A gronomy J our n al • Volu me 10 0 , I s sue 4 • 2 0 0 8 ABSTRACT Th e widespread adoption of glyphosate [N-(phosphonylmethyl)-glycine]-resistant soybean [Glycine max (L.) Merr.] and the increased cost of soybean seed have generated interest in determining the minimum plant population needed for maximum yield. Th e objective of this study was to determine yield and economic return responses to plant population for normal and late planting dates. Cultivars with relative maturities of 2.8 to 4.9 were planted at fi ve seeding rates (43,000 to 560,000 seeds ha -1 ) in May and/or June in 38-cm rows during 2003 to 2005. Th e eff ect of plant population on both yield and economic return was explained with a variation of a Mitscherlich equation. Optimum plant population (OPP) and economically optimum plant population (EOPP) were defi ned as those resulting in 95% of the estimated yield or estimated economic return, respectively, at the maximum plant population. Optimum plant population ranged from 108,000 to 232,000 plants ha -1 for May planting dates and 238,000 to 282,000 plants ha -1 for June planting dates. Economically optimum plant populations were 7 to 33% less than OPPs. Complete canopy cover at R1 produced maximum yield in 8 of 10 comparisons. Th ese results suggest that seeding rates below those that are currently recommended could lower seed costs without reducing yield.

A B S T R A C TThe effects of supplemental nitrogen (N) on soybean [Glycine max (L.) Merr.] seed yield have been the focus of much research over the past four decades. However, most experiments were region-specific and focused on the effect of a single N-related management choice, thus resulting in a limited inference space. Here, we composited data from individual experiments conducted across the US that examined the effect of N fertilization on soybean yield. The combined database included 207 environments (experiment × year combinations) for a total of 5991 N-treated soybean yields. We used hierarchical modeling and conditional inference tree analysis on the combined dataset to establish the relationship and contribution of several N management choices on soybean yield. The N treatment variables were: N-application (single or split), N-method (soil incorporated, foliar, etc.), Ntiming (pre-plant, at a reproductive stage, etc.), and N-rate (from a 0 N control to as much as 560 kg ha). Of the total yield variability, 68% was associated with the effect of environment, whereas only a small fraction of that variability (< 1%) was attributable to each N variable. Averaged over all experiments, a single N application and the split N application were 60 and 110 kg ha −1 greater yielding than the zero N control treatment, respectively. A split N application with more than one method (e.g., soil incorporated and foliar) resulted in 120 kg ha −1 greater yield than zero N plots. Split N application between planting and reproductive stages (Rn) resulted in greater yield than zero N and single application during a Rn; however, the effect was not significantly different than N application at other growth stages. Increasing the N rate increased the environment average soybean yield; however, 93% of the environment-specific N-rate responses were not significant which suggested a minimal effect of N across the examined region. A large yield variability was observed among environments E-mail address: mourtzinis@wisc.edu (S. Mourtzinis).Abbreviations: BNF, biological nitrogen fixation; C, check (no nitrogen was applied); MM, major management practices; N, nitrogen; N-rate, nitrogen rate; N-application, number of nitrogen applications; N-method, method of nitrogen application; N-timing, timing of nitrogen application (growth stage/s); P, all nitrogen was applied at planting only; PR, split nitrogen application at planting and reproductive growth stages; pP, all nitrogen was applied at pre-planting only; Rn, reproductive growth stage; R, all nitrogen was applied at a reproductive growth stage only; RR, split nitrogen application at two reproductive growth stages; V, all nitrogen was applied at a vegetative growth stage only; Vn, vegetative growth stage MARKwithin the same N rates, which was attributed to growing environment differences (e.g., in-season weather conditions, soil type etc.) and non-N related management (e.g., irrigation). Conditional inference tree analysis identified N-timing and N-rate to be conditional to irriga...

Elevated soybean [Glycine max (L.) Merr.] prices have spurred interest in maximizing soybean seed yield and has led growers to increase the number of inputs in their production systems. However, little information exists about the effects of high‐input management on soybean yield and profitability. The purpose of this study was to investigate the effects of individual inputs, as well as combinations of inputs marketed to protect or increase soybean seed yield, yield components, and economic break‐even probabilities. Studies were established in nine states and three soybean growing regions (North, Central, and South) between 2012 and 2014. In each site‐year both individual inputs and combination high‐input (SOYA) management systems were tested. When averaged between 2012 and 2014, regional results showed no seed yield responses in the South region, but multiple inputs affected seed yield in the North region. In general, the combination SOYA inputs resulted in the greatest yield increases (up to 12%) compared to standard management, but Bayesian economic analysis indicated SOYA had low break‐even probabilities. Foliar insecticide had the greatest break‐even probabilities across all environments, although insect pressure was generally low across all site‐years. Soybean producers in North region are likely to realize a greater response from increased inputs, but producers across all regions should carefully evaluate adding inputs to their soybean management systems and ensure that they continue to follow the principles of integrated pest management.

Numerous studies have been conducted to determine if decreasing row widths will increase yields of corn and soybean. Full‐season corn (Zea mays) yields typically do not increase as row widths decrease south of 43°N latitude (about the Wisconsion‐Iowa border extended east and west) in the United States. Soybean (Glycine max) yields follow a similar but less consistent trend. A corn or soybean crop must produce sufficient leaf area for maximum radiation interception just prior to or during flowering and seed set to achieve maximum yields. Full‐season corn hybrids and soybean varieties at recommended plant densities in wide rows in the central and southern United States have ample time and heat units for crop growth to intercept maximum radiation prior to flowering, making narrow row widths unnecessary for maximum yields. Conversely, full‐season corn and soybean in the northern United States and short‐season corn and soybean in central and southern United States have limited time and heat units to reach maximum radiation interception prior to flowering. Based on these observations, wide rows for full‐season corn and soybean in the central and southern United States are usually sufficient for maximum yields.

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