A machine learning interpretation of the contribution of foliar fungicides to soybean yield in the north-central United States.
Saved in:
| Title: | A machine learning interpretation of the contribution of foliar fungicides to soybean yield in the north-central United States. |
|---|---|
| Authors: | Shah DA; Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA. dashah81@ksu.edu., Butts TR; Department of Crop, Soil, and Environmental Sciences, University of Arkansas System Division of Agriculture, Lonoke, AR, 72086, USA., Mourtzinis S; Agstat Consulting, Athens, Greece., Rattalino Edreira JI; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA., Grassini P; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA., Conley SP; Department of Agronomy, University of Wisconsin-Madison, Madison, WI, 53706, USA., Esker PD; Department of Plant Pathology and Environmental Microbiology, Pennsylvania State University, University Park, PA, 16802, USA. |
| Source: | Scientific reports [Sci Rep] 2021 Sep 21; Vol. 11 (1), pp. 18769. Date of Electronic Publication: 2021 Sep 21. |
| Publication Type: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S. |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
Be the first to leave a comment!
