Soybean [Glycine max (L.) Merr.] seeding rate research across North America is typically conducted in small geo-political regions where environmental effects on the seeding rate × yield relationship are minimized. Data from 211 individual field studies (∼21,000 data points, 2007-2017) were combined from across North America ranging in yield from 1,000-7,500 kg ha −1 . Cluster analysis was used to stratify each individual field study into similar environmental (soil × climate) clusters and into high (HYL), medium (MYL), and low (LYL) yield levels. Agronomically optimal seeding rates (AOSR) were calculated and Monte Carlo risk analysis was implemented. Within the two northern most clusters the AOSR was higher in the LYL followed by the MYL and then HYL. Within the farthest south cluster, a relatively Abbreviations: AOSR, agronomically optimal seeding rate; CIPAR, cumulatively intercepted photosynthetically active radiation; HYL, high yield level; LYL, low yield level; MYL, medium yield level; NCCPI, national commodity crop productivity index; PAR, photosynthetically active radiation; VRS, variable rate seeding.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Predicting soybean [Glycine max (L.) Merr.] seed yield is of interest for crop producers to make important agronomic and economic decisions. Evaluating the soybean canopy across a range of common agronomic practices, using canopy measurements, provides a large inference for soybean producers. The individual and synergistic relationships between fractional green canopy cover (FGCC), photosynthetically active radiation (PAR) interception, and a normalized difference vegetative index (NDVI) measurements taken throughout the growing season to predict soybean seed yield in North Dakota, USA, were investigated in 12 environments. Canopy measurements were evaluated across early and late planting dates, 407,000 and 457,000 seeds ha−1 seeding rates, 0.5 and 0.8 relative maturities, and 30.5 and 61 cm row spacings. The single best yield predictor was an NDVI measurement at R5 (beginning of seed development) with a coefficient of determination of 0.65 followed by an FGCC measurement at R5 (R2 = 0.52). Stepwise and Lasso multiple regression methods were used to select the best prediction models using the canopy measurements explaining 69% and 67% of the variation in yield, respectively. Including plant density, which can be easily measured by a producer, with an individual canopy measurement did not improve the explanation in yield. Using FGCC to estimate yield across the growing season explained a range of 49% to 56% of yield variation, and a single FGCC measurement at R5 (R2 = 0.52) being the most efficient and practical method for a soybean producer to estimate yield.

North Dakota soybean [Glycine max (L.) Merr.] seeding rate and row spacing varies across the state due to climate factors. Eight soybean seeding rates (starting at 80,000 and increasing by 20,000 live seeds ac −1 increments) and row spacing (12 and 24 inches) were evaluated in 15 environments in 2017-2018 to quantify established plant densities, seed yield, and plant loss occurring during the season. Planting at a 12-inch row spacing yielded 2.7 bu ac −1 greater than 24-inch row spacing and provided $33 ac −1 greater net profit on average. Following plant establishment, 6.6% in-season plant loss occurred on average. Using 180,000 to 200,000 live seed ac −1 had higher yields than seeding rates of 120,000 or less. Maximum net partial profit based on seeding rate was 80,800, 105,300, and 167,500 live seed ac −1 for seed costs of $57.80, $50.80, and $33, respectively, for 140,000 seeds. North Dakota's current recommendation of 150,000 established plants ac −1 is in the range to optimize yield but will likely not optimize profit based on seed costs and current market values. North Dakota farmers are recommended to use 12-inch row spacing instead of 24 inches.

Planting date (PD), seeding rate (SR), relative maturity (RM) of cultivars, and row spacing (RS) are primary management factors affecting soybean (Glycine max (L.) Merr.) yield. The individual and synergistic effects of PD, SR, RM, and RS on seed yield and agronomic characteristics in North Dakota were herein investigated. Early and late PD, early and late RM cultivars, two SR (408,000 and 457,000 seed ha−1), and two RS (30.5 and 61 cm) were evaluated in four total environments in 2019 and 2020. Maximizing green canopy cover prior to the beginning of flowering improved seed yield. Individual factors of early PD and narrow RS resulted in yield increase of 311 and 266 kg ha−1, respectively. The combined factors of early PD, late RM, high SR, and narrow RS improved yield by 26% and provided a $350 ha−1 partial profit over conventional practices. Canopy cover and yield had relatively weak relationships with r2 of 0.36, 0.23, 0.14, and 0.21 at the two trifoliolate, four trifoliolate, beginning of flowering, and beginning of pod formation soybean growth stages, respectively. Producers in the most northern soybean region of the USA should combine early planting, optimum RM cultivars, 457,000 seed ha−1 SR, and 31 cm RS to improve yield and profit compared to current management practices.

Agronomic practices, such as planting date, seeding rate, and genotype, commonly influence hard red spring wheat (HRSW, Triticum aestivum L. emend. Thell.) production. Determining the agronomic optimum seeding rate (AOSR) of newly developed hybrids is needed as they respond to seeding rates differently from inbred cultivars. The objectives of this research were to determine the AOSR of new HRSW hybrids, how seeding rate alters their various yield components, and whether hybrids offer increased end-use quality, compared to conventional cultivars. The performance of two cultivars (inbreds) and five hybrids was evaluated in nine North Dakota environments at five seeding rates in 2019−2020. Responses to seeding rate for yield and protein yield differed among the genotypes. The AOSR ranged from 3.60 to 5.19 million seeds ha−1 and 2.22 to 3.89 million seeds ha−1 for yield and protein yield, respectively. The average AOSR for yield for the hybrids was similar to that of conventional cultivars. However, the maximum protein yield of the hybrids was achieved at 0.50 million seeds ha−1 less than that of the cultivars tested. The yield component that explained the greatest proportion of differences in yield as seeding rates varied was kernels spike−1 (r = 0.17 to 0.43). The end-use quality of the hybrids tested was not superior to that of the conventional cultivars, indicating that yield will likely be the determinant of the economic feasibility of any future released hybrids.