Agronomy and Crop Sciences Commons^™

Hybrid Allele‑Specific Chip‑Seq Analysis Identifies Variation In Brassinosteroid‑Responsive Transcription Factor Binding Linked To Traits In Maize, Thomas Hartwig, Michael Banf, Gisele Passaia Prietsch, Jia‑Ying Zhu, Isabel Mora‑Ramírez, Jos H. M. Schippers, Samantha J. Snodgrass, Arun S. Seetharam, Bruno Huettel, Judith M. Kolkman, Jiashi Yang, Julia Engelhorn, Zhi‑Yong Wang

Department of Agronomy and Horticulture: Faculty Publications

Background: Genetic variation in regulatory sequences that alter transcription factor (TF) binding is a major cause of phenotypic diversity. Brassinosteroid is a growth hormone that has major effects on plant phenotypes. Genetic variation in brassinosteroidresponsive cis-elements likely contributes to trait variation. Pinpointing such regulatory variations and quantitative genomic analysis of the variation in TF-target binding, however, remains challenging. How variation in transcriptional targets of signaling pathways such as the brassinosteroid pathway contributes to phenotypic variation is an important question to be investigated with innovative approaches.

Results: Here, we use a hybrid allele-specific chromatin binding sequencing (HASChseq) approach and …

Evaluating Planting Green And Herbicides For Integrated Weed Management And Their Effect On Soil Properties In Corn And Soybean In Nebraska, Trey Stephens

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Producers across the Midwest are finding new ways to implement cover crops into cropping systems and the practice of “Planting Green” is one of the newest uses of cover crops. When planting green, producers plant their row crops into actively growing cover crops and terminate the cover crop at time of planting or shortly after planting. This practice would allow for higher biomass accumulation of the cover crop and could aid in weed management of herbicide-resistant weeds. The objective of the first two studies was to evaluate planting green and its effect on soil-applied residual herbicides, weed management, dicamba/glyphosate-resistant soybean …

Genomic Selection For Yield And Seed Composition Stability In An Applied Soybean Breeding Program, Benjamin Harms

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Stability traits are of primary importance in plant breeding to ensure consistency in phenotype across a range of environments. However, selection efficiency and accuracy for stability traits can be hindered due to the requirement of obtaining phenotype data across multiple years and environments for proper stability analysis. Genomic selection is a method that allows prediction of a phenotype prior to observation in the field using genome-wide marker data and phenotype data from a training population. To assess prediction of stability traits, two elite-yielding soybean populations developed three years apart in the same breeding program were used. The individuals in each …

Investigating Effect Of Seed Source And Developing Germination Protocols To Improve Success In Restoration Of Arkansas Tallgrass Prairies, Rhiannon Spencerosa

Graduate Theses and Dissertations

American tallgrass prairie has faced losses estimated at 87-98% of original land area since European settlement. Native seeds are often used to supplement struggling or extinct plant populations in tallgrass prairie restoration and establishment sites. Two main considerations in restoration and establishment are from where to source seed and how to obtain high germination rates. In order to determine the effect of seed source, a common garden experiment was performed in Fayetteville, Arkansas in 2022 with five prairie species: Andropogon gerardii (big bluestem), Bouteloua curtipendula (sideoats grama), Panicum virgatum (switchgrass), Schizachyrium scoparium (little bluestem), and Sorghastrum nutans (Indiangrass). Seed was …

Plasticity Of Sorghum Biomass And Inflorescence Traits In Response To Nitrogen Application, Kyle M. Linders

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Nitrogen is an essential nutrient required for growth and development in plants. Insufficient nitrogen availability can reduce vegetative growth and grain yield. However, nitrogen is a costly input for farmers, is energy intensive to manufacture, and runoff of excess nitrogen fertilizer impacts water quality. Compared to its close relative, maize, sorghum has much greater resilience to nitrogen and water deficit, and heat stress, allowing sorghum to be grown with fewer inputs and on marginal land. Variation in total biomass accumulation and grain yield between sorghum accessions, as well as between nitrogen conditions, can be largely explained by differences in vegetative …

A Deep Learning Framework For Processing And Classification Of Hyperspectral Rice Seed Images Grown Under High Day And Night Temperatures, Víctor Díaz-Martínez, Jairo Orozco-Sandoval, Vidya Manian, Balpreet K. Dhatt, Harkamal Walia

Department of Agronomy and Horticulture: Faculty Publications

A framework combining two powerful tools of hyperspectral imaging and deep learning for the processing and classification of hyperspectral images (HSI) of rice seeds is presented. A seed-based approach that trains a three-dimensional convolutional neural network (3D-CNN) using the full seed spectral hypercube for classifying the seed images from high day and high night temperatures, both including a control group, is developed. A pixel-based seed classification approach is implemented using a deep neural network (DNN). The seed and pixel-based deep learning architectures are validated and tested using hyperspectral images from five different rice seed treatments with six different high temperature …

Entropy And Energy Profiles Of Chemical Reactions, Johannes C. B. Dietschreit, Dennis J. Diestler, Rafael Gómez-Bombarelli

Department of Agronomy and Horticulture: Faculty Publications

The description of chemical processes at the molecular level is often facilitated by use of reaction coordinates, or collective variables (CVs). The CV measures the progress of the reaction and allows the construction of profiles that track the evolution of a specific property as the reaction progresses. Whereas CVs are routinely used, especially alongside enhanced sampling techniques, links between profiles and thermodynamic state functions and reaction rate constants are not rigorously exploited. Here, we report a unified treatment of such reaction profiles. Tractable expressions are derived for the free-energy, internal-energy, and entropy profiles as functions of only the CV. We …

Divergent Metabolic Changes In Rhizomes Of Lowland And Upland Switchgrass (Panicum Virgatum) From Early Season Through Dormancy Onset, Nathan A. Palmer, Gautam Sarath, Michael J. Bowman, Aaron J. Saathoff, Serge J. Edmé, Robert B. Mitchell, Christian M. Tobias, Soundararajan Madhavan, Erin D. Scully, Scott E. Sattler

Department of Agronomy and Horticulture: Faculty Publications

High-biomass-yielding southerly adapted switchgrasses (Panicum virgatum L.) frequently suffer from unpredictable winter hardiness at more northerly sites arising from damage to rhizomes that prevent effective spring regrowth. Previously, changes occurring over the growing season in rhizomes sampled from a cold-adapted tetraploid upland cultivar, Summer, demonstrated a role for abscisic acid (ABA), starch accumulation, and transcriptional reprogramming as drivers of dormancy onset and potential keys to rhizome health during winter dormancy. Here, rhizome metabolism of a high-yielding southerly adapted tetraploid switchgrass cultivar, Kanlow—which is a significant source of genetics for yield improvement—was studied over a growing season at a northern …

Herbicide Drift Vs. Crop Resilience – The Influence Of Micro-Rates, Milan Brankov, Bruno Canella Vieira, Miloš Rajković, Milena Simić, Vukadinović Jelena, Violeta Mandić, Vesna Dragičević

Department of Agronomy and Horticulture: Faculty Publications

A greenhouse study was conducted to test the effects of low herbicide dose exposure on different crops measuring visible damages, plant height, leaf area, and dry matter. Seven crops were tested: lettuce (Lactuca sativa L.) cv. Novosadska majska maslena, oil pumpkin (Cucurbita maxima Duch) cv. Olivija, oilseed rape (Brassica napus L.) cv. NS Ras, pepper (Capsicum annuum L.) cv. Kurtovska kapija, soybean (Glycine max (L.) Merr) cv. ZP Laura, sunflower (Helianthus annuus L.) cv. NS Kruna, and tomato (Solanum lycopersicum L.) cv. Dunavski Rubin. Herbicide dicamba in the range of 0.14 to 1 …

Late Postemergence Glufosinate-Based Programs For Glyphosate-Resistant Palmer Amaranth Control In Dicamba/Glufosinate/Glyphosate-Resistant Soybean, Vipan Kumar, Jatinder S. Aulakh, Rui Liu, Amit J. Jhala

Department of Agronomy and Horticulture: Faculty Publications

Glyphosate-resistant (GR) Palmer amaranth (Amaranthus palmeri S. Watson) is widespread in the Central Great Plains. Introduction of newly developed dicamba/glufosinate/glyphosate (DGG)-resistant soybean varieties allows postemergence (POST) applications of dicamba and glufosinate for in-season control of GR Palmer amaranth. Limited information exists on the effectiveness of glufosinate applied late-POST for tall (70–90 cm) GR Palmer amaranth control in DGG-resistant soybean. The objectives of this study were to (1) determine the effectiveness of late-POST glufosinate-based programs for GR Palmer amaranth control, and (2) determine the impact of those programs on soybeans grain yields. Ten glufosinatebased programs were tested in a field …

A Leaf-Level Spectral Library To Support High-Throughput Plant Phenotyping: Predictive Accuracy And Model Transfer, Nuwan K. Wijewardane, Huichun Zhang, Jinliang Yang, James C. Schnable, Daniel P. Schachtman, Yufeng Ge

Department of Agronomy and Horticulture: Faculty Publications

Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of plant leaf traits due to its rapid, low-cost, multi-sensing, and non-destructive nature. However, collecting samples for model calibration can still be expensive, and models show poor transferability among different datasets. This study had three specific objectives: first, to assemble a large library of leaf hyperspectral data (n=2460) from maize and sorghum; second, to evaluate two machine-learning approaches to estimate nine leaf properties (chlorophyll, thickness, water content, nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur); and third, to investigate the usefulness of this spectral library for predicting external datasets …

Experimentation On Nebraska Farms For Sustaining Soil Health Management, Fernanda Souza Krupek

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Soil health management practices have increasingly been promoted across US agroecosystems to address many interrelated environmental and economic food system challenges. Sustaining conservation behavior – through farmer’s adoption and continued use of practices – is key for achieving many soil health-related intended social-ecological benefits. Using a range of scientific methods, from lab-based experiments to on-farm research to farmer interviews, the overall objective of this dissertation research was to explore soil and human dimension considerations to design farming and knowledge transfer systems for sustaining soil health management in the US Midwest. In a multivariate analysis of ten on-farm research sites, we …

Arkansas Cotton Variety Test 2022, F. Bourland, A. Beach, B. Milano, B. Guest, C. Kennedy, L. Martin, B. Robertson

Arkansas Agricultural Experiment Station Research Series

The primary goal of the Arkansas Cotton Variety Test is to provide unbiased data regarding the agronomic performance of cotton varieties and advanced breeding lines in the major cotton-growing areas of Arkansas. This information helps seed companies establish marketing strategies and assists producers in choosing varieties to plant. These annual evaluations will then facilitate the inclusion of new, improved genetic material in Arkansas cotton production. Adaptation of varieties is determined by evaluating the lines at five University of Arkansas System Division of Agriculture research sites (Manila, Keiser, Judd Hill, Marianna, and Rohwer). The 2022 tests at Rohwer were adversely affected …

Predicting Site‑Specific Economic Optimal Nitrogen Rate Using Machine Learning Methods And On‑Farm Precision Experimentation, Alfonso De Lara, Taro Mieno, Joe D. Luck, Laila A. Puntel

Department of Agronomy and Horticulture: Faculty Publications

Applying at the economic optimal nitrogen rate (EONR) has the potential to increase nitrogen (N) fertilization efficiency and profits while reducing negative environmental impacts. On-farm precision experimentation (OFPE) provides the opportunity to collect large amounts of data to estimate the EONR. Machine learning (ML) methods such as generalized additive models (GAM) and random forest (RF) are promising methods for estimating yields and EONR. Twenty OFPE N trials in wheat and barley were conducted and analyzed with soil, terrain and remote-sensed variables to address the following objectives: (1) to quantify the spatial variability of winter crops yield and the yield response …

A Plea For Scale, And Why It Matters For Invasive Species Management, Biodiversity And Conservation, Nicholas A. Mcmillan, Samuel D. Fuhlendorf, Craig A. Davis, Robert G. Hamilton, Landon. K. Neumann, Samantha M. Cady

Department of Agronomy and Horticulture: Faculty Publications

1. Invasive species are suspected to be major contributors to biodiversity declines worldwide. Counterintuitively, however, invasive species effects are likely scale dependent and are hypothesized to be positively related to biodiversity at large spatial scales. Past studies investigating the effect of invasion on biodiversity have been mostly conducted at small scales (<100 m²) that cannot represent large dynamic landscapes by design. Therefore, replicated experimental evidence supporting a negative effect of invasive plants on biodiversity is lacking across many landscape types, including large grasslands.

2. We collected data across eight large (333–809 ha) grassland landscapes managed with pyric herbivory—that is the recoupling …

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Soil Depth And Geographic Distance Modulate Bacterial Β-Diversity In Deep Soil Profiles Throughout The U.S. Corn Belt, Lucas Dantas Lopes, Stephanie L. Futrell, Emily E. Wright, Gerasimos J. Danalatos, Michael J. Castellano, Tony J. Vyn, Sotirios V. Archontoulis, Daniel P. Schachtman

Department of Agronomy and Horticulture: Faculty Publications

Understanding how microbial communities are shaped across spatial dimensions is of fundamental importance in microbial ecology. However, most studies on soil biogeography have focused on the topsoil microbiome, while the factors driving the subsoil microbiome distribution are largely unknown. Here we used 16S rRNA amplicon sequencing to analyse the factors underlying the bacterial β-diversity along vertical (0–240 cm of soil depth) and horizontal spatial dimensions (~500,000 km²) in the U.S. Corn Belt. With these data we tested whether the horizontal or vertical spatial variation had stronger impacts on the taxonomic (Bray-Curtis) and phylogenetic (weighted Unifrac) β-diversity. Additionally, we …

Graph Convolutional Network Using Adaptive Neighborhood Laplacian Matrix For Hyperspectral Images With Application To Rice Seed Image Classification, Jairo Orozco, Vidya Manian, Estefania Alfaro, Harkamal Walia, Balpreet K. Dhatt

Department of Agronomy and Horticulture: Faculty Publications

Graph convolutional neural network architectures combine feature extraction and convolutional layers for hyperspectral image classification. An adaptive neighborhood aggregation method based on statistical variance integrating the spatial information along with the spectral signature of the pixels is proposed for improving graph convolutional network classification of hyperspectral images. The spatial-spectral information is integrated into the adjacency matrix and processed by a single-layer graph convolutional network. The algorithm employs an adaptive neighborhood selection criteria conditioned by the class it belongs to. Compared to fixed window-based feature extraction, this method proves effective in capturing the spectral and spatial features with variable pixel neighborhood …

Harvest Aids Did Not Advance Maturity Of Non-Shatter Pennycress, Julija A. Cubins, Samantha Wells, Russ W. Gesch, Gregg A. Johnson, Maninder K. Walia, Ratan Chopra, M. David Marks, Rebecca D. Swenson, Katherine Anna Frels

Department of Agronomy and Horticulture: Faculty Publications

Reliance on summer annual crops in the Upper Midwest results in fallow land from late fall through early spring, providing opportunities to integrate winter crops, such as pennycress (Thlapsi arvense L.), onto the landscape. Pennycress agronomics have primarily been studied using unimproved wild-type lines prone to seed shatter, resulting in significant yield loss if not harvested early. However, high plant and seed moisture complicates harvest and seed storage. A new breeding line with a reducedshatter mutation made it possible to use harvest aids to reduce plant moisture without the risk of seed loss. The objectives of this study were …

A Role For Heritable Transcriptomic Variation In Maize Adaptation To Temperate Environments, Guangchao Sun, Huihui Yu, Peng Wang, Martha Lopez‑Guerrero, Ravi V. Mural, Olivier N. Mizero, Marcin Grzybowski, Baoxing Song, Karin V. Van Dijk, Daniel P. Schachtman, Chi Zhang, James C. Schnable

Department of Agronomy and Horticulture: Faculty Publications

Background: Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments.

Result: We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A …

Recombination Hotspots In Soybean [Glycine Max (L.) Merr.], Samantha Mcconaughy, Keenan L. Amundsen, Qijian Song, Vince Pantalone, D. Hyten

Department of Agronomy and Horticulture: Faculty Publications

Recombination allows for the exchange of genetic material between two parents, which plant breeders exploit to make improved cultivars. This recombination is not distributed evenly across the chromosome. Recombination mostly occurs in euchromatic regions of the genome and even then, recombination is focused into clusters of crossovers termed recombination hotspots. Understanding the distribution of these hotspots along with the sequence motifs associated with them may lead to methods that enable breeders to better exploit recombination in breeding. To map recombination hotspots and identify sequence motifs associated with hotspots in soybean [Glycine max (L.) Merr.], two biparental recombinant inbred lines …

Large And Stable Genome Edits At The Sorghum Alpha Kafirin Locus Result In Changes In Chromatin Accessibility And Globally Increased Expression Of Genes Encoding Lysine Enrichment, J. Preston Hurst, Abou Yobi, Aixia Li, Shirley Sato, Thomas E. Clemente, Ruthie Angelovici

Department of Agronomy and Horticulture: Faculty Publications

Introduction: Sorghum is a resilient and widely cultivated grain crop used for feed and food. However, it’s grain is deficient in lysine, an essential amino acid. This is due to the primary seed storage proteins, the alpha-kafirins, lacking lysine. It has been observed that reductions in alpha-kafirin protein results in rebalancing of the seed proteome and a corresponding increase in non-kafirin proteins which leads to an increased lysine content. However, the mechanisms underlying proteome rebalancing are unclear. This study characterizes a previously developed gene edited sorghum line, with deletions at the alpha kafirin locus.

Methods: A single consensus …

Large And Stable Genome Edits At The Sorghum Alpha Kafirin Locus Result In Changes In Chromatin Accessibility And Globally Increased Expression Of Genes Encoding Lysine Enrichment, J. Preston Hurst, Abou Yobi, Aixia Li, Shirley Sato, Thomas E. Clemente, Ruthie Angelovici, David R. Holding

Department of Agronomy and Horticulture: Faculty Publications

Introduction: Sorghum is a resilient and widely cultivated grain crop used for feed and food. However, it’s grain is deficient in lysine, an essential amino acid. This is due to the primary seed storage proteins, the alpha-kafirins, lacking lysine. It has been observed that reductions in alpha-kafirin protein results in rebalancing of the seed proteome and a corresponding increase in non-kafirin proteins which leads to an increased lysine content. However, the mechanisms underlying proteome rebalancing are unclear. This study characterizes a previously developed gene edited sorghum line, with deletions at the alpha kafirin locus.

Methods: A single consensus …

Facilitating Transformative Innovations In Sustainability Education [Version 2], Martin Melin, Geir Lieblein, Tor Arvid Breland, Charles A. Francis

Department of Agronomy and Horticulture: Faculty Publications

Educational strategies globally are changing from an authoritative, top-down model to one focused on greater student and stakeholder participation in planning and implementation of research and educational activities. In addition to emphasis on student-centered education, strategies currently evolve to encompass learning organizations and multistakeholder learning networks. These are essential to address the complexity and scope of tomorrow’s challenges, involving issues that could be called ’wicked problems’ not easily addressed by single disciplines nor resulting in solutions that please all the players. In this study we describe how a transformative innovation – the NEXTFOOD educational approach – may contribute substantially to …

Arkansas Corn And Grain Sorghum Performance Tests 2022, J. F. Carlin, R. B. Mulloy, R. D. Bond

Arkansas Agricultural Experiment Station Research Series

Corn and grain sorghum performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture. The tests provide information to companies marketing seed within the state and aid the Arkansas Cooperative Extension Service in formulating recommendations for producers. The 2022 corn performance tests contained 68 hybrids and were conducted at the Northeast Rice Research and Extension Center (NERREC) at Harrisburg, the Northeast Rice Research and Extension Center (NEREC) at Keiser, the Lon Mann Cotton Research Station (LMCRS) near Marianna, the Rohwer Research Station (RRS) near Rohwer, and the Rice Research and Extension Center (RREC) …

Abnormal Ear Development In Corn: Does Hybrid, Environment, And Seeding Rate Matter?, Osler A. Ortez, Anthony J. Mcmechan, Emily Robinson, Thomas C. Hoegemeyer, Reka Howard, Roger W. Elmore

Department of Agronomy and Horticulture: Faculty Publications

Corn (Zea mays L.) yields have increased in the United States since the 1930s and in other parts of the world since the 1950s and 1960s because of improvements in agricultural management and genotypes. Despite these increases, production concerns still exist. In July 2016, abnormal ear development (multi-ears per node, barbell-ears, and short-husks) was reported in cornfields that extended from the Texas Panhandle to eastern Colorado and east through Kansas, Nebraska, Iowa, and Illinois. Surveys in Nebraska farmer fields revealed significant productivity losses due to the issues, but little was known about the underlying causes. A research study was …

Intensifying A Crop–Fallow System: Impacts On Soil Properties, Crop Yields, And Economics, S. J. Ruis, S. Stepanovic, Humberto Blanco-Canqui

Department of Agronomy and Horticulture: Faculty Publications

Intensifying crop–fallow systems could address increased weed control costs, increased land or rental costs, reduced crop diversity, and degraded soil properties in water-limited environments. One strategy to intensify such systems could be the insertion of a short-season crop during fallow. But, how this strategy affects soils, crop production, and farm economics needs further research. Thus, we studied the impacts of replacing fallow in a winter wheat (Triticum aestivum L)–corn (Zea mays L.)–fallow system with a short-season spring crop [field pea (Pisum sativum L.)] on crop yields and economics from 2015 to 2019 and 5-yr cumulative effects on …

Evaluating Metabolic And Genomic Data For Predicting Grain Traits Under High Night Temperature Stress In Rice, Ye Bi, Rafael Massahiro Yassue, Puneet Paul, Balpreet Kaur Dhatt, Jaspreet Sandhu, Phuc Thi Do, Harkamal Walia, Toshihiro Obata, Gota Morota

Department of Agronomy and Horticulture: Faculty Publications

The asymmetric increase in average nighttime temperatures relative to increase in average daytime temperatures due to climate change is decreasing grain yield and quality in rice. Therefore, a better genome-level understanding of the impact of higher night temperature stress on the weight of individual grains is essential for future development of more resilient rice. We investigated the utility of metabolites obtained from grains to classify high night temperature (HNT) conditions of genotypes, and metabolites and single-nucleotide polymorphisms (SNPs) to predict grain length, width, and perimeter phenotypes using a rice diversity panel. We found that the metabolic profiles of rice genotypes …

Alfalfa In Rotation With Annual Crops Reduced Nitrate Leaching Potential, Arshdeep Singh, Tahseen Afzal, Bryan Woodbury, Charles Wortmann, Javed Iqbal

Department of Agronomy and Horticulture: Faculty Publications

Rotation of perennial alfalfa (Medicago sativa L.) with annual crops has the potential to reduce nitrate-nitrogen (NO₃-N) in the vadose zone and increase soil organic carbon (SOC) sequestration. The objective of this study was to determine the long-term effects on SOC, NO₃-N, ammonium-N (NH₄-N), and soil water in the 7.2 m depth with an alfalfa rotation compared with continuous corn (Zea mays L.). Soils from six pairs of alfalfa rotation versus continuous corn observation points were sampled to 7.2 m depth in 0.3 m increments. The uppermost 0.3 m was divided into …

Soybean Seed Protein Concentration Is Limited By Nitrogen Supply In Tropical And Subtropical Environments In Brazil, E. H. Figueiredo Moura Da Silva, N. Cafaro La Menza, G. G. Munareto, A. J. Zanon, Santos Carvalho, F. R. Marin

Department of Agronomy and Horticulture: Faculty Publications

Soybean production contributes to ca. 60% of global plant-based protein used for food and feed. Brazil is the largest soybean producer and exporter, with 60% from tropical and 40% from subtropical environments. Nitrogen (N) can play an essential role in the storage of proteins in seeds; thus, it could be a key factor in increasing the quantity and quality of seeds in high-yielding soybean crops. Unlike in temperate environments, there is a gap of knowledge on whether soybean grown under tropical and subtropical climates are limited by N-fertilization to sustain the seed yield increase without detriments in seed protein concentration. …

Combining Corn N Recommendation Tools For An Improved Economical Optimal Nitrogen Rate Estimation, 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, David Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan

Department of Agronomy and Horticulture: Faculty Publications

Improving corn (Zea mays L.) nitrogen (N) rate fertilizer recommendation tools can improve farmers’ profits and mitigate N pollution. Numerous approaches have been tested to improve these tools, but to date improvements for predicting economically optimum N rate (EONR) have been modest. This work’s objective was to use ensemble learning to improve our estimation of EONR (for a single at-planting and split N application timing) by combining multiple corn N recommendation tools. The evaluation was conducted using 49 corn N response trials from eight states in the US Corn Belt and three growing seasons (2014–2016). Elastic net and decision …