Graduate Studies


First Advisor

Cody Creech

Second Advisor

Amanda Easterly

Third Advisor

Katherine Frels

Date of this Version

Winter 12-2-2022


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agronomy, Under the Supervision of Professor Cody F. Creech. Lincoln, Nebraska: November 2022

Copyright © 2022 Maria Carolina Melo Sciencia


Winter wheat is one of the most important crops in the world, and the improvement of genetic lines in combination with optimum planting conditions and production practices optimizes its yield. To achieve the high demand for food protein, there is value in estimating wheat yield during the growing season. Furthermore, to optimize inputs and set reasonable harvest expectations to guide marketing decisions, agronomic practices and yield prediction assessment testing in dryland areas are needed. Experiments were conducted in western Nebraska to evaluate yield prediction, row spacing, and seeding rate effects in winter wheat. Different combinations of seeding rate and row spacing were tested to determine winter wheat yield components, soil water content during the growing seasons, and subsequent grain yield. In addition, the Winter Wheat State Variety Trial in five locations in western Nebraska was evaluated to test yield prediction methods, such as stand count, tiller count, Normalized Difference Vegetation Index, and Fractional Green Canopy Cover. Regarding the row spacing and seeding rate experiment, the best treatment combined the 19 cm row spacing and 3.1 million seed ha-1 seeding rate, which were the narrowest row spacing and the highest seeding rate of this experiment. Furthermore, narrower row spacings reveal a greater water use efficiency in drier years if compared with wider row spacings. The wheat yield prediction methods experiment exhibits NDVI and FGCC as likely methods that could be used to replace the stand and tiller count approaches. Moreover, FGCC at Feekes 2, 4, and 10 of wheat growth has potential to predict yield during the growing season, with prediction accuracies higher than 0.55.

Advisor: Cody F. Creech