with aquic soil moisture regimes, or areas of potential groundwater movement, and smallest measured ECa values occurred within areas with decreased effective soil depth and increased coarse fragments. A positive (r2 = 0.4; P \u3c 0.05) linear relationship occurred over time between PRP ECa standard deviation, with a negative linear relationship (r2 = 0.93; P \u3c 0.05) between HCP ECa coefficient of variation across season (i.e., Summer to Spring). The K-means-clustering method was used to delineate three precision SMZs that were reflective of areas with similar ECa and ECa variability. Relationships between ECa and tree properties were generally stronger within the whole-site, averaged across tree property and ECa configuration (| r | = 0.38), than the SMZs, averaged across tree property, ECa configuration, and SMZ (| r | = 0.27). The strength of the SMZs’ terrain-attribute-PRP-ECa relationships were 9 to 205% greater than that for the whole-site. Whole-site, multi-linear regressions showed that Slope Length and Steepness (LS)-Factor (10.5%), Mid-slope (9.4%), and Valley Depth (7.2%) were terrain attributes that had the greatest influence (i.e., largest percent of total sum of squares) on PRP ECa variability, whereas Valley Depth (15.3%), Wetness Index (11.9%), and Mid-slope (11.2%) had the greatest influence on HCP ECa variability. Results of this study show how ECa varies and relates to soil, plant (i.e., DBH and TH and forage yield), and terrain attributes in AF systems with varying topography that could be used to influence AF management

Corn response to wastewater-recycled phosphorus fertilizers

The ability to recycle phosphorus (P) from wastewaters could provide a sustainable, continuous source of P that might also help protect surface water quality from P enrichment. The mineral struvite (MgNH4PO4 · 6H2O) is an understudied material that can be created from P- and nitrogen (N)-containing wastewater and has been shown to have agricultural fertilizer value. The objective of this study was to evaluate the effects of electrochemically precipitated struvite (ECST), chemically precipitated struvite (Crystal Green; CG), diammonium phosphate (DAP), monoammonium phosphate (MAP), rock phosphate (RP), and triple superphosphate (TSP) on corn (Zea mays) response in a greenhouse pot study. The effects of fertilizer treatment on select plant properties were evaluated. Corn plant properties and elemental tissue concentrations differed (P \u3c 0.05) among fertilizer amendments. Belowground dry matter from ECST was 1.9 times greater than that from CG, TSP, DAP, and the No P/+N, and No P/-N control treatments. Corn cob-plus-husk tissue P concentration from ECST was similar to that from MAP and DAP and was 1.2 times larger than that from CG. Corn stem-plus-leaves tissue P concentration from ECST differed from that from all other treatments and was 1.8 times greater than that from the No P/+N control. Results generated from this study not only provide information on the new, thus understudied, electrochemically precipitated struvite material, but also further demonstrate why more research should be conducted on the implementation of struvite as an alternative fertilizer-P source and struvite’s potential impact on sustainable food production and the preservation of water resources

Soil quality assessment of an agroforestry system following long-term management in the Ozark Highlands

The Soil Management Assessment Framework (SMAF) is a quantitative soil quality (SQ) evaluation tool that is widely applied to assess soil response to specific agricultural management practices over time. Considering the reported SQ benefits of agroforestry (AF) systems and the potential usefulness of SMAF, the objective of this study was to evaluate the effects of tree species (pecan [Carya illinoinensis (Wangenh.) K. Koch] and northern red oak [Quercus rubra L.]), soil fertility source (poultry litter [PL] and inorganic N fertilizer [control]), and soil depth (0–15 and 15–30 cm) on SMAF-derived SQ indices after 17 yr of management at an AF site in northwest Arkansas. Averaged across soil depth, soil organic C scores under red oak with PL application had a lower score (0.48) than red oak fertilized with inorganic N (0.60) and pecan receiving long-term PL applications (0.60), which did not differ from pecan with inorganic N fertilizer application (0.51). Averaged across soil depth, the soil quality index (SQI) for pecan receiving PL applications was 1.1 times greater than that under red oak receiving PL and soils under pecan receiving inorganic N fertilizer. Soil quality assessments use in AF are novel, as SMAF has not been used to identify soil health in these systems, although specific tree crop codes need to be developed in SMAF. Results of this study demonstrate that soils planted under various tree species respond dissimilarly to fertilizer sources and that management may improve overall SQ

Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands

Greater adoption and better management of spatially complex, conservation systems such as agroforestry (AF) are dependent on determining methods suitable for delineating in-field variability. However, no work has been conducted using repeated electromagnetic induction (EMI) or apparent electrical conductivity (ECa) surveys in AF systems within the Ozark Highlands of northwest Arkansas. As a result, objectives were to (i) evaluate spatiotemporal ECa variability; (ii) identify ECa-derived soil management zones (SMZs); (iii) establish correlations among ECa survey data and in situ, soil-sensor volumetric water content, sentential site soil-sample EC, and gravimetric water content and pH; and (iv) determine the optimum frequency at which ECa surveys could be conducted to capture temporal changes in field variability. Monthly ECa surveys were conducted between August 2020 and July 2021 at a 4.25 ha AF site in Fayetteville, Arkansas. The overall mean perpendicular geometry (PRP) and horizontal coplanar geometry (HCP) ECa ranged from 1.8 to 18.0 and 3.1 to 25.8 mS m−1, respectively, and the overall mean HCP ECa was 67% greater than the mean PRP ECa. The largest measured ECa values occurred within the local drainage way or areas of potential groundwater movement, and the smallest measured ECa values occurred within areas with decreased effective soil depth and increased coarse fragments. The PRP and HCP mean ECa, standard deviation (SD), and coefficient of variation (CV) were unaffected (p > 0.05) by either the weather or growing/non-growing season. K-means clustering delineated three precision SMZs that were reflective of areas with similar ECa and ECa variability. Results from this study provided valuable information regarding the application of ECa surveys to quantify small-scale changes in soil properties and delineate SMZs in highly variable AF systems

Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands

Abstract Minimal research has been conducted relating apparent electrical conductivity (ECa) surveys to plant and terrain properties in agroforestry systems. Objectives were to identify: (i) ECa–forage yield, –tree growth, and –terrain attribute relationships within ECa‐derived soil management zones (SMZs) and (ii) terrain attributes that drive ECa variability within a 20‐year‐old, 4.25‐ha, agroforestry system in the Ozark Highlands of northwest Arkansas. The average of 12 monthly perpendicular (PRP) and horizontal coplanar (HCP) ECa surveys (August 2020 to July 2021) and 14 terrain attributes were obtained. Tree diameter at breast height (DBH) and height (TH) measurements were made in December 2020 and March 2021, respectively, and forage yield samples were collected during Summer 2018 and 2019. Apparent EC‐tree property relationships were generally stronger within the whole site (averaged across tree property and ECa configuration, |r| = 0.38) than within the SMZs (averaged across tree property, ECa configuration, and SMZ, |r| = 0.27). The strength of the SMZs’ terrain‐attribute‐PRP‐ECa relationships were 9% to 205% greater than that for the whole site. In whole‐site, multi‐linear regressions, slope length and steepness factor (10.5%), mid‐slope (9.4%), and valley depth (7.2%) had the greatest influence (i.e., percent of total sum of squares) on PRP ECa variability, whereas valley depth (15.3%), wetness index (11.9%), and mid‐slope (11.2%) had the greatest influence on HCP ECa variability. Results show how ECa relates to plant (i.e., DBH, TH, and forage yield) and terrain data within SMZs in agroforestry systems with varying topography and could be used to precisely manage agroforestry systems