Master of Science / Department of Agronomy / Antonio R. Asebedo / Current population trends project that current agricultural production will need to increase by 110% by the year 2050 to support the growing worldwide population. Many agriculturalists are looking at precision agriculture technology to help achieve this production increase. One technology that is being heavily researched is the integration of small unmanned aerial systems (sUAS) and their sensors into the agricultural sector. Much research has already been conducted in the agronomic sector utilizing sUAS. However, relatively few advancements involving sUAS have been made in the animal science industry. This thesis focuses on how sUAS can be incorporated into a diverse cropping and livestock operation. Chapter 1 - Evaluating Current Capabilities of sUAS and sUAS Mounted Sensors in Diverse Agricultural Operation: A Literature Review, focuses on the current capabilities of sUAS and explains how they are incorporated into cropping systems and livestock production. Chapter 2 - Wheat Variety Interaction on Multispectral Based Vegetative Indices, focuses on wheat variety interaction with yield, grain protein content, NDVI, NDRE and CCCI. Ten wheat varieties were tested in large plot studies; yield, protein and multispectral data were collected for Feekes 4, 7, 10 and 10.5. Wheat variety was statically significant across all vegetative indices, protein and yield during less than favorable growing conditions. Chapter 3 - Estimating Cattle Rectal Temperature Using Thermography, focuses on determining the ideal location for thermographic readings to be taken to predict rectal temperature of beef cattle. To establish if sUAS-based thermography could be utilized for cattle rectal temperature estimation, 35 crossbreed steers were selected and thermographic readings and rectal temperature data were collected and analyzed for correlation. This study found stronger relation in the animal’s eye than other facial features.