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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publications at this Location

Publications at this Location

ARS scientists publish results of their research projects in many formats. Listed below are the publications from research projects conducted at this location.

Clicking on a publication title will take you to more information on the publication. Clicking on the reprint icon Repository URL will take you to the publication reprint.

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2025 Publications
(listed by order of acceptance date)

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Show All Publications || Peer Reviewed Journal Publications Only

Displaying 1 to 11 of 11 Records

Unmanned aerial vehicles (UAVs) for precision agriculture information gathering to advance crop monitoring and management
(Proceedings)
(27-Feb-25)
Performance of johnsongrass and switchgrass from seeds and rhizome fragments in a mature switchgrass stand
(Peer Reviewed Journal)
(27-Feb-25)
Changes in leaf economic trait relationships across a precipitation gradient are related to differential gene expression in a C4 perennial grass
(Peer Reviewed Journal)
(23-Feb-25)
Version 1.4.0 - pyfao56: FAO-56 evapotranspiration in Python Reprint Icon
(Peer Reviewed Journal)
(21-Feb-25)
Prediction and mapping of soil organic carbon stock via large datasets coupled with pedotransfer functions Reprint Icon
(Peer Reviewed Journal)
(19-Feb-25)
Inter-comparison of soybean models for the simulation of evapotranspiration in a humid continental climate Reprint Icon
(Peer Reviewed Journal)
(18-Feb-25)
Manure handling certification programs in manuresheds across the United States Reprint Icon
(Peer Reviewed Journal)
(18-Feb-25)
Johnsongrass: A grassland invader Reprint Icon
(Review Article)
(3-Feb-25)
Soil test phosphorus predicts field-level, but not sub-field level corn yield response
(Peer Reviewed Journal)
(25-Jan-25)
Digital mapping of agricultural soils texture of the Brazilian Cerrado biome Reprint Icon
(Peer Reviewed Journal)
(23-Jan-25)
Leveraging spectral neighborhood information for corn yield prediction with spatial-lagged machine learning modeling: Can neighborhood information outperform vegetation indices?
(Peer Reviewed Journal)
(20-Jan-25)