Degree Type


Date of Award


Degree Name

Master of Science




Soil Science

First Advisor

Michael Castellano


Soil nitrate (NO3-) is one of the most important forms of nitrogen in in nature. It is an important plant nutrient, but it also easily lost to the environment where it can diminish air and water quality. However, the ability to measure soil NO3--is limited by manual sampling and laboratory analyses, and only low-resolution data can be obtained with conventional procedures. In this thesis, a new kind of instantaneous soil NO3--N sensor was used to measure soil NO3--N concentration both in the laboratory and in a continuous maize fertilizer nitrogen (N) rate trial during the 2019 maize growth season. First, agreement between status-quo salt-extraction based measurements and sensor measurements was assessed using linear regression models, Bland and Altman plots, and intraclass correlation coefficients (ICCs). All three quantitative comparisons demonstrated good agreement, especially at relatively high NO3--N concentrations that are relevant for fertilizer N management. Subsequently, using the validated sensors, temporal variability of soil nitrate and the effect of temporal soil sampling resolution were quantified in situ using 60 days of soil NO3--N measurements every 10 seconds. A new finding, made possible with the new sensors, was that there was no consistent within-day pattern in soil NO3--N concentration. Across-days, when soil solution NO3--N was dynamic and sampling frequency was >5 days, estimates of mean daily NO3--N concentration were >20% from the actual mean daily concentration. The underlying temporal variability can affect the efficiency of given sampling management, which means the soil NO3--N sensor can have a promising application in the future soil fertilizer management. In the future, research will be required to interpret sensor measurements and spatial variability of sensor measurements.


Copyright Owner

Yunjiao Zhu



File Format


File Size

39 pages