Browsing by Author "Fornah, Alimamy"

Now showing 1 - 4 of 4
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    Effect of Spacing, Planting Methods and Nitrogen on Maize Grain Yield
    (Communications in Soil Science and Plant Analysis, 2020) Fornah, Alimamy; Aula, Lawrence; Omara, Peter; Oyebiyi, Fikayo; Dhillon, Jagmandeep; Raun, William R.
    Maize (Zea mays L.) production in the developing countries takes place on marginal landscapes using indigenous planting methods that conflict with appropriate row spacing (RS) and plant to plant spacing (PPS). A study was conducted to determine the effect of different RS, variable plant densities and different planting methods on maize grain yield. This study was conducted for two years at three locations in Oklahoma including Lake Carl Blackwell (Port silt loam), Efaw (Ashport silty clay loam), and Perkins (Teller sandy loam-fine-loamy). Fourteen treatments were evaluated at each location in a randomized complete block design with three replications. Treatments included two RS (0.51 m, 0.76 m), three nitrogen (N) application rates (0, 60, 120 kg N ha−1), two PPS (0.15 m, 0.30 m) and two planting methods (Greenseeder hand planter; farmers practice). Results showed an increase in grain yield by 34% in 2017 and 44% in 2018 for the narrow RS of 0.51 m compared to the 0.76 m RS. This was likely due to increased plant population at the narrow RS. This study suggests that maize producers in developing countries could use narrow RS (0.51 m) with wide PPS (0.30 m) to increase grain yields.
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    Improving winter wheat grain yield and nitrogen use efficiency using nitrogen application time and rate
    (Agrosystems, Geosciences & Environment, 2021) Aula, Lawrence; Omara, Peter; Oyebiyi, Fikayo B.; Eickhoff, Elizabeth; Carpenter, Jonathan; Nambi, Eva; Fornah, Alimamy; Raun, William R.
    Preplant nitrogen (N) application, which involves placing nutrients in the soil before seeding, has been an integral part of crop production systems for decades. Some producers are known to apply N at least 21 d before planting. This may increase N loss and lower grain yield. This study evaluated the effect of timing and rate of N application on winter wheat (Triticum aestivum L.) grain yield and N use efficiency (NUE). An experiment with a factorial arrangement of treatments was set up in a randomized complete block design with three replications. Treatments included four N rates (0, 45, 90, and 135 kg ha–1) with each applied 7 or 30 d before planting, and at Feekes 5 (FK5). Grain N was analyzed using LECO CN dry combustion analyzer. The difference method [Grain N from (fertilized plot – check plot)]/N applied was used to compute NUE. Nitrogen application rate significantly affected grain yield (P ≤ .01). Although the rate may be temporally and spatially variable, approximately 90 kg N ha–1 was required to obtain yields that differ markedly from the check. Midseason applied N (FK5) had similar yields to preplant applied N in two of four siteyears and significantly increased yield at one site in 2020. Out of two sites, the timing of N application had a substantial effect on NUE in both years (P ≤ 0.11). In this case, NUE was increased by as much as 9.5% for midseason applied N compared to 30 d before planting N application time.
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    Unpredictable Nature of Environment on Nitrogen Supply and Demand
    (Agronomy Journal, 2019) Raun, William R.; Dhillon, Jagmandeep; Aula, Lawrence; Eickhoff, Elizabeth; Weymeyer, Gwen; Figueirdeo, Bruno; Lynch, Tyler; Omara, Peter; Nambi, Eva; Oyebiyi, Fikayo; Fornah, Alimamy
    The second law of thermodynamics states that entropy or randomness in a given system will increase with time. This is shown in science, where more and more biological processes have been found to be independent. Contemporary work has delineated the independence of yield potential (YP0) and nitrogen (N) response in cereal crop production. Each year, residual N in the soil following crop harvest is different. Yield levels change radically from year to year, a product of an ever-changing and unpredictable/ random environment. The contribution of residual soil N for next years’ growing crop randomly influences N response or the response index (RI). Consistent with the second law of thermodynamics, where it is understood that entropy increases with time and is irreversible, biological systems are expected to become increasingly random with time. Consequently, a range of different biological parameters will influence YP0 and RI in an unrelated manner. The unpredictable nature that environment has on N demand, and the unpredictable nature that environment has on final grain yield, dictate the need for independent estimation of multiple random variables that will be used in mid-season biological algorithms of the future.
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    Variability in Winter Wheat (Triticum aestivum L.) Grain Yield Response to Nitrogen Fertilization in Long-Term Experiments
    (Communications in Soil Science and Plant Analysis, 2020) Omara, Peter; Aula, Lawrence; Dhillon, Jagmandeep S.; Oyebiyi, Fikayo; Eickhoff, Elizabeth M.; Nambi, Eva; Fornah, Alimamy; Carpenter, Jonathan; Raun, William
    Crop nitrogen (N) use is always affected by the variability in production environment. Dataset (2001 to 2014) from long-term winter wheat (Triticum aestivum L.) experiments at Lahoma and Stillwater, Oklahoma was used. Both experiments have a randomized complete block design with four replications, and fertilizer N was applied as urea pre-plant. Responsiveness of grain yield to maximum fertilizer N rate (112 kg ha−1 – Lahoma; 135 kg ha−1 – Stillwater) was compared with that from check plot (0 kg ha−1). The objective was to determine the relative influence of environment, management, and variety on winter wheat grain yield. The combined analysis of variance indicated that the main effect of year, treatment, location, and variety accounted for 29.3%, 21.2%, 3.1%, and 22.6%, respectively of the variance terms. Over the study period, the nonresponsiveness of winter wheat to fertilizer N accounted for 29% and 23% of grain yield at Lahoma and Stillwater, respectively where yield at maximum N rate did not significantly differ from check plot. This highlights the importance of random changes in a crop production environment and its influence in dictating the response to applied N fertilizer. Nitrogen fertilizer losses could be reduced by adopting in-season variable N application techniques.