Agronomy and Horticulture, Department of

 

First Advisor

Dr. Martha Mamo

Second Advisor

Dr. Jerry Volesky

Date of this Version

12-2019

Comments

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 Professors Martha Mamo and Jerry Volesky. Lincoln, Nebraska: December, 2019

Copyright 2019, Amanda E. Shine

Abstract

Nutrient inputs from cattle dung are crucial drivers of nutrient cycling processes in grazed ecosystems. These inputs are important both spatially and temporally and are affected by variables such as grazing strategy, water location, and the nutritional profile of forage being grazed. Past research has attempted to map dung deposition patterns in order to more accurately estimate nutrient input, but the large spatial extent of a typical pasture and the tedious nature of identifying and mapping individual dung pats has prohibited the development of a time- and cost-effective methodology. The first objective of this research was to develop and validate a new method for the detection and mapping of dung using an unmanned aerial vehicle (UAV) and multispectral imagery. The second objective was to quantify change over time in water-extractable organic carbon (WEOC), water-extractable phosphorus (WEP), and water-extractable nitrogen (WEN) in naturally-deposited dung that ranged from one to twenty-four days old. In addition, pre-analysis dung storage methods (refrigeration vs. freezing) were evaluated for their impact on laboratory analyses results. Multispectral images of pastures were classified using object-based image analysis. Post-classification accuracy assessment showed an overall accuracy of 82.6% and a Kappa coefficient of 0.71. Most classification errors were attributable to the misclassification of dung as vegetation, especially in spectrally heterogeneous areas such as trampled vegetation. Limitations to the implementation of this method for identifying and mapping cattle dung at large scales include the high degree of geospatial accuracy required for successful classification, and the need for additional method validation in diverse grassland environments. Dung WEN concentrations ranged from 1.20 g kg-1 at three days of age, to a low of 0.252 g kg-1 at 24 days. The highest WEOC values were in day-old dung, 19.25 g kg-1, and lowest in 14-day-old dung, 2.86 g kg-1. WEOC and WEN both followed exponential decay patterns of loss as dung aged. WEP was lowest at 1.28 g kg-1 (day one) and highest at 12 days (3.24 g kg-1), and dry matter and WEOC concentration were stronger determinants of WEP than age alone. Freezing consistently increased WEN and WEOC concentrations over fresh values, but WEP was inconsistent across ages in its response. This research provides new insight into dung nutrient dynamics and presents a novel method for studying them across large spatial and temporal scales.

Advisors: Martha Mamo and Jerry Volesky

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