The Role of Agricultural Science and Technology in Climate 21 Project Implementation

Authors

  • David Baltensperger Texas A&M University image/svg+xml Author
  • Manojit Basu CropLife America Author
  • Zhengxia Dou University of Pennsylvania image/svg+xml Author
  • Sally Flis Nutrien Ag Solutions Author
  • David Galligan University of Pennsylvania image/svg+xml Author
  • Marty Matlock University of Arkansas Author
  • Cristine Morgan Soil Health Institute Author
  • Debbie Reed Ecosystem Services Market Consortium Author
  • Charles W. Rice Kansas State University image/svg+xml Author
  • Gerald Shurson University of Minnesota image/svg+xml Author
  • Alex Thomasson Mississippi State University image/svg+xml Author
  • Addie M. Thompson Michigan State University image/svg+xml Author
  • Allison Thomson Field to Market Author
  • Juan M. Tricarico Author
  • Jianming Yu Author

DOI:

https://doi.org/10.62300/0p2xj465

Keywords:

Climate‑Smart Agriculture, Greenhouse Gas Mitigation, Soil Carbon Sequestration, Precision Agriculture Technologies, Carbon Markets

Abstract

This commentary evaluates how agricultural science and technology can support implementation of the federal Climate 21 Project, which positions the U.S. Department of Agriculture as a central actor in national climate mitigation and resilience strategies. Agriculture and forestry are highlighted as the only major sectors capable of becoming net greenhouse gas sinks, offering substantial potential to help the United States reach net‑zero emissions by 2050 through soil carbon sequestration, improved nutrient management, reduced tillage, and strengthened crop and livestock systems. The document synthesizes scientific knowledge and identifies opportunities to scale climate‑smart practices across plant, soil, animal, and food systems. Key strategies include conservation agriculture to improve soil health and water efficiency; precision nutrient, water, and pest management to reduce nitrous oxide emissions; integrated pest management and conservation tillage to cut fuel use and enhance carbon storage; and innovations in animal agriculture that target methane mitigation, improved feed efficiency, and whole‑farm greenhouse gas modeling. The commentary also highlights emerging tools such as precision agriculture, remote sensing, advanced breeding, and improved soil carbon measurement technologies that can accelerate adoption and strengthen measurement, reporting, and verification.

Downloads

Download data is not yet available.

References

Abidine, A. Z., Heidman, B. C., Upadhyaya, S. K., & Hills, D. J. (2002). Application of RTK GPS–based auto‑guidance system in agricultural production. ASABE.

Ackerson, J. P., Morgan, C. L. S., & Ge, Y. (2017). Penetrometer‑mounted VisNIR spectroscopy: Application of EPO‑PLS to in situ VisNIR spectra. Geoderma, 286, 131–138.

Atkinson, J. A., Pound, M. P., Bennett, M. J., & Wells, D. M. (2019). Uncovering the hidden half of plants using advances in root phenotyping. Current Opinion in Biotechnology, 55, 1–8.

Bailey, R. L., West, K. P., & Black, R. E. (2015). The epidemiology of global micronutrient deficiencies. Annals of Nutrition and Metabolism, 66(Suppl. 2), 22–33.

Balafoutis, A. et al. (2017). Precision agriculture technologies contributing to GHG mitigation, productivity, and economics. Sustainability, 9(8), 1339.

Basarab, J. A. et al. (2013). Reducing GHG emissions through genetic improvement for feed efficiency. Animal, 7(S2), 303–315.

Bates, J., Brophy, N., Harfoot, M., & Webb, J. (2009). SERPEC‑CC: Sectoral emission reduction potentials for agriculture.

Batte, M. T., & Ehsani, M. R. (2006). The economics of precision guidance with auto‑boom control. Computers and Electronics in Agriculture, 53, 28–44.

Bausch, W. C., & Delgado, J. A. (2005). Impact of residual soil nitrate on in‑season nitrogen applications. Precision Agriculture, 6, 509–519.

Bayer Crop Science. Climate Change. (Accessed Dec 4, 2020).

Bentrup, F., & Paliere, C. (2008). Energy Efficiency and Greenhouse Gas Emissions in European Nitrogen Fertilizer Production and Use.

Bernardo, R. (2020). Breeding for Quantitative Traits in Plants (3rd ed.). Stemma Press.

Bora, G. C., Nowatzki, J. F., & Roberts, D. C. (2012). Energy savings by adopting precision agriculture. Energy, Sustainability and Society, 2, 22.

Bonnie, R., Jones, L., & Harrell, M. (2021). Climate 21 USDA Transition Memo.

Brown, R. M. et al. (2016). The carbon footprint and economic impact of precision agriculture. Journal of Environmental Economics and Policy, 5(3), 335–348.

Bustos‑Korts, D. et al. (2019). Combining crop growth modeling and genomic modeling. Frontiers in Plant Science, 10, 1491.

Buzby, J. C., Wells, H. F., & Hyman, J. E. (2014). The Estimated Amount, Value and Calories of Postharvest Food Losses. USDA‑ERS EIB‑121.

Buzby, J. C. et al. (2016). Supermarket shrink estimates for fresh foods. USDA‑ERS EIB‑155.

Cady, R. A. (2020). A review of GWP*: Estimating warming potential of short‑lived climate pollutants.

Chaikam, V. et al. (2019). Doubled haploid technology in maize. Theoretical and Applied Genetics, 132, 3227–3243.

Chambers, A., Lal, R., & Paustian, K. (2016). Croplands and grasslands: Implementing the 4 per 1000 Initiative. Journal of Soil and Water Conservation, 71, 68A–74A.

Chen, Y. et al. (2013). Variable‑rate air‑assisted spraying in tree canopies. Transactions of the ASABE, 56, 1263–1272.

Clancy, M., Fuglie, K., & Heisey, P. (2016). U.S. Agricultural R&D in an Era of Falling Public Funding. USDA‑ERS.

CropLife America (2011). Contribution of crop protection products to the U.S. economy.

CropLife International (2020). Importance and benefits of pesticides.

Crossa, J. et al. (2017). Genomic selection in plant breeding. Trends in Plant Science, 22, 961–975.

Dammer, K.‑H., & Wartenberg, G. (2007). Sensor‑based weed detection. Crop Protection, 26, 270–277.

Dammer, K.‑H., & Adamek, R. (2012). Sensor‑based insecticide spraying. Agronomy Journal, 104, 1694–1701.

De Deyn, G. B., Cornelissen, J. H. C., & Bardgett, R. D. (2008). Plant functional traits and soil carbon sequestration. Ecology Letters, 11, 516–531.

Dou, Z. (2020). Leveraging livestock in circular food systems. FASEB, 8(1), 188–193.

Dou, Z., & Toth, J. (2021). Global primary data on consumer food waste. Resources, Conservation & Recycling.

Dou, Z., Galligan, D., et al. (2018). Food loss and waste (CAST Issue Paper #62).

Dou, Z., Toth, J. D., & Westendorf, M. (2018). Food waste for livestock feeding. Global Food Security.

Evans, R. G. et al. (2013). Variable‑rate sprinkler irrigation. Irrigation Science, 31, 871–887.

FAO (2011). World Livestock: Livestock in Food Security.

FAO (2013). Food Wastage Footprint: Impacts on Natural Resources.

FAO (2017). Nutrition and Food Systems.

Friedberg, S. (2018). Corporate food sustainability supply chains. Journal of Peasant Studies.

Furbank, R. et al. (2019). Field crop phenomics. New Phytologist, 233, 1717–1727.

Gage, J. et al. (2019). Latent space phenotyping for maize. Plant Phenome Journal.

Garnett, T. et al. (2013). Sustainable intensification. Science, 341, 33–34.

Gerber, P. J. et al. (2013). Tackling Climate Change Through Livestock. FAO.

Gerhards, R. et al. (1999). Site‑specific herbicide application.

Ghahramani, A., & Moore, A. D. (2016). Climate change impacts on crop‑livestock systems. Agricultural Systems, 146, 142–155.

Gil, E. et al. (2007). Variable‑rate plant protection in vineyards. Crop Protection, 26, 1287–1297.

Heisel, T. et al. (1999). Site‑specific weed management field experiments.

Hengl, T. et al. (2017). SoilGrids: Global gridded soil data. PLOS ONE.

Hörbe, T. A. N. et al. (2013). Optimizing corn populations. Precision Agriculture, 14, 450–465.

HydroSence (2013). Precision irrigation technologies.

IPCC (2007). Climate Change 2007: The Physical Science Basis.

Jarquin, D. et al. (2014). Reaction‑norm genomic models. TAG, 127, 597–607.

Ju, M. et al. (2016). Food waste recycling in Korea. Journal of Material Cycles and Waste Management, 18, 419–426.

Kebreab, E. et al. (2019). Integrated dairy system modeling. Animal Frontiers, 9(2), 25–32.

Kell, D. B. (2011). Deep‑rooted crop plants. Annals of Botany, 108, 407–418.

Kibler, K. M. et al. (2018). Food waste management review. Waste Management, 74, 52–62.

Kim, M.‑H., & Kim, J.‑W. (2010). Food waste disposal LCA. Science of the Total Environment, 408, 3998–4006.

Kusmec, A. et al. (2021). Data‑driven plant breeding. One Earth, 4, 372–383.

Le Quéré, C. et al. (2018). Global carbon budget. Earth System Science Data, 10, 2141–2194.

Leinweber, P. et al. (2017). The phosphorus paradox. Ambio, 47, S3–S19.

Li, X. et al. (2021). GWAS and GS integration. Molecular Plant, 14, 874–887.

Lin, L. et al. (2018). AD and composting review. Renewable and Sustainable Energy Reviews, 89, 151–167.

Lipper, L. et al. (2014). Climate‑smart agriculture. Nature Climate Change, 4, 1068–1072.

Llorens, J. et al. (2010). Variable‑rate dosing in viticulture. Crop Protection, 29, 239–248.

Lynch, J. et al. (2020). Demonstrating GWP*. Environmental Research Letters, 15, 044023.

Messina, C. D. et al. (2018). Integrating crop models and genomics. EJA, 100, 151–162.

Millar, N. et al. (2010). Nitrogen fertilizer management protocol. Mitigation and Adaptation Strategies for Global Change, 15, 185–204.

Montes, F. et al. (2013). Manure methane mitigation. Journal of Animal Science, 91, 5070–5094.

Mullet, J. E. et al. (2014). Energy sorghum genetics. Journal of Experimental Botany, 65, 3479–3489.

Nelson, D. W., & Sommers, L. E. (1996). Total carbon and organic matter. In Methods of Soil Analysis.

Niles, M. T. et al. (2019). Dairy farmer manure management decisions. Environmental Research Letters, 14, 053004.

Ogle, S. et al. (2010). GHG mitigation literature review for agriculture. USDA.

Padeyanda, Y. et al. (2016). Food waste LCA. Journal of Material Cycles and Waste Management, 18, 493–508.

Parton, W. J. et al. (1998). DAYCENT model description. Global Planetary Change, 19, 35–48.

Peteinatos, G. G. et al. (2015). Precision harrowing. In Precision Agriculture.

Pinguet, B. (2020). Drone technology in sustainable agriculture.

Powlson, D. et al. (1996). Evaluation of Soil Organic Models. Springer.

Reis, S. et al. (2016). Nitrogen management. Environmental Research Letters, 11, 120205.

ReFED. Rethink Food Waste Through Economics and Data.

Ribaudo, M. et al. (2011). Nitrogen in Agricultural Systems. USDA‑ERS ERR‑127.

Salemdeeb, R. et al. (2017). Environmental evaluation of food waste prevention. Waste Management, 59, 442–450.

Schahczenski, J., & Hill, H. (2009). Agriculture, Climate Change and Carbon Sequestration.

Schepers, J. S., & Raun, W. R. (2008). Nitrogen in Agricultural Systems.

Sehy, U. et al. (2003). Nitrous oxide fluxes in maize. Agriculture, Ecosystems & Environment, 99, 97–111.

Seré, C. et al. (1996). World Livestock Production Systems. FAO.

Shi, Y. et al. (2016). UAVs for phenotyping. PLOS ONE.

Shockley, J. M. et al. (2015). Auto‑steer navigation economics. Journal of Agricultural and Applied Economics, 43, 57–75.

Shurson, G. (2020). Recycling food waste into feed. Sustainability, 12, 7071.

Smith, P. et al. (2014). AFOLU—Mitigation of climate change. IPCC AR5.

Soil Survey Staff (USDA). SSURGO database.

Solanelles, F. et al. (2006). Electronic control for pesticide application. Biosystems Engineering, 95, 473–481.

SARE (2017). Cover crops and pollution prevention.

Sutton, M. A. et al. (2021). The nitrogen decade. One Earth, 4, 10–14.

Swan, A. et al. (2015). COMET‑Planner companion report.

Tanksley, S. et al. (1982). Mapping quantitative traits. Heredity.

Tibbs Cortes, L. et al. (2021). GWAS status and prospects. Plant Genome.

Thomson, A. M. et al. (2019). Supply chain sustainability metrics. In Sustainability Perspectives.

Timmermann, C. et al. (2003). Economic impact of site‑specific weed control. Precision Agriculture, 4, 249–260.

Topp, C. N. et al. (2013). Root architecture QTLs. PNAS, 110, E1695–E1704.

Tricarico, J. M. et al. (2020). Dairy sustainability in low‑income countries. Journal of Dairy Science, 103, 9791–9802.

Trost, B. et al. (2013). Irrigation, SOC, and N₂O emissions. Agronomy for Sustainable Development, 33, 733–749.

Ubbens, J., & Stavness, I. (2017). Deep plant phenomics. Frontiers in Plant Science.

UNEP (2021). Food Waste Index Report.

USDA (2016). Soil health and no‑till transformations.

USDA (2018). America’s Diverse Family Farms.

USDA‑ERS (2019). Agricultural Research Funding in Public and Private Sectors.

US EPA (2021a). Inventory of U.S. GHG Emissions and Sinks.

US EPA (2021b). Overview of Greenhouse Gases.

NRCS (2016). Reduction in Annual Fuel Use from Conservation Tillage.

Utkina, I. (2017). Global carbon stocks soil map (FAO).

Van Eeuwijk, F. et al. (2018). Modeling phenotyping strategies. Plant Science.

Viscarra Rossel, R. et al. (2008). Digital camera use for soil C estimation. Biosystems Engineering, 100, 149–159.

Viscarra Rossel, R. et al. (2016). Global soil spectral library. Earth‑Science Reviews, 155, 198–230.

White, R. R., & Hall, M. B. (2017). Impacts of removing animals from U.S. agriculture. PNAS, 114, E10301–E10308.

Wielopolski, L. et al. (2000). Soil carbon via neutron scattering. IEEE Transactions on Nuclear Science, 47, 914–917.

Wijewardane, N. K. et al. (2020). Multi‑sensing penetrometer. Soil & Tillage Research, 199, 104604.

Willett, W. et al. (2019). EAT‑Lancet healthy diets. The Lancet, 393, 447–492.

Wood, S., & Cowie, A. (2004). GHG emission factors for fertilizer production. IEA Bioenergy.

Xu, Y. et al. (2020). Enhancing genetic gain via genomic selection. Plant Communications, 1, 100005.

Yang, K. W. et al. (2021). Integrating remote sensing with crop growth models. in silico Plants.

Yang, W. et al. (2020). Crop phenomics. Molecular Plant, 13, 187–214.

Zhang, H., & Forde, B. G. (1998). MADS‑box gene regulating root architecture. Science, 279, 407–409.

Zhu, H., Li, C., & Gao, C. (2020). CRISPR–Cas in agriculture. Nature Reviews Molecular Cell Biology, 21, 661–677.

zu Ermgassen, E. K. H. J., Balmford, A., & Salemdeeb, R. (2016). Recycle food waste. Science, 352, 1526.

Downloads

Published

2021-06-28

Issue

Section

CAST Commentaries

How to Cite

Baltensperger, D., Basu, M., Dou, Z., Flis, S., Galligan, D., Matlock, M., Morgan, C., Reed, D., Rice, C. W., Shurson, G., Thomasson, A., Thompson, A. M., Thomson, A., Tricarico, J. M., & Yu, J. (2021). The Role of Agricultural Science and Technology in Climate 21 Project Implementation. Council for Agricultural Science and Technology (CAST). https://doi.org/10.62300/0p2xj465

Similar Articles

21-24 of 24

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)