Nutifafa Adotey

Dr. Nutifafa Adotey

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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1 September 2022 in European Journal of Soil Science
Verified
Journal Article
Closed access
Dinesh PandayDinesh Panday
Dinesh Panday
DSDebasish Saha
Debasish Saha
JLJaehoon Lee
Jaehoon Lee
SJSindhu Jagadamma
Sindhu Jagadamma
NANutifafa Adotey
Nutifafa Adotey
AMAlemu Mengistu
Alemu Mengistu

28 March 2025 in Agrosystems, Geosciences & Environment
Verified
Journal Article
Open access
AAAziz Ahmed
Aziz Ahmed
JWJim Wang
Jim Wang
MKManoch Kongchum
Manoch Kongchum
DHDustin L. Harrell
Dustin L. Harrell
NANutifafa Adotey
Nutifafa Adotey
CHANGYOON JEONGCHANGYOON JEONG
CHANGYOON JEONG
Conventional delayed‐flood rice (Oryza sativa L.; DFR) cultivation in United States faces increasing challenges such as nutrient losses, water scarcity, and greenhouse gas emissions. Alternative furrow‐irrigated rice (FIR) cultivation is gaining interest for its water use efficiency and production flexibility. Despite FIR's growing adoption, its impacts on soil biological functioning and nutrient cycling remain poorly understood, limiting the ability to optimize management practices for this emerging system. Understanding these impacts is crucial as soil health directly influences nutrient availability, crop productivity, and long‐term sustainability. This study aimed to compare soil enzyme activities and other health indicators between DFR and FIR systems. Soil samples were collected from Louisiana DFR and FIR field experiments established in 2020 and 2021 and analyzed for β‐glucosidase (BG), β‐glucosaminidase (NAG), phosphomonoesterase (PME), arylsulfatase (AST), permanganate oxidizable carbon (POXC), respiration (CO2‐burst), and alkali‐hydrolysable nitrogen (AHN). Principal component analysis (PCA) revealed distinct separations between the DFR and FIR systems in different sites. The results showed that the FIR system significantly (p < 0.05) increased NAG by 35%–57% and AST by 35%–113% activities at both sites as well as BG by 35% and PME by 92% at one of the two site‐years over the DFR system, indicating improved nutrient cycling. The FIR also had significantly (p < 0.05) higher CO2‐burst by 21%–33% and POXC by 44% at one of the two sites than the DFR. Rice grain yields were significantly and positively related to BG (R2 = 0.28, p < 0.05) and PME (R2 = 0.18, p < 0.05) in the FIR system across site‐years but not in the DFR system, reflecting different sensitivities of these enzymes to the two rice cultivations. This study provides insights into understanding the difference in nutrient cycling between the two rice production systems.

27 November 2024 in Agronomy
Verified
Journal Article
Open access
PDF file
NANutifafa Adotey
Nutifafa Adotey
AMAngela T. McClure
Angela T. McClure
XYXinhua Yin
Xinhua Yin
JMJake McNeal
Jake McNeal
ADAndrew B Denton
Andrew B Denton
Enhanced efficiency nitrogen fertilizer (EENF) is a viable N management tool that can minimize N loss and maximize crop productivity. Research on the efficiency of EENF under relatively newer N-sidedress placement methods for liquid fertilizers, such as Y-Drop dribble, is limited, hence the necessity to address this knowledge gap. A two-year field trial was conducted to evaluate ammonia volatilization, grain quality, and grain yield from surface-applied EENF forms of urea and EENF forms of urea ammonium nitrate (UAN) applied under four placement methods in a rainfed no-till corn production system. The EENF forms of urea evaluated in this trial included Environmentally Smart Nitrogen, SuperU, and ANVOL-treated urea, while ANVOL-treated UAN was the EENF form of UAN. All the urea fertilizers were surface broadcasted while the UAN fertilizers were broadcasted, dribbled in between rows, Y-Drop dribbled, and injected behind colters. Among the non-EENF, urea volatilized the most ammonia (23.1% of total N applied) compared to UAN. Broadcast UAN was much more susceptible to ammonia volatilization than dribbled UAN in between rows. In this trial, the EENF forms of urea and UAN reduced ammonia loss by 65 to 94 and 50 to 51%, respectively, compared to their corresponding non-EENF forms. In 2021, the grain yield of the non-EENF forms of UAN was similar to the EENF forms of the corresponding placement methods. In contrast, there was an additive yield effect from all the urea forms of EENF. A significant negative relationship was observed between ammonia loss and grain protein, grain N, and grain yield; hence, placement methods with higher ammonia loss potential are prone to yield loss.

16 July 2025 in Soil Systems
Verified
Journal Article
Open access
PDF file
SOSamuel Kudzo Okai
Samuel Kudzo Okai
XYXinhua Yin
Xinhua Yin
LDLori Duncan
Lori Duncan
DYDaniel Yoder
Daniel Yoder
DSDebasish Saha
Debasish Saha
NANutifafa Adotey
Nutifafa Adotey
There are discrepancies regarding the effectiveness of enhanced efficiency nitrogen (N) fertilizer (EENF) products on ammonia loss from unincorporated, surface applications of urea-based fertilizers. Soil properties and management practices may account for the differences in the performance of EENF. However, few studies have investigated the performance of urea- and urea ammonium nitrate (UAN)-based EENF on soils with contrasting properties. Controlled-environment incubation experiments were conducted on two soils with different properties to evaluate the efficacy of urea and UAN forms of EENF to minimize ammonia volatilization losses. The experiments were set up as a completely randomized design, with seven treatments replicated four times for 16 days. The N treatments, which were surface-applied at 134 kg N ha−1, included untreated urea, untreated UAN, urea+ANVOLTM (urease inhibitor product), UAN+ANVOLTM, environmentally smart nitrogen (ESN®), SUPERU® (urease and nitrification inhibitor product), and urea+Excelis® (urease and nitrification inhibitor product). In this study, urea was more susceptible to ammonia loss (24.12 and 26.49% of applied N) than UAN (5.24 and 16.17% of applied N), with lower ammonia volatility from soil with a pH of 5.8 when compared to 7.0. Urea-based EENF products performed better in soil with a pH of 5.8 compared to the soil with pH 7.0, except for ESN, which was not influenced by pH. In contrast, the UAN-based EENF was more effective in the high-pH soil (7.0). Across both soils, all EENFs reduced cumulative ammonia loss by 32–91% in urea and 27–70% in UAN, respectively, when compared to their untreated forms. The urea-based EENF formulations containing both nitrification and urease inhibitors were the least effective among the EENF types, performing particularly poorly in high-pH soil (pH 7.0). In conclusion, the efficacy of EENF is dependent on soil pH, N source, and the form of EENF. These findings underscore the importance of tailoring EENF applications to specific soil conditions and N sources to optimize N use efficiency (NUE), enhance economic returns for producers, and minimize environmental impacts.

17 December 2025 in Agrosystems, Geosciences & Environment
Verified
Journal Article
Open access
SOSamuel Okai
Samuel Okai
SLSydney Logwood
Sydney Logwood
LDLori Duncan
Lori Duncan
DYDaniel Yoder
Daniel Yoder
DSDebasish Saha
Debasish Saha
NANutifafa Adotey
Nutifafa Adotey
The composition and breakdown paths of urea ammonium nitrate (UAN) and urea are different, but there is limited information on how soil properties relate to ammonia volatilization loss from surface‐applied, unincorporated UAN and urea on various soils. Controlled environment incubation experiments were conducted to evaluate ammonia volatilization potential of commonly used urea‐containing fertilizers, and to correlate these losses to selected soil properties. A completely randomized design with four replicates was used to evaluate and correlate ammonia loss from urea and UAN applied onto eight soils at a rate of 134 kg N ha −1 . Urea was more susceptible to ammonia loss (21% of applied N) than UAN (3.3% of applied N) in soils with pH < 7. In contrast, the losses from UAN were either higher or comparable to urea for soils with pH > 7. A significant and strong relationship was evident between ammonia loss from UAN and soil pH ( R 2 = 0.84), soil organic matter ( R 2 = 0.65), clay content ( R 2 = 0.69), and container capacity ( R 2 = 0.90). In contrast, the loss relationships observed for the urea and these properties were insignificant. Stepwise regression analysis identified clay content and soil pH as the most influential factors affecting ammonia loss from both urea and UAN applications. In conclusion, high initial soil pH significantly increases ammonia loss for surface‐applied UAN but not for urea, suggesting that different soil management strategies may be needed depending on the N fertilizer source used.