{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T05:46:53Z","timestamp":1779169613184,"version":"3.51.4"},"reference-count":49,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006229","name":"Oak Ridge Institute for Science and Education","doi-asserted-by":"publisher","award":["DE-AC05-06OR23100"],"award-info":[{"award-number":["DE-AC05-06OR23100"]}],"id":[{"id":"10.13039\/100006229","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Midwestern US is dominated by corn (Zea mays L.) and soybean (Glycine max [L.] Merr.) production, and the carbon dynamics of this region are dominated by these production systems. An accurate regional estimate of gross primary production (GPP) is imperative and requires upscaling approaches. The aim of this study was to upscale corn and soybean GPP (referred to as GPPcalc) in four counties in Central Iowa in the 2016 growing season (DOY 145\u2013269). Eight eddy-covariance (EC) stations recorded carbon dioxide fluxes of corn (n = 4) and soybean (n = 4), and net ecosystem production (NEP) was partitioned into GPP and ecosystem respiration (RE). Additional field-measured NDVI was used to calculate radiation use efficiency (RUEmax). GPPcalc was calculated using 16 MODIS satellite images, ground-based RUEmax and meteorological data, and improved land use maps. Seasonal NEP, GPP, and RE (     x \u00af      \u00b1 SE) were 678 \u00b1 63, 1483 \u00b1 100, and \u2212805 \u00b1 40 g C m\u22122 for corn, and 263 \u00b1 40, 811 \u00b1 53, and \u2212548 \u00b1 14 g C m\u22122 for soybean, respectively. Field-measured NDVI aligned well with MODIS fPAR (R2 = 0.99), and the calculated RUEmax was 3.24 and 1.90 g C MJ\u22121 for corn and soybean, respectively. The GPPcalc vs. EC-derived GPP had a RMSE of 2.24 and 2.81 g C m\u22122 d\u22121, for corn and soybean, respectively, which is an improvement to the GPPMODIS product (2.44 and 3.30 g C m\u22122 d\u22121, respectively). Corn yield, calculated from GPPcalc (12.82 \u00b1 0.65 Mg ha\u22121), corresponded well to official yield data (13.09 \u00b1 0.09 Mg ha\u22121), while soybean yield was overestimated (6.73 \u00b1 0.27 vs. 4.03 \u00b1 0.04 Mg ha\u22121). The approach presented has the potential to increase the accuracy of regional corn and soybean GPP and grain yield estimates by integrating field-based flux estimates with remote sensing reflectance observations and high-resolution land use maps.<\/jats:p>","DOI":"10.3390\/rs11141688","type":"journal-article","created":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T02:44:03Z","timestamp":1563331443000},"page":"1688","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Upscaling Gross Primary Production in Corn-Soybean Rotation Systems in the Midwest"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6035-5597","authenticated-orcid":false,"given":"Christian","family":"Dold","sequence":"first","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2981-8856","authenticated-orcid":false,"given":"Jerry L.","family":"Hatfield","sequence":"additional","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John H.","family":"Prueger","sequence":"additional","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom B.","family":"Moorman","sequence":"additional","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom J.","family":"Sauer","sequence":"additional","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael H.","family":"Cosh","sequence":"additional","affiliation":[{"name":"USDA-ARS, Hydrology and Remote Sensing Laboratory, BARC-West, Beltsville, MD 20705, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2593-7599","authenticated-orcid":false,"given":"Darren T.","family":"Drewry","sequence":"additional","affiliation":[{"name":"Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH 43210, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7035-1071","authenticated-orcid":false,"given":"Ken M.","family":"Wacha","sequence":"additional","affiliation":[{"name":"USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,17]]},"reference":[{"key":"ref_1","unstructured":"(2019, April 04). National Agricultural Statistics Service (NASS), Available online: https:\/\/www.nass.usda.gov\/Publications\/Ag_Statistics\/index.php."},{"key":"ref_2","unstructured":"FAOSTAT (2019, April 04). Food and Agriculture Organization of the United Nations, Statistics Division. Forestry Production and Trade. Available online: http:\/\/www.fao.org\/faostat\/en\/#data\/FO."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"E1327","DOI":"10.1073\/pnas.1320008111","article-title":"Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence","volume":"111","author":"Guanter","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2134\/age2018.08.0032","article-title":"Impact of Management Practices on Carbon and Water Fluxes in Corn\u2013Soybean Rotations","volume":"2","author":"Dold","year":"2019","journal-title":"AGE"},{"key":"ref_5","unstructured":"USDA-NASS (2019, July 09). 2017 Census of Agriculture, Available online: https:\/\/www.nass.usda.gov\/Publications\/AgCensus\/2017\/Full_Report\/Volume_1,_Chapter_1_State_Level\/Iowa\/."},{"key":"ref_6","unstructured":"Running, S.W., and Zhao, M. (2019, March 19). Daily GPP and Annual NPP (MOD17A2\/A3) Products NASA Earth Observing System MODIS Land Algorithm, Available online: https:\/\/landweb.modaps.eosdis.nasa.gov\/QA_WWW\/forPage\/user_guide\/MOD17UsersGuide2015v3.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1080\/01431160512331326567","article-title":"Usefulness and limits of MODIS GPP for estimating wheat yield","volume":"26","author":"Reeves","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1029\/2011GB004053","article-title":"Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales","volume":"25","author":"Ryu","year":"2011","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.rse.2016.08.030","article-title":"Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS)","volume":"186","author":"Jiang","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.rse.2006.09.010","article-title":"Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand","volume":"107","author":"Coops","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1016\/j.rse.2010.07.012","article-title":"Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest","volume":"114","author":"Wu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.agrformet.2014.11.004","article-title":"Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States","volume":"201","author":"Xin","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5926","DOI":"10.3390\/rs5115926","article-title":"A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US","volume":"5","author":"Xin","year":"2013","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2014.07.012","article-title":"Estimation of crop gross primary production (GPP): fAPARchl versus MOD15A2 FPAR","volume":"153","author":"Zhang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agrformet.2014.09.003","article-title":"Estimation of crop gross primary production (GPP): II. Do scaled MODIS vegetation indices improve performance?","volume":"200","author":"Zhang","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2012.12.023","article-title":"Evaluation of MODIS gross primary productivity for Africa using eddy covariance data","volume":"131","author":"Zhao","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.rse.2006.02.017","article-title":"Evaluation of MODIS NPP and GPP products across multiple biomes","volume":"102","author":"Turner","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"676","DOI":"10.2134\/jeq2016.09.0363","article-title":"Agricultural Conservation Planning Framework: 3. Land Use and Field Boundary Database Development and Structure","volume":"46","author":"Tomer","year":"2017","journal-title":"J. Environ. Qual."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"014516","DOI":"10.1117\/1.JRS.13.014516","article-title":"Estimating vegetation water content during the Soil Moisture Active Passive Validation Experiment 2016","volume":"13","author":"Cosh","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.rse.2019.04.004","article-title":"Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16)","volume":"227","author":"Colliander","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_21","unstructured":"USDA-NRCS (2018). Soil Survey Geographic (SSURGO) Database for Hardin, Franklin, Hamilton & Story County, Iowa."},{"key":"ref_22","unstructured":"IEM (2018, October 10). Iowa Environmental Mesonet\u2014Climate Data. Available online: https:\/\/mesonet.agron.iastate.edu\/."},{"key":"ref_23","unstructured":"Burba, G. (2013). Eddy Covariance Method for Scientific, Industrial, Agricultural and Regulatory Applications: A Field Book on Measuring Ecosystem Gas. Exchange and Areal Emission Rates, LI-COR Biosciences."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3695","DOI":"10.5194\/gmd-8-3695-2015","article-title":"A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP)","volume":"8","author":"Kljun","year":"2015","journal-title":"Geosci. Model. Dev."},{"key":"ref_25","unstructured":"Tanner, C.B., and Thurtell, G.W. (1969). Anemoclinometer Measurements of Reynolds Stress and Heat Transport in the Atmospheric Surface Layer, Department of Soil Science Wisconsin University."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1002\/qj.49710644707","article-title":"Correction of flux measurements for density effects due to heat and water vapour transfer","volume":"106","author":"Webb","year":"1980","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.agrformet.2016.07.012","article-title":"Long-term carbon uptake of agro-ecosystems in the Midwest","volume":"232","author":"Dold","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1016\/j.agrformet.2011.07.017","article-title":"Carbon dioxide fluxes in corn\u2013soybean rotation in the midwestern U.S.: Inter- and intra-annual variations, and biophysical controls","volume":"151","author":"Hatfield","year":"2011","journal-title":"Agric. For. Meteorol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.agrformet.2004.11.005","article-title":"Examining strategies to improve the carbon balance of corn\/soybean agriculture using eddy covariance and mass balance techniques","volume":"128","author":"Baker","year":"2005","journal-title":"Agric. For. Meteorol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s00704-009-0169-y","article-title":"Energy balance and turbulent flux partitioning in a corn\u2013soybean rotation in the Midwestern US","volume":"100","author":"Hatfield","year":"2010","journal-title":"Theor. Appl. Climatol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1111\/j.1365-2486.2005.001002.x","article-title":"On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm","volume":"11","author":"Reichstein","year":"2005","journal-title":"Glob. Chang. Boil."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.agee.2006.12.008","article-title":"Partitioning European grassland net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using light response function analysis","volume":"121","author":"Gilmanov","year":"2007","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Campbell, G.S., and Norman, J.M. (1998). An Introduction to Environmental Biophysics, Springer Science and Business Media LLC.","DOI":"10.1007\/978-1-4612-1626-1"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1820","DOI":"10.2134\/agronj2013.0310","article-title":"Radiation Use Efficiency: Evaluation of Cropping and Management Systems","volume":"106","author":"Hatfield","year":"2014","journal-title":"Agron. J."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"562","DOI":"10.3390\/rs2020562","article-title":"Value of Using Different Vegetative Indices to Quantify Agricultural Crop Characteristics at Different Growth Stages under Varying Management Practices","volume":"2","author":"Hatfield","year":"2010","journal-title":"Remote Sens."},{"key":"ref_36","unstructured":"Abendroth, L.J., Elmore, R.W., Boyer, M.J., and Marlay, S.K. (2011). Corn Growth and Development, PMR. Iowa State University Extension."},{"key":"ref_37","unstructured":"Pedersen, P. (2004). Soybean Growth and Development, Iowa State University."},{"key":"ref_38","unstructured":"USGS (2019, March 21). US Geological Survey, MODIS Products Courtesy of the U.S. Geological Survey, Available online: https:\/\/lpdaacsvc.cr.usgs.gov\/appeears\/."},{"key":"ref_39","unstructured":"Myneni, R., Knyazikhin, Y., and Park, T. (2018, October 10). MOD15A2H MODIS\/Terra Leaf Area Index\/FPAR 8-Day L4 Global 500 m SIN Grid V006 [Dataset]. Available online: http:\/\/doi.org\/10.5067\/MODIS\/MOD15A2H.006."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1175\/1520-0450(1977)016<0100:AAPFTC>2.0.CO;2","article-title":"An Approximating Polynomial for the Computation of Saturation Vapor Pressure","volume":"16","author":"Lowe","year":"1977","journal-title":"J. Appl. Meteorol."},{"key":"ref_41","unstructured":"R Core Team (2014). The R Foundation for Statistical Computing, The R Foundation."},{"key":"ref_42","unstructured":"Friedl, M., and Sulla-Menashe, D. (2018, October 10). MCD12Q1 MODIS\/Terra+ Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006 [Dataset]. Available online: http:\/\/doi.org\/10.5067\/MODIS\/MCD12C1.006."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1372","DOI":"10.2134\/agronj2004.1372","article-title":"Response of Soybean Yield Components to Management System and Planting Date","volume":"96","author":"Pedersen","year":"2004","journal-title":"Agron. J."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"8621","DOI":"10.3390\/su7078621","article-title":"Corn Stover Nutrient Removal Estimates for Central Iowa, USA","volume":"7","author":"Karlen","year":"2015","journal-title":"Sustainability"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1890\/1051-0761(2001)011[1194:NPPOUS]2.0.CO;2","article-title":"Net primary production of US Midwest croplands from agricultural harvest yield data","volume":"11","author":"Prince","year":"2001","journal-title":"Ecol. Appl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1867","DOI":"10.1111\/j.1365-2486.2005.01050.x","article-title":"The conversion of the corn\/soybean ecosystem to no-till agriculture may result in a carbon sink","volume":"11","author":"Bernacchi","year":"2005","journal-title":"Glob. Chang. Boil."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"285","DOI":"10.2134\/agronj2005.0116S","article-title":"Spatial and Temporal Variation of Energy and Carbon Fluxes in Central Iowa","volume":"99","author":"Hatfield","year":"2007","journal-title":"Agron. J."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"98","DOI":"10.2134\/jeq2006.0392","article-title":"Soil Carbon Dioxide Emission and Carbon Content as Affected by Irrigation, Tillage, Cropping System, and Nitrogen Fertilization","volume":"37","author":"Sainju","year":"2008","journal-title":"J. Environ. Qual."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1631","DOI":"10.1175\/BAMS-83-11-1631","article-title":"NCEP\u2013DOE AMIP-II Reanalysis (R-2)","volume":"83","author":"Kanamitsu","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1688\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:06:22Z","timestamp":1760187982000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1688"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,17]]},"references-count":49,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["rs11141688"],"URL":"https:\/\/doi.org\/10.3390\/rs11141688","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,17]]}}}