Effect of irrigation technology and plant density on cotton growth, yield, yield components, and water use efficiency

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dc.contributor.author Koudahe, Komlan
dc.date.accessioned 2022-11-09T21:35:24Z
dc.date.available 2022-11-09T21:35:24Z
dc.identifier.uri https://hdl.handle.net/2097/42826
dc.description.abstract Limited water resources and insufficiently developed infrastructure provide challenges to sustainable production of cotton (Gossypium hirsutum L.) in Western Kansas. This study aimed to (i) assess the effect of irrigation technology and plant density on cotton growth, yield, and yield components, and (ii) determine the actual evapotranspiration, water use efficiency, and grass-reference crop coefficients of cotton under different irrigation technologies and rainfed conditions. Four irrigation technologies, which were Low Energy Precision Application (LEPA), Low Elevation Spray Application (LESA), Mobile Drip Irrigation 1 (MDI1 with 3.79 L/hour), Mobile Drip Irrigation 2 (MDI2 with 7.57 L/hour), and rainfed treatments were evaluated under two crop densities (135,908 and 160,618 plants/ha) in a split plot design with three replications using cotton variety PHY 205 W3FE in 2021. The results indicated that the MDI2 had the highest growth characteristics, such as plant height, leaf area index (LAI), and canopy cover, while the rainfed treatment registered the lowest growth performance. There is a significant positive relationship (p<0.05) between the canopy cover and LAI with coefficient of determination (R2) of 0.98, between NDVI and LAI (R2 of 0.92), and between the plant height and LAI (R2 of 0.87). Likewise, the R2 of the yield and the maximum growth characteristics were high (0.59-0.72) indicating that the variability of the yield could be explained by the variability of the crop growth parameters at flowering and early boll development stage. The cotton lint yield varied and was statistically significant (p<0.05) between the irrigation technologies and rainfed condition with the LEPA having the highest cotton lint yield (950.3 kg ha-1). The low-density provided the optimum cotton lint yield. The soil water balance analysis showed that, of all irrigation technologies, cotton under MDI1 had the highest actual evapotranspiration (ETa) of 490.3 mm, while the rainfed treatments had the lowest ETa of 287.1 mm. In terms of the impact of crop density, high-density plots registered a higher ETa of 447.1 mm compared to 441.3 mm of low-density plots. The LEPA irrigation technologies resulted in the highest crop water use efficiency (CWUE), actual evapotranspiration water use efficiency (ETWUE), and irrigation water use efficiency (IWUE), and the values were 0.30 kg m-3, 21 kg m-3, and 0.44 kg m-3, respectively. Irrigated cotton crop coefficients were estimated at 0.35, 0.92 to 1.04, and 0.39 to 0.48 for initial, mid, and late season stages, respectively. Under rainfed conditions, the crop coefficients were 0.18, 0.46 to 0.48, and 0.10 to 0.28 for the respective growth stages. These results indicate that the irrigated initial Kc is similar to the Food and Agriculture Organization of the United Nations (FAO) initial Kc, while mid and late season Kc are lower than the FAO values by 15% and 4%, respectively. On average, the two-step approach (ETa = ETo x Kc.adj.) overestimated cotton ETa by approximately 30% for irrigated fields and 118% for the rainfed condition compared to the water balance approach. This study shows that the development of a site-specific, local cotton Kc is important for better understanding of irrigation management strategies and crop water use in Western Kansas. en_US
dc.language.iso en_US en_US
dc.subject Actual evapotranspiration en_US
dc.subject Cotton en_US
dc.subject Crop coefficient en_US
dc.subject Irrigation en_US
dc.title Effect of irrigation technology and plant density on cotton growth, yield, yield components, and water use efficiency en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Biological & Agricultural Engineering en_US
dc.description.advisor Jonathan P Aguilar en_US
dc.description.advisor Aleksey Y Sheshukov en_US
dc.date.published 2022 en_US
dc.date.graduationmonth December en_US

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