Adrian Correndo
Assistant Professor
Pick Family Chair in Sustainable Cropping Systems
Email:
Phone:
519-824-4120 x53572
Education:
B.S. (Agronomy) University of Buenos Aires;
M.S. (Soil Science) University of Buenos Aires;
Ph.D. (Agronomy) Kansas State University
Location:
Crop Science Building
Room:
226 CRSC
Dr. Correndo is the Research Chair for the The Pick Family Chair in Sustainable Cropping Systems. Martin and Denise established The Pick Family Chair in Sustainable Cropping Systems to develop and introduce effective, simple to use and widely acceptable cropping systems that deal with the issue of soil degradation.
“I certainly look forward to substantially contribute to the development and education on science-based solutions for sustainable farming systems in Ontario by identifying and promoting best soil and crop management practices. On this endeavor, my work heavily relies on maintaining and leveraging the value and legacy of multiple long-term trials at the Elora Research Station, where management practices such as tillage, crop rotation, cover crops, and fertilization management are the subject of study. Finally, I find applied statistics and reproducible programming to be essential for the development of accessible and cross-scale digital tools. I want to put modern data analytics like machine learning and Bayesian statistics to the service of our agricultural communities.”
Previously, Dr. Correndo worked on research and extension in soil fertility and crop nutrition as the Assistant Agronomist (2008-2018) for the Latin America Southern Cone Program of the former International Plant Nutrition Institute (IPNI); and from 2018 to 2023 in Kansas State University (United States) as a Graduate Research Assistant while pursuing his Ph.D. in Agronomy (2018-2021), and as a Post-doctoral Fellow (2022-2023) working on research and extension in corn and soybean production.
Courses:
Relevant Links:
Selected Publications:
Correndo, A.A., Pearce, A., Bolster, C., Spargo, J., Osmond, D., and Ciampitti, I.A., 2023. The soiltestcorr R package: An accessible framework for reproducible correlation analysis of crop yield and soil test data. Submitted to SoftwareX 21, 101275, https://doi.org/10.1016/j.softx.2022.101275
Correndo, A.A., Moro Rosso, L.H., Hernandez, C.H., Bastos, L.M., Nieto, L., Holzworth, D., Ciampitti, I.A., 2022. metrica: an R package to evaluate prediction performance of regression and classification point-forecast models. Journal of Open Source Software, 7(79), 4655, https://joss.theoj.org/papers/10.21105/joss.04655
Correndo, A.A., McArtor, B., Prestholt, A., Hernandez, C., Kyveryga, P., and Ciampitti , I.A., 2022. Interactive Soybean Variable-Rate Seeding Simulator for Farmers. Agron. J. 114, 3554-3565, https://doi.org/10.1002/agj2.21181
Correndo, A.A., Adee, E., Moro Rosso, L.H., Tremblay, N., Vara Prasad, P.V., Du, J., and Ciampitti, I.A., 2022. Footprints of corn nitrogen management on the following soybean crop. Agron. J. 1-14. https://doi.org/10.1002/agj2.21023
Correndo, A.A., Tremblay, N., …Ciampitti, I.A. et al., 2021. Unraveling uncertainty drivers of the maize yield response to nitrogen: A Bayesian and machine learning approach. Agr. For. Meteorol. 311, 108668. https://doi.org/10.1016/j.agrformet.2021.108668
Correndo, A.A., Gutierrez-Boem, F.H., Garcia, F.O.,… Salvagiotti, F., 2021. Attainable yield and soil texture as drivers of maize response to nitrogen: a synthesis analysis for Argentina. Field Crops Res. 273, 108299. https://doi.org/10.1016/j.fcr.2021.108299
Correndo, A.A., Fernandez, J., Prasad, V., Ciampitti, I.A., 2021. Do water and nitrogen management practices impact grain quality in maize? Agronomy 11(9), 1851. https://doi.org/10.3390/agronomy11091851
Correndo, A.A., Hefley, T., Holzworth, D., Ciampitti, I.A., 2021. Revisiting linear regression to test agreement in continuous predicted-observed datasets. Agr. Syst. 192, 103194. https://doi.org/10.1016/j.agsy.2021.103194
Correndo, A.A., Moro Rosso, L.H., Ciampitti, I.A., 2021. Retrieving and processing agro-meteorological from API-client sources using R software. BMC Res. Notes 14, 205. https://doi.org/10.1186/s13104-021-05622-8
Correndo, A.A., Rubio, G., Garcia, F.O., Ciampitti, I.A., 2021. Subsoil-potassium depletion accounts for the nutrient budget in high-potassium agricultural soils. Sci. Rep. 11, 11597. https://doi.org/10.1038/s41598-021-90297-1
Correndo, A.A., Rotundo, J.L., Tremblay, N., et al., 2021. Assessing the uncertainty of maize yield with no nitrogen fertilization. Field Crops Res. 260, 107985. https://doi.org/10.1016/j.fcr.2020.107985
Correndo, A.A., Salvagiotti, F., García, F.O., Gutiérrez Boem, F.H., 2017. A modification of the arcsine-log calibration curve for analysing soil test value-relative yield relationships. Crop and Pasture Science 68 (3): 297-304. https://doi.org/10.1071/CP16444
