Delineating Soybean Maturity Groups across the United States. (1st July 2017)

• Record Type: Journal Article
• Authors: Mourtzinis, Spyridon; Conley, Shawn P.
• Is Part Of: Agronomy Journal. Volume 109:Number 4(2017)
• Page Start: 1397
• Page End: 1403
• Publication Date: 2017-07-01
• Subjects: Agronomy -- Periodicals; 630
• DOI: 10.2134/agronj2016.10.0581
• Languages: English
• ISSNs: 0002-1962

Abstract

Abstract : Core Ideas: Seven maturity group zones were identified across the United States. The width of maturity group zones 4 and 5 cover the largest geographic region. Maturity group zones were defined by a downward deflection of the maturity group lines. Maturity group adaptation zones need to be continuously monitored and adjusted. Photoperiod and in‐season temperature are the primary factors that dictate the region where a soybean [ Glycine max (L.) Merr.] variety is adapted. The first study that defined hypothetical maturity groups (MGs) zones across the US was 45 yr ago, and the most recent used data up to 2003. Although, photoperiod remains constant, climatic conditions, management practices, and soybean genetics have changed during the past decades. Therefore, the objective of this study was to re‐delineate soybean MGs across the US using recent genetics. Soybean MG‐specific yield data from variety trials conducted in 2005–2015 were aggregated from 312 locations across the United States. Seven MG zones were identified starting from MG = 0 in North Dakota to MG = 6 in southern Georgia and South Carolina. The width of MG = 4 and 5 zones cover the largest geographic region extending from north of latitude 28°N to 39°N. Additionally, in contrast to previous studies, the MG zones were defined by a downward deflection of the MG lines moving from East to West rather than convex parallel lines. Due to the strong effect of planting date on MG selection, a multi‐location‐year experiment should be conducted across the United States using multiple MGs evaluated in several planting dates. Such study could provide further insight on location‐specific optimum MG. Overall results, update current knowledge by providing valuable information for decision making and regional modeling. This work highlights the need to continuously monitor and adjust the MG zones due to the constantly changing climate, management, and genetics.