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    Bioethanol potential of switchgrass cultivars for rainfed and irrigated conditions in marginal lands
    (Taylor & Francis Ltd, 2023) Gonulal, Erdal; Hocaoglu, Onur
    Bioethanol is a climate-friendly alternative to conventional energy sources. This study was conducted to determine bioenergy potential of switchgrass cultivation in Central Anatolia where water scarcity limits the agricultural production. Field trials were conducted in a randomized blocks design with three replications under irrigated and rainfed conditions for three growing seasons (2019, 2020 and 2021). Biomass yield (BY), theoretical cellulosic ethanol yield (TEY), theoretical ethanol potential (TEP) with several quality parameters of 10 switchgrass cultivars were evaluated. Highest BY averages were obtained from Boomaster cultivar with 5.28 (rainfed) and 18.45 t ha-1 (irrigated) when Dacotah had the lowest BY averages of 1.55 (rainfed) and 5.29 t ha-1 (irrigated). ANOVA and Genotype Trait Biplot results revealed higher BY, TEY and TEP with lower ADF, NDF and ADL of lowland ecotype cultivars. Lowland ecotypes provided superior results in both rainfed and irrigated conditions with a higher response to irrigation. TEY of switchgrass were found as positively associated with BY, plant height and stem weight which could be used as indicators of TEY for genotype selection. In conclusion, lowland ecotype cultivars of switchgrass were recommended for bioethanol production in water limited environments.
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    Modelling the Effect of Irrigation Deficit on Maize Growth with Logistic Regression
    (Taylor & Francis Inc, 2023) Hocaoglu, Onur; Gonulal, Erdal; Akcura, Mevlut
    This research is conducted to model the limiting effects of irrigation deficit on maize growth which is a major challenge in dry areas. Field trials were conducted in completely randomized block design with three replications in Konya region (Turkey) during 2020 and 2021 growing seasons between May and August. Dry matter (DM) increase of maize was assessed on weekly intervals under four irrigation treatments, configured as %100, 75, 50 and 25 of the field capacity. Curve fitting with Logistic regression model demonstrated gradual decreases of maximum DM (from 496.331 to 254.119 g) and maximum growth rate (49,95 to 29,47 g/weeks) in average due to irrigation deficit when accurately modeling the DM accumulation with the varying R-2 values between 0.979 and 0.995. Results of logistic regression curves and IWUE suggested that even 25% restriction of irrigation water caused an average of %25.5 decrease on DM when 50% and more restriction could be associated with water stress. Additionally, irrigation water use efficiency (IWUE) was increased after the maximum acceleration point (MAP) which coincided with tasseling stage and inflection point (IP) where growth rate reaches to maximum, indicating that these periods were critical for maize in terms of preventing water deficiency.