Tyler J. Nigon

Tyler J. Nigon
University of Minnesota Twin Cities | UMN · Soil, Water, and Climate

PhD & MS - Land and Atmospheric Science; BS - Soil and Land Management

About

10
Publications
3,574
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223
Citations
Introduction
My research focuses on evaluating remote sensing and other precision agriculture tools as a means to reduce fertilizer loss and keep our soil and water resources clean and productive.

Publications

Publications (10)
Article
Full-text available
A meticulous image processing workflow is oftentimes required to derive quality image data from high-resolution, unmanned aerial systems. There are many subjective decisions to be made during image processing, but the effects of those decisions on prediction model accuracy have never been reported. This study introduced a framework for quantifying...
Article
Corn is an important food crop in the world, widely distributed in many countries because of its excellent environmental adaptability. Moreover, corn is an important feed source for animal production and it is an indispensable raw material for many different industries. With increasing human population and decreasing arable land, there is an increa...
Article
Full-text available
The ability to predict spatially explicit nitrogen uptake (NUP) in maize (Zea mays L) during the early development stages provides clear value for making in-season nitrogen fertilizer applications that can improve NUP efficiency and reduce the risk of nitrogen loss to the environment. Aerial hyperspectral imaging is an attractive agronomic research...
Article
A Python package, “EONR”, was developed for computing the economic optimum nitrogen rate (EONR) and its profile-likelihood confidence intervals (CIs) under economic conditions defined by the user. This work was motivated by the need to improve nitrogen fertilizer recommendations using the maximum return to nitrogen approach, specifically to make it...
Conference Paper
Full-text available
Corn nitrogen recommendations for individual fields must improve to minimize the negative influence that agriculture has on the environment and society. Two adaptive N management approaches for making in-season N fertilizer recommendations are remote sensing and crop systems modeling. Remote sensing has the advantage of characterizing the spatial v...
Presentation
Full-text available
Assessing the impact of nitrogen [N] and irrigation [IRR] best management practices [BMPs] on nitrate leaching loads is difficult to directly measure. One strategy commonly used by researchers in sandy soils is to install suction cup lysimeters below the root zone to sample the soil solution. However, making comparisons between treatments is diffic...
Article
Full-text available
The present study focuses on (i) evaluation of potato crop yield under present time slice (PTS) with recommended management of nitrogen (N) fertilizer and irrigation on sandy soils of Minnesota, USA (ii) simulation of potato productivity and nitrate leaching with the SUBSTOR DSSAT-potato model in a projected future climatic environment (2038–2067)...
Article
Full-text available
Potato yield and quality are highly dependent on an adequate supply of water. In this study, 3 years of information from thermal and RGB images were collected to evaluate water status in potato fields. Irrigation experiments were conducted in commercial potato fields (Desiree; drippers). Two water-deficit scenarios were tested: a short-term water d...
Article
Full-text available
The nitrogen sufficiency index (NSI) can be used for in-season variable rate management of nitrogen (N) fertilizer to maintain productivity of potato (Solanum tuberosum, L.) while reducing leaching losses. The objective of this study was to evaluate the implications of using high spatial resolution broad-band imagery for determining N prescriptions...

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