Modelling the Effect of Irrigation Deficit on Maize Growth with Logistic Regression

• Published in: Communications in Soil Science and Plant Analysis 2023-05, Vol.54 (9), p.1293-1305
• Main Authors: Hocaoğlu, Onur, Gönülal, Erdal, Akçura, Mevlüt
• Format: Article
• Language: English
• Subjects: Corn; Curve fitting; Dry matter; Field capacity; Growing season; Growth rate; Irrigation; irrigation deficit; Irrigation effects; Irrigation efficiency; Irrigation water; Logistic regression; maize; rapid growth period; Regression analysis; Regression models; Water stress; Water use; Water use efficiency
• ISSN: 0010-3624; 1532-2416; 1532-4133
• DOI: 10.1080/00103624.2022.2142236

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.