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Canavalia And Dolichos Extracts For Sustainable Pest Biocontrol And Plant Nutrition Improvement In El Salvador, Carlos Martinez 2019 University of Nebraska - Lincoln

Canavalia And Dolichos Extracts For Sustainable Pest Biocontrol And Plant Nutrition Improvement In El Salvador, Carlos Martinez

Theses, Dissertations, and Student Research in Agronomy and Horticulture

Botanical repellents and pesticides are now being rediscovered as new tools for integrated pest management in order to reduce the use of toxic chemicals in crop production. Canavalia gladiata and Dolichos lablab are two Fabaceae very well adapted to farmlands of El Salvador, effective as living barriers and mostly as cover crops, however, they are not yet very well disseminated. This document describes the potential for using the liquid extracts and the dry flour of raw seeds of those plants for economic benefit and practical convenience for pest management in Salvadorian agriculture under field conditions. Seed extracts were useful when ...


Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan 2019 University of Missouri

Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan

Agronomy Publications

Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset containing ...


Impact Of Pesticide Regulation On Innovation In The United States And European Union, Brooke D. Schafer 2019 Purdue University

Impact Of Pesticide Regulation On Innovation In The United States And European Union, Brooke D. Schafer

The Journal of Purdue Undergraduate Research

No abstract provided.


Origins Of Space Food From Mercury To Apollo, Celine Chang 2019 Purdue University

Origins Of Space Food From Mercury To Apollo, Celine Chang

The Journal of Purdue Undergraduate Research

No abstract provided.


Negative Impacts Of The Beef Industry: Lab-Grown Meat, Stephanie Grass 2019 Bowling Green State University

Negative Impacts Of The Beef Industry: Lab-Grown Meat, Stephanie Grass

WRIT: Journal of First-Year Writing

The beef industry is harmful to the environment and human health and alternative solutions must be implemented in order to mitigate the effects of climate change. Water and grain are used in agriculture in abundance despite the negative environmental effects it causes. Cattle are the biggest contributors to greenhouse gas emissions in the sector, also contributing to climate change. Antibiotics are used in large quantities without regard to potential future consequences. One potential solution for this problem is lab-grown beef, which demands very little from the consumer and would take pressure off the environmental issues the beef industry creates. Lab-grown ...


Effects Of Cover Crops And Phosphorus Fertilizer Management On Soil Health Parameters In A No-Till Corn-Soybean Cropping System In Riley County, Kansas, L. M. Starr, P. J. Tomlinson, N. O. Nelson, K. L. Roozeboom, G. J. Kluitenberg, D. R. Presley 2019 Kansas State University

Effects Of Cover Crops And Phosphorus Fertilizer Management On Soil Health Parameters In A No-Till Corn-Soybean Cropping System In Riley County, Kansas, L. M. Starr, P. J. Tomlinson, N. O. Nelson, K. L. Roozeboom, G. J. Kluitenberg, D. R. Presley

Kansas Agricultural Experiment Station Research Reports

This study was implemented to examine the effects of cover crops and mineral phos­phorus (P) fertilizer application on water quality and soil health parameters. The experiment was established in 2014, at the Kansas Agricultural Watershed (KAW) field research facility, Ashland Bottoms Research Farm, Kansas State University, Manhattan, KS. The experiment was a 2 × 3 factorial design with two cover crop treatments (with and without) and three phosphorus fertilizer treatments (none, spring injected P, and fall broadcast P). Measures of nutrient demand (enzyme activity), microbial metabolic activity (soil respiration), and labile carbon (potassium permanganate oxidized carbon) were taken to assess ...


Relative Salt Tolerance Of Seven Japanese Spirea Cultivars, Yuxiang Wang, Liqin Li, Youping Sun, Xin Dai 2019 Xinjiang Agricultural University

Relative Salt Tolerance Of Seven Japanese Spirea Cultivars, Yuxiang Wang, Liqin Li, Youping Sun, Xin Dai

Youping Sun

Spirea (Spiraea sp.) plants are commonly used in landscapes in Utah and the intermountain western United States. The relative salt tolerance of seven japanese spirea (Spiraea japonica) cultivars (Galen, Minspi, NCSX1, NCSX2, SMNSJMFP, Tracy, and Yan) were evaluated in a greenhouse. Plants were irrigated with a nutrient solution with an electrical conductivity (EC) of 1.2 dSmL1 (control) or saline solutions with an EC of 3.0 or 6.0 dSmL1 once per week for 8 weeks. At 8 weeks after the initiation of treatment, all japanese spirea cultivars irrigated with saline solution with an EC of 3.0 dSmL1 ...


Determining The Functions Of Novel Genes Required For Photosynthesis, Gillian Gomer, Moshe Kafri, Martin Jonikas 2019 University of Central Florida

Determining The Functions Of Novel Genes Required For Photosynthesis, Gillian Gomer, Moshe Kafri, Martin Jonikas

Gillian Gomer

As land available for agriculture remains limited, it is becoming more necessary to explore methods to improve the efficiency of crop production in order to support Earth’s growing populations. Newly characterized photosynthetic genes could improve our understanding of the way organisms convert light energy into fuel, allowing improvements in plant growth and environmental resistance. Using an insertion mutant library of the unicellular algae, Chlamydomonas reindhartii, that covers 83% of its genome, we are identifying and characterizing the hundreds of genes associated with photosynthesis. Chlamydomonas can be grown with or without a light source, which allows us to identify mutants ...


Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan 2019 University of Missouri

Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan

John E. Sawyer

Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset containing ...


Adjusting For Spatial Effects In Genomic Prediction, Xiaojun Mao, Somak Dutta, Raymond K. W. Wong, Dan Nettleton 2019 Fudan University

Adjusting For Spatial Effects In Genomic Prediction, Xiaojun Mao, Somak Dutta, Raymond K. W. Wong, Dan Nettleton

Dan Nettleton

This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genome-wide association studies (GWAS), spatial effects often affect phenotypic measurements of plants. We consider a Gaussian random field (GRF) model with an additive covariance structure that incorporates genotype effects, spatial effects and subpopulation effects. An empirical study shows the existence of spatial effects and heterogeneity across different subpopulation families while simulations illustrate the improvement in selecting genotypically superior plants by adjusting for spatial effects in genomic prediction.


Development Of Optimized Phenomic Predictors For Efficient Plant Breeding Decisions Using Phenomic-Assisted Selection In Soybean, Kyle Parmley, Koushik Nagasubramanian, Soumik Sarkar, Baskar Ganapathysubramanian, Asheesh K. Singh 2019 Iowa State University

Development Of Optimized Phenomic Predictors For Efficient Plant Breeding Decisions Using Phenomic-Assisted Selection In Soybean, Kyle Parmley, Koushik Nagasubramanian, Soumik Sarkar, Baskar Ganapathysubramanian, Asheesh K. Singh

Baskar Ganapathysubramanian

The rate of advancement made in phenomic-assisted breeding methodologies has lagged those of genomic-assisted techniques, which is now a critical component of mainstream cultivar development pipelines. However, advancements made in phenotyping technologies have empowered plant scientists with affordable high-dimensional datasets to optimize the operational efficiencies of breeding programs. Phenomic and seed yield data was collected across six environments for a panel of 292 soybean accessions with varying genetic improvements. Random forest, a machine learning (ML) algorithm, was used to map complex relationships between phenomic traits and seed yield and prediction performance assessed using two cross-validation (CV) scenarios consistent with breeding ...


Qqs Orphan Gene And Its Interactor Nf‐Yc4 Reduce Susceptibility To Pathogens And Pests, Mingsheng Qi, Wenguang Zheng, Xuefeng Zhao, Jessica D. Hohenstein, Yuba Kandel, Seth O’Conner, Yifan Wang, Chuanlong Du, Dan Nettleton, Gustavo C. Macintosh, Gregory L. Tylka, Eve Syrkin Wurtele, Steven A. Whitham, Ling Li 2019 Iowa State University

Qqs Orphan Gene And Its Interactor Nf‐Yc4 Reduce Susceptibility To Pathogens And Pests, Mingsheng Qi, Wenguang Zheng, Xuefeng Zhao, Jessica D. Hohenstein, Yuba Kandel, Seth O’Conner, Yifan Wang, Chuanlong Du, Dan Nettleton, Gustavo C. Macintosh, Gregory L. Tylka, Eve Syrkin Wurtele, Steven A. Whitham, Ling Li

Ling Li

Enhancing the nutritional quality and disease resistance of crops without sacrificing productivity is a key issue for developing varieties that are valuable to farmers and for simultaneously improving food security and sustainability. Expression of the Arabidopsis thaliana species‐specific AtQQS (Qua‐Quine Starch) orphan gene or its interactor, NF‐YC4 (Nuclear Factor Y, subunit C4), has been shown to increase levels of leaf/seed protein without affecting the growth and yield of agronomic species. Here, we demonstrate that overexpression of AtQQS and NF‐YC4 in Arabidopsis and soybean enhances resistance/reduces susceptibility to viruses, bacteria, fungi, aphids, and soybean cyst ...


Expression Of Multi-Domain Lytic Peptide Genes In Transgenic Plants For Disease Resistance, George Biliarski 2019 University of Nebraska - Lincoln

Expression Of Multi-Domain Lytic Peptide Genes In Transgenic Plants For Disease Resistance, George Biliarski

Theses, Dissertations, and Student Research in Agronomy and Horticulture

Four non-plant multi-domain lytic peptide genes coding for antimicrobial peptides were expressed in Nicotiana benthamiana plants and tested against three fungal pathogens: Sclerotinia sclerotiorum, Rhizoctonia solani, and Pythium sp. Detached-leaf bioassay was performed for the transgenic plants carrying multi-domain lytic peptide constructs and compared with transgenic and wild type control plants. Symptom area of each leaf was measured with high precision using the Compu-Eye software and processed by SAS statistical package. The transgenic lines ORF13 and RSL1 showed substantial resistance to Sclerotinia sclerotiorum infection producing significantly smaller lesion areas compared to control plants. However, these lines were not ...


Identifying Consumer Perceptions Of Fresh-Market Blackberries, Aubrey Dunteman 2019 University of Arkansas, Fayetteville

Identifying Consumer Perceptions Of Fresh-Market Blackberries, Aubrey Dunteman

Food Science Undergraduate Honors Theses

Blackberries are grown worldwide for commercial fresh markets, but there is limited information on consumer perceptions of this fruit. In this study, physiochemical and consumer sensory attributes of three Arkansas-grown fresh-market blackberry genotypes were evaluated and consumer perceptions of fresh-market blackberries were also investigated though an online survey. Two cultivars (Natchez and Ouachita) and one advanced selection (A-2418) were evaluated for compositional and nutraceutical analysis and consumer sensory analysis. Natchez had the highest berry weight, length, drupelets and pyrenes/berry, and pyrene weight/berry. Ouachita had the highest soluble solids content (11.9%), pH (3.18) and soluble solids/titratable ...


B.R. Wells Arkansas Rice Research Studies, R. J. Norman, K. A.K. Moldenhauer 2019 University of Arkansas, Fayetteville

B.R. Wells Arkansas Rice Research Studies, R. J. Norman, K. A.K. Moldenhauer

Research Series

No abstract provided.


Forage News [2019-08], University of Kentucky Department of Plant and Soil Sciences 2019 University of Kentucky

Linkage Of Climate Diagnostics In Predictions For Crop Production: Cold Impacts In Taiwan And Thailand, Parichart Promchote 2019 Utah State University

Linkage Of Climate Diagnostics In Predictions For Crop Production: Cold Impacts In Taiwan And Thailand, Parichart Promchote

All Graduate Theses and Dissertations

This research presents three case studies of low temperature anomalies that occurred during the winter–spring seasons and their influence on extreme events and crop production. We investigate causes and effects of each climate event and developed prediction methods for crops based on the climate diagnostic information. The first study diagnosed the driven environmental-factors, including climate pattern, climate change, soils moisture, and sea level height, associated with the 2011 great flood in Thailand and resulting total crop loss. The second study investigated climate circulation and indices that contributed to wet-and-cold (WC) events leading to significant crop damage in Taiwan. We ...


Genetic Mapping Of Grass Monoculture And Grass-Legume Mixture Compatibility Qtls In Intermediate Wheatgrass, John Mortenson 2019 Utah State University

Genetic Mapping Of Grass Monoculture And Grass-Legume Mixture Compatibility Qtls In Intermediate Wheatgrass, John Mortenson

All Graduate Theses and Dissertations

Due to increased environmental stewardship and fertilizer prices, there is increased interest in using legume mixes in perennial croplands. The objective of this study was to compare quantitative genetic parameters and quantitative trait loci (QTLs) associated with intermediate wheatgrass (Thinopyrum intermedium) when grown in 1) a non-competitive spaced environment, 2) a polyculture with alfalfa (Medicago sativa), and 3) a monoculture with crested wheatgrass (Agropyron desertorum). Traits evaluated include plant growth characteristics (Zadok’s maturity, height, and tiller count), biomass, and forage nutritive value (CP, NDF, ADF, ADL, IVTD, NDFD, NFC, ME, RFQ). A linkage map comprised of 3568 single nucleotide ...


Seed And Seedling Data From Sugarcreek Metropark Restoration Experiment, Michaela J. Woods, Meredith Cobb, Ryan W. McEwan 2019 University of Dayton

Seed And Seedling Data From Sugarcreek Metropark Restoration Experiment, Michaela J. Woods, Meredith Cobb, Ryan W. Mcewan

Five Rivers MetroParks Collaboration Data Archive

This dataset encompasses information following seed germination and seedling growth of three tree species: Quercus rubra, Juglans cinerea, and Carya laciniosa. Seed sizes were recorded prior to incubation in sand, vermiculite, or without media. Seeds were then germinated with time to germination recorded in this dataset. After germination, seedlings were planted in Sugarcreek Metropark in either fall 2011 or spring 2012. One-half of seedlings were planted in tree tubes and a half without. Seedling height and diameter was recorded in June 2014 and March 2019, and death of seedlings was noted.


The Database Of Identified Root-Specific Genes And Their Promoters In Maize, Sorghum, And Soybean, Gleb Moisseyev, Divith Rajagopal, Alix Cui, Kiyoul Park, Edgar B. Cahoon, Chi Zhang 2019 University of Nebraska - Lincoln

The Database Of Identified Root-Specific Genes And Their Promoters In Maize, Sorghum, And Soybean, Gleb Moisseyev, Divith Rajagopal, Alix Cui, Kiyoul Park, Edgar B. Cahoon, Chi Zhang

Faculty Publications from the Center for Plant Science Innovation

Root genes are essential to plants as they dictate factors such as the strength of the plant, reproductivity success, etc. However, in status quo studies on roots genes are simply inefficient. To be more specific, currently there are very few online databases of roots genes and promoters, which essentially deters root gene studies from being successful. To fix this problem, our lab constructed and coded an online database that contains information about the roots of maize, soybean, and sorghum. We collected 1200 root genes and assessed the strength and success of a given gene. This online database of these crops ...


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