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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Research Project #441925

Research Project: Improving Crop Performance and Precision Irrigation Management in Semi-Arid Regions through Data-Driven Research, AI, and Integrated Models

Location: Water Management and Systems Research

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

Estimating leaf chlorophyll content of winter wheat from UAV multispectral images using machine learning algorithms under different species, growth stages, and nitrogen stress conditions Reprint Icon - (Peer Reviewed Journal)
Zhang, L., Wang, A., Zhang, H., Zhu, Q., Zhang, H., Sun, W., Niu, Y. 2024. Estimating leaf chlorophyll content of winter wheat from UAV multispectral images using machine learning algorithms under different species, growth stages, and nitrogen stress conditions. Agriculture. 14(7). Article e1064. https://doi.org/10.3390/agriculture14071064.

Diurnal patterns in sap flow through maize stems suggest a role for capacitance tissues in maintaining the transpiration stream - (Peer Reviewed Journal)

Mapping maize evapotranspiration with two-source land surface energy balance approaches and multiscale remote sensing imagery pixel sizes: Accuracy determination toward a sustainable irrigated agriculture Reprint Icon - (Peer Reviewed Journal)
Costa-Filho, E., Chavez, J.L., Zhang, H. 2024. Assessing maize evapotranspiration estimation from two-source surface energy balance approaches using several remote sensing sensors. Sustainability. 16(11). Article e4850. https://doi.org/10.3390/su16114850.

Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado Reprint Icon - (Peer Reviewed Journal)
DeJonge, K.C., Thorp, K.R., Brekel, J.J., Pokoski, T.C., Trout, T.J. 2024. Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado. Agricultural Water Management. 299. Article e108891. https://doi.org/10.1016/j.agwat.2024.108891.

Comparative venation costs of monocotyledon and dicotyledon species in the Eastern Colorado steppe Reprint Icon - (Peer Reviewed Journal)
Drobnitch, S., Kray, J.A., Gleason, S.M., Ocheltree, T. 2024. Comparative venation costs of monocotyledon and dicotyledon species in the Eastern Colorado steppe. Planta. 260. Article e2. https://doi.org/10.1007/s00425-024-04434-x.

Diurnal trends of maize canopy cover imaging under water stress, and estimation of evapotranspiration coefficients - (Abstract Only)

Linking fine root lifespan to root chemical and morphological traits - a global analysis Reprint Icon - (Peer Reviewed Journal)
Hou, J., McCormack, L.M., Reich, P.B., Sun, T., Phillips, R.P., Lambers, H., Chen, H.H., Ding, Y., Comas, L.H., Valverde-Barrantes, O.J., Solly, E.F., Freschet, G.T. 2024. Linking fine root lifespan to root chemical and morphological traits - a global analysis. Proceedings of the National Academy of Sciences (PNAS). 121(16). Article e2320623121. https://doi.org/10.1073/pnas.2320623121.

Estimating winter wheat plant nitrogen content using spectral and texture features based on a low-cost UAV RGB system throughout the growing season Reprint Icon - (Peer Reviewed Journal)
Zhang, L., Song, X., Zhu, Q., Zhang, H., Wang, A., Niu, Y. 2024. Estimating winter wheat plant nitrogen content using spectral and texture features based on a low-cost UAV RGB system throughout the growing season. Agriculture. 14(3). Article e456. https://doi.org/10.3390/agriculture14030456.

A novel remote sensing-based modeling approach for maize light extinction coefficient determination Reprint Icon - (Peer Reviewed Journal)
Costa-Filho, E., Chavez, J.L., Zhang, H. 2024. A novel remote sensing-based modeling approach for maize light extinction coefficient determination. Remote Sensing. 16(6). Article 1012. https://doi.org/10.3390/rs16061012.

Searching for mechanisms driving root pressure in Zea mays—a transcriptomic approach Reprint Icon - (Peer Reviewed Journal)
Drobnitch, S.T., Wenz, J.A., Gleason, S.M., Comas, L.H. 2024. Searching for mechanisms driving root pressure in Zea mays—a transcriptomic approach. Journal of Plant Physiology. 296. Article e154209. https://doi.org/10.1016/j.jplph.2024.154209.

Development and application of an inexpensive open-source dendrometer for detecting xylem water potential and radial stem growth at high spatial and temporal resolution Reprint Icon - (Peer Reviewed Journal)
Gleason, S.M., Stewart, J.J., Allen, B.S., Polutchko, S.K., McMahon, J.E., Barnard, D.M., Spitzer, D.B. 2024. Development and application of an inexpensive open-source dendrometer for detecting xylem water potential and radial stem growth at high spatial and temporal resolution. AoB Plants. 16(2). Article eplae009. https://doi.org/10.1093/aobpla/plae009.

Diurnal trends of maize canopy cover under water stress Reprint Icon - (Peer Reviewed Journal)
Dejonge, K.C., Zhang, H., Cummins, L., Gilkerson, T., Ascough, K., Pokoski, T.C. 2024. Diurnal trends of maize canopy cover under water stress. Journal of Natural Resources and Agricultural Ecosystems. 2(2): 77-89. https://doi.org/10.13031/jnrae.15792.

Prediction Of chlorophyll-a as an index of harmful algal blooms using machine learning models Reprint Icon - (Peer Reviewed Journal)
Busari, I., Sahoo, D., Harmel, R.D., Haggard, B. 2024. Prediction Of chlorophyll-a as an index of harmful algal blooms using machine learning models. American Society of Agricultural and Biological Engineers. 2(2):53-61. https://doi.org/10.13031/jnrae.15812.

Assessing multi-sensor hourly maize evapotranspiration estimation using a one-source surface energy balance approach Reprint Icon - (Peer Reviewed Journal)
Costa-Filho, E., Chavez, J.L., Zhang, H. 2024. Assessing multi-sensor hourly maize evapotranspiration estimation using a one-source surface energy balance approach. Journal of Irrigation and Drainage. https://doi.org/10.1002/ird.2923.

Estimating and mapping the dynamics of soil salinity under different crop types using Sentinel-2 satellite imagery Reprint Icon - (Peer Reviewed Journal)
Cui, X., Han, W., Zhang, H., Dong, Y., Ma, W., Zhai, X., Zhang, L., Li, G. 2023. Estimating and mapping the dynamics of soil salinity under different crop types using Sentinel-2 satellite imagery. Geoderma. 440(2023). Article e116738. https://doi.org/10.1016/j.geoderma.2023.116738.

Nitrogen fertilizer and irrigation effects on plant and soil nitrogen dynamics - (Abstract Only)
Donovan, T., Schneekloth, J., Comas, L.H., Schipanski, M. 2023. Nitrogen fertilizer and irrigation effects on plant and soil nitrogen dynamics. Meeting Abstract.

Maize evapotranspiration estimates using Planet Dove mini-satellites and field-level infra-red thermometers Reprint Icon - (Peer Reviewed Journal)
Chávez, J.L., Zhang, H., Brown, A., Andales, A.A., Costa-Filho, E. 2024. Maize evapotranspiration estimates using Planet Dove mini-satellites and field-level infra-red thermometers. Applied Engineering in Agriculture. 40(1): 69-78. https://doi.org/10.13031/aea.15703.

Winter wheat crop models improve growth simulation by including phenological response to water-deficit stress Reprint Icon - (Peer Reviewed Journal)
Mankin, K.R., Edmunds, D.A., McMaster, G.S., Fox, F.A., Wagner, L.E., Green, T.R. 2023. Winter wheat crop models improve growth simulation by including phenological response to water-deficit stress. Environmental Modeling and Assessment. 29:235-248. https://doi.org/10.1007/s10666-023-09939-5.

Enhancing model performance in detecting lodging areas in wheat fields using UAV RGB imagery: Considering spatial and temporal variations Reprint Icon - (Peer Reviewed Journal)
Zhang, D., Zhang, G., Tao, C., Zhang, H. 2023. Enhancing model performance in detecting lodging areas in wheat fields using UAV RGB imagery: Considering spatial and temporal variations. Computers and Electronics in Agriculture. 214. Article e108297. https://doi.org/10.1016/j.compag.2023.108297.

Grass veins are leaky pipes: Vessel widening in grass leaves explain variation in stomatal conductance and vessel diameter among species Reprint Icon - (Peer Reviewed Journal)
Ocheltree, T.W., Gleason, S.M. 2023. Grass veins are leaky pipes: Vessel widening in grass leaves explain variation in stomatal conductance and vessel diameter among species. New Phytologist. 241(1):243-252. https://doi.org/10.1111/nph.19368.

A review of data quality and cost considerations for water quality monitoring at the field scale and in small watersheds Reprint Icon - (Peer Reviewed Journal)
Harmel, R.D., Preisendanz, H.E., King, K.W., Busch, D., Birgand, F., Sahoo, D. 2023. A review of data quality and cost considerations for water quality monitoring at the field scale and in small watersheds. Water. 15(17), 3110. https://doi.org/10.3390/w15173110.

A multi-sensor analysis of selected reflectance-based crop coefficient models for daily maize evapotranspiration estimation Reprint Icon - (Peer Reviewed Journal)
Costa-Filho, E., Chavez, J.L., Zhang, H., Andales, A.A., Brown, A. 2023. A multi-scale analysis of reflectance-based crop coefficient models for daily maize evapotranspiration estimation. Journal of Agricultural Science. 15(12). https://doi.org/10.5539/jas.v15n12p1.

Comparative anatomy vs mechanistic understanding: How to interpret the diameter-vulnerability link Reprint Icon - (Peer Reviewed Journal)
Lens, F., Gleason, S.M., Bortolami, G., Brodersen, C., Delzon, S., Jansen, S. 2023. Comparative anatomy vs mechanistic understanding: How to interpret the diameter-vulnerability link. IAWA Journal(International Association of Wood Anatomists Journal). 44(3-4):368-380. https://doi.org/10.1163/22941932-bja10137.

The effects of copper deficiency on lignification, xylem vessel structure, and hydraulic traits in hybrid Poplar Reprint Icon - (Peer Reviewed Journal)
Hunter, C., Sun, Z., Mansfield, S., Shahbaz, M., Pilon, M., Gleason, S.M. 2023. The effects of copper deficiency on lignification, xylem vessel structure, and hydraulic traits in hybrid Poplar. Plant Physiology. 175(5). Article e14006. https://doi.org/10.1111/ppl.14006.

High N availability decreases N uptake and yield under limited water availability in maize Reprint Icon - (Peer Reviewed Journal)
Flynn, N.E., Comas, L.H., Stewart, C.E., Fonte, S.J. 2023. High N availability decreases N uptake and yield under limited water availability in maize. Scientific Reports. 13. Article e14269. https://doi.org/10.1038/s41598-023-40459-0.

Nitrogen and water availability effects on soil N dynamics - (Abstract Only)
Donovan, T., Schipanski, M., Schneekloth, J., Comas, L.H. 2023. Nitrogen and water availability effects on soil N dynamics. ASA-CSSA-SSSA Annual Meeting Abstracts. Meeting Abstract.

Do lags in hydraulic time constants of sap flow through maize stems correspond to the size of capacitance tissues? - (Abstract Only)

Drought conditioning of rhizosphere microbiome influences maize water use traits Reprint Icon - (Peer Reviewed Journal)
Carter, K.R., Nachtsheim, A.C., Dickman, L.T., Moore, E.R., Negi, S., Heneghan, J.P., Sabella, A.J., Steadman, C.R., Albright, M.B., Anderson-Cook, C.M., Comas, L.H., Harris, R.J., Heikoop, J.M., Lubbers, N.E., Marina, O.C., Musa, D., Newman, B.D., Perkins, G.B., Twary, S., Yeager, C.M., Dunbar, J.M., Sevanto, S. 2023. Drought conditioning of rhizosphere microbiome influences maize water use traits. Plant and Soil. 492:587-604. https://doi.org/10.1007/s11104-023-06204-2.

Weather data-centric prediction of maize non-stressed canopy temperature in semi-arid climates for irrigation management Reprint Icon - (Peer Reviewed Journal)
Nakabuye, H., Rudnick, D., DeJonge, K.C., Ascough, K.A., Liang, W., Lo, T., Franz, T., Qiao, X., Katimbo, A., Duan, J. 2023. Weather data-centric prediction of maize non-stressed canopy temperature in semi-arid climates for irrigation management. Irrigation Science. https://doi.org/10.1007/s00271-023-00863-w.

Can the Law of Constant Final Yield be used to delineate plant productivity limited by competition for water? - (Abstract Only)

Quantifying crop behavior with observations and models: Constraining simulations at LIRF - (Abstract Only)

Assessing CO2 exchange, water use and yield of maize crops under full and deficit irrigation using UAV and satellite imagery - (Abstract Only)

TSWIFT – A scanning tower-based hyperspectral instrument to capture diurnal and seasonal physiological plant response - (Abstract Only)

Spatiotemporal modeling of maize light extinction coefficient using Sentinel-2 multispectral data - (Abstract Only)

Soil Biology: Root form and function - (Book / Chapter)
Garbowski, M., Freschet, G.T., Brown, C.S., Jackson, L.E., Comas, L.H. 2023. Soil Biology: Root form and function. In: Goss, M., Oliver, M., editors. Encyclopedia of Soils in the Environment. 2nd edition. Amsterdam, The Netherlands: Elsevier ScienceDirect. p. 321-331.

Evaluation of artificial intelligence algorithms with sensor data assimilation in estimating crop evapotranspiration and crop water stress index for precision irrigation water management Reprint Icon - (Peer Reviewed Journal)
Katimbo, A., Rudnick, D.R., Zhang, J., Ge, Y., DeJonge, K.C., Franz, T.E., Shi, Y., Liang, W., Qiao, X., Heeren, D.M., Kabenge, I., Nakabuye, H.N., Duan, J. 2023. Evaluation of artificial intelligence algorithms with sensor data assimilation in estimating crop evapotranspiration and crop water stress index for precision irrigation water management. Smart Agricultural Technology. 4. Article e100176. https://doi.org/10.1016/j.atech.2023.100176.

Soil-plant hydraulics explain the stomatal efficiency-safety tradeoff Reprint Icon - (Peer Reviewed Journal)
Cai, G., Carminati, A., Gleason, S.M., Javaux, M., Ahmed, M. 2023. Soil-plant hydraulics explain the stomatal efficiency-safety tradeoff. Plant, Cell & Environment. https://doi.org/10.1111/pce.14536.

Evaluating soil moisture content under maize coverage using UAV multimodal data by machine learning algorithms Reprint Icon - (Peer Reviewed Journal)
Zhang, Y., Han, W., Zhang, H., Niu, X., Shao, G. 2023. Evaluating soil moisture content under maize coverage using UAV multimodal data by machine learning algorithms. Journal of Hydrology. 617. Article e129086. https://doi.org/10.1016/j.jhydrol.2023.129086.

Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods Reprint Icon - (Peer Reviewed Journal)
Shao, G., Han, W., Zhang, H., Zhang, L., Wang, Y., Zhang, Y. 2022. Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods. Agricultural Water Management. 276. Article e108064. https://doi.org/10.1016/j.agwat.2022.108064.

Using remote sensing to inform crop coefficient based irrigation scheduling under deficit irrigation - (Abstract Only)

Improved estimation of crop water use by linking multi-scale thermal and solar-induced fluorescence measurements - (Abstract Only)

Optimizing soil moisture sensor depth for irrigation management using universal multiple linear regression - (Abstract Only)

Evaluating reflectance-based maize evapotranspiration modeling under different irrigation systems - (Abstract Only)

Deficit irrigation strategies for the western U.S. Reprint Icon - (Peer Reviewed Journal)
Trout, T.J., Howell, T.A., English, M.J., Martin, D.L. 2020. Deficit irrigation strategies for the western U.S.. American Society of Agricultural and Biological Engineers. 63(6), 1813-1825. https://doi.org/10.13031/trans.14114.