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Ngo, V.M
Swinton, S.M
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Authors
Ngo, V.M
Le-Khac, N
Kechadi, M
Lee, S
Swinton, S.M
Lee, S
Swinton, S.M
Topics
Big Data, Data Mining and Deep Learning
Data Analytics for Production Ag
Land Improvement and Conservation Practices
Type
Oral
Year
2018
2024
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Filter results3 paper(s) found.

1. An Efficient Data Warehouse for Crop Yield Prediction

Nowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi

2. Comparing Profitability of Variable Rate Nitrogen Prescription Methods

Variable rate nitrogen (VRN) prescriptions have been field-tested against uniform N application for over 25 years.  VRN prescription algorithms vary in the type and cost of information they require.  To date, few studies have compared the benefits and costs of alternative VRN prescription methods. VRN prescriptions draw on diverse information, including soil and tissue N sampling, yield history (YH), and remotely sensed spectral reflectance (such as the Normalized Difference... S. Lee, S.M. Swinton

3. Opportunity Cost of Precision Conservation

Crop production and biodiversity conservation vie for limited agricultural land resources. While biodiversity conservation benefits society as a whole, it is farmers who bear the immediate economic consequences of shifting land from agricultural to conservation use. When parts of a field are put into conservation use, farmers give up the net revenue that they earned from crop production, accepting the “opportunity cost” of losing that revenue stream.  But since crop yields are... S. Lee, S.M. Swinton