Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
-
- Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research (3)
- Arkansas Agricultural Experiment Station Research Series (2)
- Department of Agronomy and Horticulture: Faculty Publications (2)
- Agricultural and Environmental Sciences Faculty Research (1)
- Department of Biological Systems Engineering: Dissertations and Theses (1)
Articles 1 - 10 of 10
Full-Text Articles in Entire DC Network
Integration Of Cover Crops Into Midwest Corn-Soybean Cropping Systems And Potential For Weed Suppression, Joshua S. Wehrbein
Integration Of Cover Crops Into Midwest Corn-Soybean Cropping Systems And Potential For Weed Suppression, Joshua S. Wehrbein
Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research
Cover crops have potential to provide benefits to agricultural systems, such as improved soil productivity, nutrient scavenging, weed suppression, and livestock forage. There are several challenges associated with cover crop integration into traditional Midwest corn-soybean cropping systems. One of these challenges is timely establishment in the fall, which is limited by the relatively late harvest of corn and soybean. Cover crop effectiveness is related to the amount of biomass produced, thus maximizing the growth period in the fall is desired. To address this challenge, we evaluated the potential to utilize early-season soybean maturity groups (MGs) to allow for earlier soybean …
Understanding Nitrogen Limitation In Soybean, Nicolas Cafaro La Menza
Understanding Nitrogen Limitation In Soybean, Nicolas Cafaro La Menza
Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research
Meeting soybean demand on existing cropland area for a global population of 9.7 billion people by the year 2050 requires narrowing the existing gap between average producer yield and yield potential. Soybean relies on two sources on nitrogen (N): biological N2 fixation and indigenous soil N supply. As soybean yield continues to increase, it seems critical to know if there is a yield level at which potential contribution of indigenous nitrogen sources and fixation becomes insufficient to meet crop N requirements for high yields, while still maintaining or increasing protein and oil concentration. This study evaluated N limitation across 29 …
Arkansas Soybean Research Studies 2018, Jeremy Ross
Arkansas Soybean Research Studies 2018, Jeremy Ross
Arkansas Agricultural Experiment Station Research Series
Arkansas is the leading soybean-producing state in the mid-southern United States. Arkansas ranked 11th in soybean production in 2018 when compared to the other soybean-producing states in the U.S. The state represents 3.7% of the total U.S. soybean production and 3.7% of the total acres planted in soybean in 2018. The 2018 state soybean average was 50.5 bushels per acre, half a bushel lower than the state record set in 2017. The top five soybean-producing counties in 2018 were Mississippi, Desha, Phillips, Arkansas, and Poinsett Counties (Table 1). These five counties accounted for 33.7% of soybean production in Arkansas in …
Arkansas Soybean Performance Tests 2019, J. F. Carlin, R. D. Bond, J. A. Still
Arkansas Soybean Performance Tests 2019, J. F. Carlin, R. D. Bond, J. A. Still
Arkansas Agricultural Experiment Station Research Series
Soybean variety and strain performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture’s Arkansas Crop Variety Improvement Program. The tests provide information to companies developing varieties and/or marketing seed within the State, and aid the Arkansas Cooperative Extension Service in formulating variety recommendations for soybean producers.
Glycerol-3-Phosphate Mediates Rhizobia-Induced Systemic Signaling In Soybean, M. B. Shine, Qing-Ming Gao, R. V. Chowda-Reddy, Asheesh K. Singh, Pradeep Kachroo, Aardra Kachroo
Glycerol-3-Phosphate Mediates Rhizobia-Induced Systemic Signaling In Soybean, M. B. Shine, Qing-Ming Gao, R. V. Chowda-Reddy, Asheesh K. Singh, Pradeep Kachroo, Aardra Kachroo
Plant Pathology Faculty Publications
Glycerol-3-phosphate (G3P) is a well-known mobile regulator of systemic acquired resistance (SAR), which provides broad spectrum systemic immunity in response to localized foliar pathogenic infections. We show that G3P-derived foliar immunity is also activated in response to genetically-regulated incompatible interactions with nitrogen-fixing bacteria. Using gene knock-down we show that G3P is essential for strain-specific exclusion of non-desirable root-nodulating bacteria and the associated foliar pathogen immunity in soybean. Grafting studies show that while recognition of rhizobium incompatibility is root driven, bacterial exclusion requires G3P biosynthesis in the shoot. Biochemical analyses support shoot-to-root transport of G3P during incompatible rhizobia interaction. We describe …
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Department of Biological Systems Engineering: Dissertations and Theses
Mid-late season weeds are those that escape the early season herbicide applications and those that emerge late in the season. They might not affect the crop yield, but if uncontrolled, will produce a large number of seeds causing problems in the subsequent years. In this study, high-resolution aerial imagery of mid-season weeds in soybean fields was captured using an unmanned aerial vehicle (UAV) and the performance of two different automated weed detection approaches – patch-based classification and object detection was studied for site-specific weed management. For the patch-based classification approach, several conventional machine learning models on Haralick texture features were …
Rapid Profiling Of Soybean Aromatic Compounds Using Electronic Nose, Ramasamy Ravi, Ali Taheri, Durga Khandekar, Reneth Millas
Rapid Profiling Of Soybean Aromatic Compounds Using Electronic Nose, Ramasamy Ravi, Ali Taheri, Durga Khandekar, Reneth Millas
Agricultural and Environmental Sciences Faculty Research
Soybean (Glycine max (L.)) is the world’s most important seed legume, which contributes to 25% of global edible oil, and about two-thirds of the world’s protein concentrate for livestock feeding. One of the factors that limit soybean’s utilization as a major source of protein for humans is its characteristic soy flavor. This off-flavor can be attributed to the presence of various chemicals such as phenols, aldehydes, ketones, furans, alcohols, and amines. In addition, these flavor compounds interact with protein and cause the formation of new off-flavors. Hence, studying the chemical profile of soybean seeds is an important step in understanding …
Effect Of Soil-Applied Protoporphyrinogen Oxidase Inhibitor Herbicides On Soybean Seedling Disease, Nicholas J. Arneson
Effect Of Soil-Applied Protoporphyrinogen Oxidase Inhibitor Herbicides On Soybean Seedling Disease, Nicholas J. Arneson
Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research
Seedling disease is one the most economically important diseases of soybean in the United States. It is commonly caused by Fusarium spp., Rhizoctonia solani, Pythium spp., and Phytophthora sojae, alone, or together as a disease complex. Fungicide seed treatments continue to provide the most consistent management of seedling diseases. Soil-applied protoporphyrinogen oxidase (PPO) inhibitor herbicides are used preemergence in soybean production to manage several broadleaf weeds. Applications of PPO-inhibitors can result in phytotoxic injury to soybean when environmental conditions are not favorable for soybean growth. These environmental conditions can favor seedling disease development as well. In this thesis, two …
Response Surface Analysis Of Genomic Prediction Accuracy Values Using Quality Control Covariates In Soybean, Diego Jarquin, Reka Howard, George L. Graef, Aaron Lorenz
Response Surface Analysis Of Genomic Prediction Accuracy Values Using Quality Control Covariates In Soybean, Diego Jarquin, Reka Howard, George L. Graef, Aaron Lorenz
Department of Agronomy and Horticulture: Faculty Publications
An important and broadly used tool for selection purposes and to increase yield and genetic gain in plant breeding programs is genomic prediction (GP). Genomic prediction is a technique where molecular marker information and phenotypic data are used to predict the phenotype (eg, yield) of individuals for which only marker data are available. Higher prediction accuracy can be achieved not only by using efficient models but also by using quality molecular marker and phenotypic data. The steps of a typical quality control (QC) of marker data include the elimination of markers with certain level of minor allele frequency (MAF) and …
Generating High Density, Low Cost Genotype Data In Soybean [Glycine Max (L.) Merr.], Mary M. Happ, Haichuan Wang, George L. Graef, David L. Hyten
Generating High Density, Low Cost Genotype Data In Soybean [Glycine Max (L.) Merr.], Mary M. Happ, Haichuan Wang, George L. Graef, David L. Hyten
Department of Agronomy and Horticulture: Faculty Publications
Obtaining genome-wide genotype information for millions of SNPs in soybean [Glycine max (L.) Merr.] often involves completely resequencing a line at 5X or greater coverage. Currently, hundreds of soybean lines have been resequenced at high depth levels with their data deposited in the NCBI Short Read Archive. This publicly available dataset may be leveraged as an imputation reference panel in combination with skim (low coverage) sequencing of new soybean genotypes to economically obtain high-density SNP information. Ninety-nine soybean lines resequenced at an average of 17.1X were used to generate a reference panel, with over 10 million SNPs called using …