Topographic Position Index Predicts Within-Field Yield Variation in a Dryland Cereal Production System

Agricultural systems exhibit a large degree of within-field yield variability. We require a better understanding of the drivers of this variability in order to optimally manage croplands. We investigated drivers of sub-field spatial variability in yield for three crops (hard red winter wheat, Tritic...

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Veröffentlicht in:	Agronomy (Basel) Jg. 15; H. 6; S. 1304
Hauptverfasser:	Macdonald, Jacob A., Barnard, David M., Mankin, Kyle R., Miner, Grace L., Erskine, Robert H., Poss, David J., Mehan, Sushant, Mahood, Adam L., Mikha, Maysoon M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.06.2025
Schlagworte:	Agricultural land Agricultural production Arid zones Carbon content Crops Datasets dryland Farming systems Generalized linear models Hypotheses Machine learning Meteorological data Millet Nitrogen Precipitation Production data rainfed random forest Soil properties Soils spatial variability Topography Triticum aestivum Variability Wheat Winter wheat yield United States United States > US Colorado
ISSN:	2073-4395, 2073-4395
Online-Zugang:	Volltext
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