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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Research Project #445467

Research Project: Enhancing Cropping System and Grassland Sustainability in the Texas Gulf Coast Region by Managing Systems for Productivity and Resilience

Location: Grassland Soil and Water Research Laboratory

Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)

Laboratory root processing and scanning for grasslands and forages Reprint Icon - (Other)
Grisham, C., Rowley, D.W., Schantz, M.C. 2025. Laboratory root processing and scanning for grasslands and forages. Protocols.io. https://dx.doi.org/10.17504/protocols.io.261ge8zxwg47/v1.

From field to analysis: Strengthening reproducibility and confirmation in research for sustainable agriculture Reprint Icon - (Peer Reviewed Journal)
White, J.W., Boote, K.J., Kimball, B.A., Porter, C., Salmeron, M., Shelia, V., Thorp, K.R., Hoogenboom, G. 2025. From field to analysis: Strengthening reproducibility and confirmation in research for sustainable agriculture. Sustainable Agriculture. 3(27). https://doi.org/10.1038/s44264-025-00067-z.

Performance of johnsongrass and switchgrass from seeds and rhizome fragments in a mature switchgrass stand Reprint Icon - (Peer Reviewed Journal)
Schwinning, S., Fay, P.A., Polley, H. 2025. Performance of johnsongrass and switchgrass from seeds and rhizome fragments in a mature switchgrass stand. Plant Ecology. https://doi.org/10.1007/s11258-025-01505-1.

Changes in leaf economic trait relationships across a precipitation gradient are related to differential gene expression in a C4 perennial grass Reprint Icon - (Peer Reviewed Journal)
Heckman, R.A., Aspinwall, M.J., Taylor, S.H., Lowry, D.B., Khasanova, A., Bonnette, J.E., Razzaque, S., Fay, P.A., Juenger, T.E. 2025. Changes in leaf economic trait relationships across a precipitation gradient are related to differential gene expression in a C4 perennial grass. New Phytologist. https://doi.org/10.1111/nph.70089.

Version 1.4.0 - pyfao56: FAO-56 evapotranspiration in Python Reprint Icon - (Peer Reviewed Journal)
Thorp, K.R., Gulati, D., Kukal, M., Ames, R.B., Pokoski, T.C., DeJonge, K.C. 2025. Version 1.4.0 - pyfao56: FAO-56 evapotranspiration in Python. SoftwareX. 30:102109. https://doi.org/10.1016/j.softx.2025.102109.

Prediction and mapping of soil organic carbon stock via large datasets coupled with pedotransfer functions Reprint Icon - (Peer Reviewed Journal)
Dharumarajan, S., Adhikari, K., Chakraborty, R., Kalaiselvi, B., Vasundhara, R., Lalitha, M., Hegde, R., Prakash, H., Parvathy, S., Rajesh, R.L. 2025. Prediction and mapping of soil organic carbon stock via large datasets coupled with pedotransfer functions. Earth Science Informatics. 18:314. https://doi.org/10.1007/s12145-025-01822-z.

Manure handling certification programs in manuresheds across the United States Reprint Icon - (Peer Reviewed Journal)
Flynn, K.C., Erb, K., Meinen, R.J., Krecker-Yost, J.L., Inaoka, M., Spiegal, S.A. 2025. Manure handling certification programs in manuresheds across the United States. Cleaner Waste Systems. 10. Article 100241. https://doi.org/10.1016/j.clwas.2025.100241.

Johnsongrass: A grassland invader Reprint Icon - (Review Article)
Schantz, M.C. 2025. Johnsongrass: A grassland invader. Weed Science. https://doi.org/10.1017/wsc.2025.7.

Advancements in remote sensing techniques for earthquake engineering: A review Reprint Icon - (Review Article)
Hassan Krishmurthy, C., Flynn, K.C., Ashworth, A.J. 2025. Advancements in remote sensing techniques for earthquake engineering: A review. Earthquake Research Advances. https://doi.org/10.1016/j.eqrea.2024.100352.

Mechanistic insights into plant community responses to environmental variables: genome size, cellular nutrient investments, and metabolic trade-offs - (Peer Reviewed Journal)
Hersch-Green, E.I., Petosky, H., Smith, N.G., Fay, P.A. 2024. Mechanistic insights into plant community responses to environmental variables: genome size, cellular nutrient investments, and metabolic trade-offs. New Phytologist. https://doi.org/10.1111/nph.20374.

Enhancing LAI estimation using multispectral imagery and machine learning: a comparison between reflectance-based and vegetation indices-based approaches Reprint Icon - (Peer Reviewed Journal)
Chatterjee, S., Baath, G.S., Sapkota, B., Flynn, K.C., Smith, D.R. 2024. Enhancing LAI estimation using multispectral imagery and machine learning: a comparison between reflectance-based and vegetation indices-based approaches. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2024.109790.

Simulating sagebrush-cheatgrass plant community Biomass production in the Great Basin using ALMANAC Reprint Icon - (Peer Reviewed Journal)
Schantz, M.C., Kiniry, J.R., Williams, A.S., Thorp, K.R., Hardegree, S.P., Newingham, B.A., Williams, C.J., Davies, K.W., Sheley, R.L. 2024. Simulating sagebrush-cheatgrass plant community Biomass production in the Great Basin using ALMANAC. Ecosphere. https://doi.org/10.1002/csc2.21440.

Phenotyping cotton leaf chlorophyll via in situ hyperspectral reflectance sensing, spectral vegetation indices, and machine learning Reprint Icon - (Peer Reviewed Journal)
Thorp, K.R., Thompson, A.L., Herritt, M.T. 2024. Phenotyping cotton leaf chlorophyll via in situ hyperspectral reflectance sensing, spectral vegetation indices, and machine learning. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2024.1495593.

vegspec: A compilation of spectral vegetation indices and transformations in Python Reprint Icon - (Peer Reviewed Journal)
Thorp, K.R. 2024. vegspec: A compilation of spectral vegetation indices and transformations in Python. SoftwareX. https://doi.org/10.1016/j.softx.2024.101928.

LiDAR-based estimation of corn (Zea Mays L.) plant height and leaf area index across multiple planting dates - (Abstract Only)

Greenhouse gas emissions from corn fields as influenced by cover crop management - (Abstract Only)

A meta-analysis to understand the combined effect of cover cropping and nitrogen fertilization on corn yield in the U.S. - (Abstract Only)

Enhancing leaf area index estimation with multispectral imagery and machine learning - (Abstract Only)

Early seedling counts: Enhancing producer confidence - (Abstract Only)

Optimizing corn yield through strategic nitrogen application - (Abstract Only)

From reflectance to yield: Understanding corn production metrics - (Abstract Only)

When soil carbon isn’t everything: Impact of regenerative practices on soil health metrics in the semi-arid west - (Abstract Only)

Corn yield response and water use efficiency following cover crop management in rainfed corn production system - (Abstract Only)

Advancements in remote sensing techniques for earthquake engineering: A review Reprint Icon - (Peer Reviewed Journal)
Macdougall, A., Esch, E., Chen, Q., Carroll, O., Bonner, C., Ohlert, T., Siewart, M., Sulik, J., Schweiger, A., Borer, E., Naidu, D., Bagchi, S., Hautier, Y., Wilfahrt, P., Larson, K., Olofsson, J., Cleland, E., Muthukrishnan, R., O'Halloran, L., Alberti, J., Anderson, T., Arnillas, C.A., Bakker, J.D., Barrio, I.C., Biederman, L., Boughton, E.H., Brudvig, L., Bruschetti, M., Buckley, Y., Bugalho, M.N., Cadotte, M.W., Caldeira, M.C., Catford, J.A., D'Antonio, C., Davies, K., Daleo, P., Dickman, C.R., Donohue, I., Dupre, M., Elgersma, K., Eisenhauer, N., Eskelinen, A., Estrada, C., Fay, P.A., Feng, Y., Gruner, D.S., Hagenah, N., Haider, S., Harpole, S., Hersch-Green, E., Jentsch, A., Kirkman, K., Knops, J.M., Laanisto, L., Lannes, L.S., Laungani, R., Lkhagva, A., Macek, P., Martina, J.P., Mcculley, R.L., Melbourne, B., Mitchell, R., Moore, J.L., Morgan, J.W., Niu, Y.O., Partel, M., Peri, P.L., Power, S.A., Price, J.N., Prober, S.M., Ren, Z., Risch, A.C., Smith, N., Sonnier, G., Standish, R.J., Stevens, C.J., Tedder, M., Tognetti, P., Veen, C.G., Virtanen, R., Wardle, G.M., Waring, E., Wolf, A.A., Yahdjian, L., Seabloom, E. 2024. Advancements in remote sensing techniques for earthquake engineering: A review. Earthquake Research Advances. https://doi.org/10.1038/s41559-024-02500-x.

The LTAR cropland common experiment at the Texas Gulf Reprint Icon - (Peer Reviewed Journal)
Yost, J.L., Smith, D.R., Adhikari, K., Arnold, J.G., Collins, H.P., Flynn, K.C., Hajda, C.B., Menefee, D.S., Mohanty, B.P., Schantz, M.C., Thorp, K.R., White, M.J. 2024. The LTAR cropland common experiment at the Texas Gulf. Journal of Environmental Quality. https://doi.org/10.1002/jeq2.20592.

Evaluating the role of alternative grazing strategies on plant production and soil health across a decade timescale - (Abstract Only)

The LTAR-integrated grazing land common experiment at the Texas Gulf Reprint Icon - (Peer Reviewed Journal)
Schantz, M.C., Smith, D.R., Harmel, R.D., Goodwin, D.J., Tolleson, D.R., Osorio Leyton, J.M., Flynn, K.C., Krecker-Yost, J.L., Thorp, K.R., Arnold, J.G., White, M.J., Adhikari, K., Hajda, C.B. 2024. The LTAR-integrated grazing land common experiment at the Texas Gulf. Journal of Environmental Quality. https://doi.org/10.1002/jeq2.20573.

Evaluating the role of grazing strategies on plant production and soil health across a decade timescale - (Abstract Only)

Version 1.3.0 - pyfao56: FAO-56 evapotranspiration in Python Reprint Icon - (Peer Reviewed Journal)
Thorp, K.R., DeJonge, K.C., Pokoski, T., Gulati, D., Kukal, M., Farag, F., Hashem, A., Erismann, G., Baumgartner, T., Holzkaemper, A. 2024. Version 1.3.0 - pyfao56: FAO-56 evapotranspiration in Python. SoftwareX. 26. Article 101724. https://doi.org/10.1016/j.softx.2024.101724.

Monitoring cotton water status with microtensiometers Reprint Icon - (Peer Reviewed Journal)
Christensen, C.G., Gohardoust, M.R., Calleja, S., Thorp, K.R., Tuller, M., Pauli, D. 2024. Monitoring cotton water status with microtensiometers. Irrigation Science. 42:995-1011. https://doi.org/10.1007/s00271-024-00930-w.

Creating a producer toolbox for in-field soil health assessment in southern Idaho: Active carbon - (Abstract Only)

When soil carbon isn’t everything: Impact of regenerative practices on soil health metrics in the semi-Arid west - (Abstract Only)

Understanding within-field variation in Nitrogen Use Efficiency (NUE) using proximal sensing, field observations, and machine learning - (Abstract Only)

Evaluating intra-field spatial variability for nutrient management zone delineation through geospatial techniques and multivariate analysis Reprint Icon - (Peer Reviewed Journal)
Salem, H.M., Schott, L.R., Piaskowski, J., Chapagain, A., Yost, J.L., Brooks, E., Johnson-Maynard, J. 2024. Evaluating intra-field spatial variability for nutrient management zone delineation through geospatial techniques and multivariate analysis. Sustainability. 16(2). Article 645. https://doi.org/10.3390/su16020645.

Understanding the role of active carbon in sugarbeet cropping systems - (Trade Journal)
Schott, L.R., Agin, A., Olsen, D., Krecker-Yost, J.L. 2024. Understanding the Role of Active Carbon in Sugarbeet Cropping Systems. The Sugarbeet. 24-26.

Forecasting plant production across Great Basin rangelands - (Abstract Only)

Forecasting rangeland plant production by ecological sites; are they better than forecasts by geographical location - (Abstract Only)