scholarly journals The influence of winter annual grass litter on herbicide availability

Weed Science ◽  
2019 ◽  
Vol 67 (6) ◽  
pp. 702-709
Author(s):  
Shannon L. Clark ◽  
Paulo V. da Silva ◽  
Franck E. Dayan ◽  
Scott J. Nissen ◽  
Derek J. Sebastian
Keyword(s):  
Soil Surface ◽  
Grass Species ◽  
State University ◽  
Simulated Rainfall ◽  
Annual Grass ◽  
Colorado State University ◽  
Grass Litter ◽  
Initial Control ◽  
Liquid Chromatography Tandem Mass ◽  
Winter Annual

AbstractInvasive winter annual grass infestations on rangeland accumulate large quantities of litter on the soil surface, as plants senesce yearly and decompose slowly. It has been speculated that winter annual grass litter can adsorb soil-active herbicides and reduce overall performance. Three experiments were conducted from 2017 to 2018 at the Colorado State University Weed Research Laboratory to evaluate interception and subsequent desorption of herbicides applied to litter from three invasive winter annual grass species with simulated rainfall. Imazapic, rimsulfuron, and indaziflam were applied to medusahead [Taeniatherum caput-medusae (L.) Nevski], ventenata [Ventenata dubia (Leers) Coss.], and downy brome (Bromus tectorum L.) litter at two amounts (equivalent to 1,300 and 2,600 kg ha−1). Rainfall was simulated at 3, 6, 12, and 24 mm at 0, 1, and 7 d after herbicide application. Herbicide concentration from the collected rainfall was measured using liquid chromatography–tandem mass spectrometry. At 2,600 kg ha−1, B. tectorum herbicide interception was 84.3%, while V. dubia and T. caput-medusae averaged 76% herbicide interception. There were no differences in desorption among the three litter types. Simulated rainfall at 0 d after application recovered 100% of the intercepted rimsulfuron and imazapic from B. tectorum litter, while recovery decreased to 65% with rainfall at 1 or 7 d after application. Only 54% of indaziflam could be recovered at 0 d, and recovery decreased to 33% when rainfall was applied at 1 or 7 d after application. Applying soil-active herbicides before forecasted rain or tank mixing with a POST herbicide to provide initial control could potentially increase the amount of herbicide reaching the soil and provide more consistent invasive winter annual grass control.

A MODEL FOR DEVELOPING HIGH-QUALITY ONLINE COURSES: INTEGRATING A SYSTEMS APPROACH WITH LEARNING THEORY

2008 ◽  
Vol 12 (3) ◽  
Author(s):  
Maria Jean Puzziferro ◽  
Kaye Shelton
Keyword(s):  
Online Education ◽  
Design Theory ◽  
Systems Approach ◽  
Online Courses ◽  
Process Models ◽  
State University ◽  
High Quality ◽  
Colorado State University ◽  
Online Instructional Design ◽  
Online Course Development

As the demand for online education continues to increase, institutions are faced with developing process models for efficient, high-quality online course development. This paper describes a systems, team-based, approach that centers on an online instructional design theory (Active Mastery Learning) implemented at Colorado State University-Global Campus.

scholarly journals Preface: Modern Heterocycle Synthesis and Functionalization

Synlett ◽  
2021 ◽  
Vol 32 (02) ◽  
pp. 140-141
Author(s):  
Louis-Charles Campeau ◽  
Tomislav Rovis
Keyword(s):  
Active Pharmaceutical Ingredient ◽  
Associate Professor ◽  
Columbia University ◽  
State University ◽  
Heterocycle Synthesis ◽  
Colorado State University ◽  
University Of Toronto ◽  
Process Chemistry ◽  
The University ◽  
Small Molecule Therapeutics

obtained his PhD degree in 2008 with the late Professor Keith Fagnou at the University of Ottawa in Canada as an NSERC Doctoral Fellow. He then joined Merck Research Laboratories at Merck-Frosst in Montreal in 2007, making key contributions to the discovery of Doravirine (MK-1439) for which he received a Merck Special Achievement Award. In 2010, he moved from Quebec to New Jersey, where he has served in roles of increasing responsibility with Merck ever since. L.-C. is currently Executive Director and the Head of Process Chemistry and Discovery Process Chemistry organizations, leading a team of smart creative scientists developing innovative chemistry solutions in support of all discovery, pre-clinical and clinical active pharmaceutical ingredient deliveries for the entire Merck portfolio for small-molecule therapeutics. Over his tenure at Merck, L.-C. and his team have made important contributions to >40 clinical candidates and 4 commercial products to date. Tom Rovis was born in Zagreb in former Yugoslavia but was largely raised in southern Ontario, Canada. He earned his PhD degree at the University of Toronto (Canada) in 1998 under the direction of Professor Mark Lautens. From 1998–2000, he was an NSERC Postdoctoral Fellow at Harvard University (USA) with Professor David A. Evans. In 2000, he began his independent career at Colorado State University and was promoted in 2005 to Associate Professor and in 2008 to Professor. His group’s accomplishments have been recognized by a number of awards including an Arthur C. Cope Scholar, an NSF CAREER Award, a Fellow of the American Association for the Advancement of Science and a ­Katritzky Young Investigator in Heterocyclic Chemistry. In 2016, he moved to Columbia University where he is currently the Samuel Latham Mitchill Professor of Chemistry.

scholarly journals 260 Genetic prediction for first-service conception rate in Angus heifers using a random regression model

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 197-198
Author(s):  
Miguel A Sánchez-Castro ◽  
Milt Thomas ◽  
Mark Enns ◽  
Scott Speidel
Keyword(s):  
Conception Rate ◽  
Random Regression ◽  
State University ◽  
Base Function ◽  
Genetic Prediction ◽  
Colorado State University ◽  
Random Regression Model ◽  
Service Conception ◽  
Available Information ◽  
Angus Heifers

Abstract First-service conception rate (FSCR) can be defined as the probability of a heifer conceiving in response to her first artificial insemination (AI). Given the binary nature of its phenotypes, FSCR has been typically evaluated using animal threshold models (ATM). However, susceptibility of these models to the extreme-category problem (ECP) limits their ability to use all available information to calculate Expected Progeny Differences (EPD). Random regression models (RRM) represent an alternative method to evaluate binary traits, and they are not affected by ECP. Nevertheless, RRM were originally developed to analyze longitudinal traits, so their usefulness to evaluate traits with singly observed phenotypes remains unclear. Therefore, objectives herein were to evaluate the feasibility of a RRM genetic prediction for heifer FSCR by comparing its resulting EPD and genetic parameters to those obtained with a traditional ATM. Breeding and ultrasound records of 4,334 Angus heifers (progeny of 354 sires and 1,626 dams) collected between 1992 to 2019 at the Colorado State University Beef Improvement Center were utilized. Observations for FSCR (1, successful; 0, unsuccessful) were defined by fetal age at pregnancy inspections performed approximately 130 d post-AI. Traditional FSCR evaluation was performed using a univariate BLUP threshold animal model, whereas an alternative evaluation was performed by regressing FSCR on age at AI using a linear RRM with Legendre Polynomials as the base function. Heritability estimates were 0.03 ± 0.02 for the ATM and 0.005 ± 0.001 for the average age at AI with the RRM, respectively. Pearson and rank correlations between EPD obtained with each method were 0.63 and 0.60, respectively. The regression coefficient of RRM predictions on those obtained with the ATM was 0.095. In conclusion, these results suggested that although a RRM genetic prediction for FSCR was feasible, a considerable degree of re-ranking occurred between the two methodologies.

The Coaxium® Wheat Production System: A New Herbicide-Resistant System for Annual Grass Weed Control and Integrated Weed Management

2021 ◽  
Vol 32 (4) ◽  
pp. 151-157
Author(s):  
Raven A. Bough ◽  
Phillip Westra ◽  
Todd A. Gaines ◽  
Eric P. Westra ◽  
Scott Haley ◽  
...  
Keyword(s):  
Weed Management ◽  
Production System ◽  
Integrated Weed Management ◽  
State University ◽  
Wheat Production ◽  
Colorado State University ◽  
Herbicide Resistant ◽  
System A ◽  
Grass Weed ◽  
Global Food

The authors discuss the importance of wheat as a global food source and describe a novel multi-institutional, public-private partnership between Colorado State University, the Colorado Wheat Research Foundation, and private chemical and seed companies that resulted in the development of a new herbicide-resistant wheat production system.

Urochloa platyphylla (broadleaf signalgrass).

2021 ◽  
Author(s):  
Julissa Rojas-Sandoval ◽  
Pedro Acevedo-Rodríguez
Keyword(s):  
Environmental Conditions ◽  
Crop Residue ◽  
Soil Surface ◽  
Grass Species ◽  
Crop Fields ◽  
Wide Range ◽  
Germinating Seeds

Abstract U. platyphylla is a weedy grass species commonly found in disturbed, open and sandy sites such as crop fields, ditches and roadsides. It is considered a troublesome weed because of its tolerance to some herbicides principally in maize plantations (Chamblee et al., 1982; Gallaher et al.,1999). U. platyphylla is highly adaptable and it is able to germinate and grow throughout a wide range of soil and environmental conditions (Burke et al., 2003). Additionally, its seeds may remain on the crop residue until pre-emergence herbicides are no longer effective in controlling the germinating seeds, at which time the seeds fall to the soil surface and germinate (Alford et al., 2005).

scholarly journals Grass Canopy Architecture Influences Temperature Exposure at Soil Surface

Fire ◽  
2018 ◽  
Vol 1 (3) ◽  
pp. 35 ◽  
Author(s):  
Xiulin Gao ◽  
Dylan Schwilk
Keyword(s):  
Fire Regime ◽  
Fire Behavior ◽  
Soil Surface ◽  
Grass Species ◽  
Canopy Architecture ◽  
Height Ratio ◽  
Biomass Density ◽  
Litter Flammability ◽  
Temperature Exposure ◽  
Density And Biomass

There is increasing recognition that plant traits contribute to variations in fire behavior and fire regime. Diversity across species in litter flammability and canopy flammability has been documented in many woody plants. Grasses, however, are often considered homogeneous fuels in which any flammability differences across species are attributable to biomass differences alone and therefore are of less ecological interest, because biomass is hugely plastic. We examined the effect of grass canopy architecture on flammability across eight grass species in short grass steppe of New Mexico and Texas. To characterize grass canopy architecture, we measured biomass density and “biomass-height ratio” (the ratio of canopy biomass above 10 cm to that of biomass below 10 cm). Indoor flammability experiments were performed on air-dried individual plants. As expected, plant biomass influenced all flammability measures. However, biomass-height ratio had additional negative effect on temperature exposure at soil surface (accumulation of mean temperature >100 °C) in well-cured grasses, which is an important fire behavior metric predicting soil heating and meristem survival. This canopy architecture effect, however, needs further investigation to be isolated from biomass density due to correlation of these two traits. This result demonstrates the potential for species-specific variation in architecture to influence local fire effects in grasses.

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