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Trang, T
Thornton, M
Liu, Z
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Authors
Liu, Z
Griffin, T
Kirkpatrick, T
Monfort, S
Samborski, S.M
Szatylowicz, J
Gnatowski, T
Leszczyńska, R
Thornton, M
Walsh, O
Zhang, Y
Hodeghatta, U.R
Dhiman, V
Barai, K
Trang, T
Topics
Spatial Variability in Crop, Soil and Natural Resources
On Farm Experimentation with Site-Specific Technologies
Data Analytics for Production Ag
Type
Poster
Oral
Year
2012
2022
2024
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Filter results3 paper(s) found.

1. Spatial Econometric Approaches to Develop Site-Specific Nematode Management Strategies in Cotton Production

Root-knot nematode infestations tend to be spatially clustered within agricultural... Z. Liu, T. Griffin, T. Kirkpatrick, S. Monfort

2. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield Estimators

Prediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that most... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh

3. Predicting Water Potentials of Wild Blueberries During Drought Treatment Using Hyperspectral Sensor and Machine Learning

Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using... Y. Zhang, U.R. Hodeghatta, V. Dhiman, K. Barai, T. Trang