Location: Cropping Systems and Water Quality Research
2022 Annual Report
Accomplishments
1. Determined corn nitrogen use efficiency is very low near optimal yield, an important consideration in balancing profitability with environmental sustainability. For corn, nitrogen (N) fertilizer use is often summarized from field to global scales using average N use efficiency ((NUE) the amount of N found in the grain relative to the applied N). However, expressing NUE as an average over the growing season is misleading because grain increase relative to added N diminishes near optimal yield. Therefore, environmental risks increase as economic benefits decrease. ARS scientists in Columbia, Missouri, in collaboration with other scientists in the U.S. Midwest, used North America datasets of corn grain yield response to N fertilizer to create and interpret “incremental NUE”, or the change in NUE with change in N fertilization. The analysis led to four results: 1) For those last units of N applied to reach economic optimal N rate (EONR, the N rate when marginal profit equals zero), NUE was only about 6%; 2) Incremental NUE was higher for medium-textured soils than fine-textured soils, possibly because fine-textured soils are more predisposed to loss of nitrate-N to gaseous forms of N and/or lower mineralization of organic N into nitrate-N; 3) Excessive and/or uneven rainfall lowered incremental NUE; and 4) A new strategy was proposed where N fertilization practices for producers should be targeted to recommend slightly below EONR—such would produce minor forgone profit but improve average NUE by about 10%. This research creates unique perspectives and ideas for how to improve N fertilizer management tools for producers, educational programs, and public policies and regulations.
Review Publications
Abendroth, L.J., Chighladze, G., Frankenberger, J., Bowling, L., Helmers, M., Herzmann, D., Jia, X., Kjaersgaard, J., Pease, L., Reinhart, B., Strock, J., Youssef, M. 2022. Paired field and water measurements from drainage management practices in row-crop agriculture. Scientific Data. 9. Article 257. https://doi.org/10.1038/s41597-022-01358-7.
Bagnall, D.K., Morgan, C.L., Cope, M., Bean, G.M., Cappellazzi, S.B., Greub, K.L., Liptzin, D., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Dungan, R.S., Fortuna, A., Kautz, M.A., Kitchen, N.R., Leytem, A.B., Liebig, M.A., Moore Jr, P.A., Osborne, S.L., Sainju, U.M., Sherrod, L.A., Watts, D.B., Ashworth, A.J., Owens, P.R., et al. 2022. Carbon-sensitive pedotransfer functions for plant-available water. Soil Science Society of America Journal. 86(3):612-629. https://doi.org/10.1002/saj2.20395.
Goodrich, D.C., Bosch, D.D., Bryant, R.B., Cosh, M.H., Endale, D.M., Veith, T.L., Kleinman, P.J., Langendoen, E.J., McCarty, G.W., Pierson Jr., F.B., Schomberg, H.H., Smith, D.R., Starks, P.J., Strickland, T.C., Tsegaye, T.D., Awada, T., Swain, H., Derner, J.D., Bestelmeyer, B.T., Schmer, M.R., Baker, J.M., Carlson, B.R., Huggins, D.R., Archer, D.W., Armendariz, G.A. 2022. Long term agroecosystem research experimental watershed network. Hydrological Processes. 36(3). Article e14534. https://doi.org/10.1002/hyp.14534. [Corrigendum: Hydrological Processes: 2022, 36(6), Article e14609. https://doi.org/10.1002/hyp.14609.]
Kitchen, N.R., Ransom, C.J., Schepers, J.S., Hatfield, J.L., Massey, R., Drummond, S.T. 2022. A new perspective when examining maize fertilizer nitrogen use efficiency, incrementally. PLoS ONE. 17(5). Article e0267215. https://doi.org/10.1371/journal.pone.0267215.
Ransom, C.J., Clark, J., Bean, G.M., Bandura, C., Schafer, M., Kitchen, N.R., Camberato, J.J., Carter, P.R., Ferguson, R.B., Fernandez, F.G., Franzen, D.W., Laboski, C.A., Myers, B.D., Nafziger, E.D., Sawyer, J.E., Shanahan, J. 2021. Data from a public–industry partnership for enhancing corn nitrogen research. Agronomy Journal. 113(5):4429-4436. https://doi.org/10.1002/agj2.20812.
Shen, Z., Ramirez-Lopez, L., Behrens, T., Cui, L., Zhang, M., Walden, L., Wetterlind, J., Shi, Z., Sudduth, K.A., Baumann, P., Song, Y., Catambay, K., Viscarra Rossel, R.A. 2022. Deep transfer learning of global spectra for local soil carbon monitoring. Journal of Photogrammetry and Remote Sensing. 188:190-200. https://doi.org/10.1016/j.isprsjprs.2022.04.009.
Vong, C., Conway, L.S., Feng, A., Zhou, J., Kitchen, N.R., Sudduth, K.A. 2022. Corn emergence uniformity estimation and mapping using UAV imagery and deep learning. Computers and Electronics in Agriculture. 198. Article 107008. https://doi.org/10.1016/j.compag.2022.107008.
