Defining optimal soybean seeding rates and associated risk across North America

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 small (±15,000 seeds ha−1) change in seeding rate from the MYL was required to reach the AOSR of the LYL and HYL, respectively. The increase in seeding rate to reach the LYL AOSR was relatively greater (5x) than the decrease to reach the HYL AOSR within the northern most cluster. Regardless, seeding rates below the AOSR presented substantial risk and potential yield loss, while seeding rates above provided slight risk reduction and yield increases. Specific to LYLs and MYLs, establishing and maintaining an adequate plant stand until harvest maximized yield regardless of the seeding rate, while maximizing seed number was important with lower seeding rates. These findings will help growers manage their soybean seed investment by adjusting seeding rates based upon the productivity of the environment.Fil: Gaspar, Adam P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mourtzinis, Spyridon. University of Wisconsin; Estados UnidosFil: Kyle, Don. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Galdi, Eric. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Lindsey, Laura E.. Ohio State University; Estados UnidosFil: Hamman, William P.. Ohio State University; Estados UnidosFil: Matcham, Emma G. University of Wisconsin; Estados UnidosFil: Kandel, Hans J.. North Dakota State University; Estados UnidosFil: Schmitz, Peder. North Dakota State University; Estados UnidosFil: Stanley, Jordan D.. North Dakota State University; Estados UnidosFil: Schmidt, John P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mueller, Daren S.. University of Iowa; Estados UnidosFil: Nafziger, Emerson D.. University of Illinois; Estados UnidosFil: Ross, Jeremy. University of Arkansas for Medical Sciences; Estados UnidosFil: Carter, Paul R.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Varenhorst, Adam J.. University of South Dakota; Estados UnidosFil: Wise, Kiersten A.. University of Kentucky; Estados UnidosFil: Ciampitti, Ignacio Antonio. Kansas State University; Estados UnidosFil: Carciochi, Walter Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Kansas State University; Estados UnidosFil: Chilvers, Martin I.. Michigan State University; Estados UnidosFil: Hauswedell, Brady. University of South Dakota; Estados UnidosFil: Tenuta, Albert U.. University of Guelph; CanadáFil: Conley, Shawn P.. University of Wisconsin; Estados Unido

Case Reports1. A Late Presentation of Loeys-Dietz Syndrome: Beware of TGFβ Receptor Mutations in Benign Joint Hypermobility

Background: Thoracic aortic aneurysms (TAA) and dissections are not uncommon causes of sudden death in young adults. Loeys-Dietz syndrome (LDS) is a rare, recently described, autosomal dominant, connective tissue disease characterized by aggressive arterial aneurysms, resulting from mutations in the transforming growth factor beta (TGFβ) receptor genes TGFBR1 and TGFBR2. Mean age at death is 26.1 years, most often due to aortic dissection. We report an unusually late presentation of LDS, diagnosed following elective surgery in a female with a long history of joint hypermobility. Methods: A 51-year-old Caucasian lady complained of chest pain and headache following a dural leak from spinal anaesthesia for an elective ankle arthroscopy. CT scan and echocardiography demonstrated a dilated aortic root and significant aortic regurgitation. MRA demonstrated aortic tortuosity, an infrarenal aortic aneurysm and aneurysms in the left renal and right internal mammary arteries. She underwent aortic root repair and aortic valve replacement. She had a background of long-standing joint pains secondary to hypermobility, easy bruising, unusual fracture susceptibility and mild bronchiectasis. She had one healthy child age 32, after which she suffered a uterine prolapse. Examination revealed mild Marfanoid features. Uvula, skin and ophthalmological examination was normal. Results: Fibrillin-1 testing for Marfan syndrome (MFS) was negative. Detection of a c.1270G > C (p.Gly424Arg) TGFBR2 mutation confirmed the diagnosis of LDS. Losartan was started for vascular protection. Conclusions: LDS is a severe inherited vasculopathy that usually presents in childhood. It is characterized by aortic root dilatation and ascending aneurysms. There is a higher risk of aortic dissection compared with MFS. Clinical features overlap with MFS and Ehlers Danlos syndrome Type IV, but differentiating dysmorphogenic features include ocular hypertelorism, bifid uvula and cleft palate. Echocardiography and MRA or CT scanning from head to pelvis is recommended to establish the extent of vascular involvement. Management involves early surgical intervention, including early valve-sparing aortic root replacement, genetic counselling and close monitoring in pregnancy. Despite being caused by loss of function mutations in either TGFβ receptor, paradoxical activation of TGFβ signalling is seen, suggesting that TGFβ antagonism may confer disease modifying effects similar to those observed in MFS. TGFβ antagonism can be achieved with angiotensin antagonists, such as Losartan, which is able to delay aortic aneurysm development in preclinical models and in patients with MFS. Our case emphasizes the importance of timely recognition of vasculopathy syndromes in patients with hypermobility and the need for early surgical intervention. It also highlights their heterogeneity and the potential for late presentation. Disclosures: The authors have declared no conflicts of interes

Management strategies for early- and late-planted soybean in the north-central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs

Management strategies for early‐ and late‐planted soybean in the north‐central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs

Management strategies for early- and late-planted soybean in the north-central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs.This article is published as Matcham, Emma G., Spyridon Mourtzinis, Shawn P. Conley, Juan I. Rattalino Edreira, Patricio Grassini, Adam C. Roth, Shaun N. Casteel et al. "Management strategies for early‐and late‐planted soybean in the north‐central United States." Agronomy Journal 112, no. 4 (2020): 2928-2943. doi:10.1002/agj2.20289. Posted with permission. 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

Defining optimal soybean seeding rates and associated risk across North America

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 small (±15,000 seeds ha−1) change in seeding rate from the MYL was required to reach the AOSR of the LYL and HYL, respectively. The increase in seeding rate to reach the LYL AOSR was relatively greater (5x) than the decrease to reach the HYL AOSR within the northern most cluster. Regardless, seeding rates below the AOSR presented substantial risk and potential yield loss, while seeding rates above provided slight risk reduction and yield increases. Specific to LYLs and MYLs, establishing and maintaining an adequate plant stand until harvest maximized yield regardless of the seeding rate, while maximizing seed number was important with lower seeding rates. These findings will help growers manage their soybean seed investment by adjusting seeding rates based upon the productivity of the environment.Fil: Gaspar, Adam P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mourtzinis, Spyridon. University of Wisconsin; Estados UnidosFil: Kyle, Don. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Galdi, Eric. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Lindsey, Laura E.. Ohio State University; Estados UnidosFil: Hamman, William P.. Ohio State University; Estados UnidosFil: Matcham, Emma G. University of Wisconsin; Estados UnidosFil: Kandel, Hans J.. North Dakota State University; Estados UnidosFil: Schmitz, Peder. North Dakota State University; Estados UnidosFil: Stanley, Jordan D.. North Dakota State University; Estados UnidosFil: Schmidt, John P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mueller, Daren S.. University of Iowa; Estados UnidosFil: Nafziger, Emerson D.. University of Illinois; Estados UnidosFil: Ross, Jeremy. University of Arkansas for Medical Sciences; Estados UnidosFil: Carter, Paul R.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Varenhorst, Adam J.. University of South Dakota; Estados UnidosFil: Wise, Kiersten A.. University of Kentucky; Estados UnidosFil: Ciampitti, Ignacio Antonio. Kansas State University; Estados UnidosFil: Carciochi, Walter Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Kansas State University; Estados UnidosFil: Chilvers, Martin I.. Michigan State University; Estados UnidosFil: Hauswedell, Brady. University of South Dakota; Estados UnidosFil: Tenuta, Albert U.. University of Guelph; CanadáFil: Conley, Shawn P.. University of Wisconsin; Estados Unido