Characterizing genotype × Management interactions on soybean seed yield

David A. Marburger, Bryson J. Haverkamp, Randall G. Laurenz, John M. Orlowski, Eric W. Wilson, Shaun N. Casteel, Chad D. Lee, Seth L. Naeve, Emerson D. Nafziger, Kraig L. Roozeboom, William J. Ross, Kurt D. Thelen, Shawn P. Conley

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Increased soybean [Glycine max (L.) Merr.] commodity prices in recent years have generated interest in high-input systems to increase yield. The objective of this study was to evaluate the effects of current, high-yielding cultivars under high-and low-input systems on soybean yield and yield components. Research trials were conducted at 19 locations spanning nine states from 2012 to 2014. At each location, six high-yielding cultivars were grown under three input systems: (i) standard practice (SP, current recommended practices), (ii) high-input treatment consisting of a seed treatment fungicide, insecticide, nematistat, inoculant, and lipo-chitooligosaccharide (LCO); soil-applied N fertilizer; foliar LCO, fertilizer, antioxidant, fungicide and insecticide (SOYA), and (iii) SOYA minus foliar fungicide (SOYA-FF). An individual site-year yield analysis found only 3 of 53 (5.7%) site-years examined had a significant cultivar × input system interaction, suggesting cultivar selection and input system decisions can remain independent. Across all site-years, the SOYA and SOYA-FF treatments yielded 231 (5.5%) and 147 kg ha–1 (3.5%) more than the SP, and input system differences were found among maturity groups. Yield component measurements (seeds m–2, seed mass, early-season and final plant stand, pods plant–1, and seeds pod–1) indicated positive yield responses were due to increased seeds m–2 and seed mass. While both high-input systems increased yield on average, grower return on investment (ROI) would be negative given today’s commodity prices. These results further support the use of integrated pest management principles for making input decisions instead of using prophylactic applications to maximize soybean yield and profitability.

Original languageEnglish (US)
Pages (from-to)786-796
Number of pages11
JournalCrop Science
Volume56
Issue number2
DOIs
StatePublished - Mar 1 2016

Bibliographical note

Publisher Copyright:
© Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved.

Fingerprint

Dive into the research topics of 'Characterizing genotype × Management interactions on soybean seed yield'. Together they form a unique fingerprint.

Cite this