Search Results - "Beavis, D."

Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean by Ramasubramanian, Vishnu, Beavis, William D.

“…Plant breeding is a decision-making discipline based on understanding project objectives. Genetic improvement projects can have two competing objectives:…”
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Genetic Architecture of Soybean Yield and Agronomic Traits by Diers, Brian W, Specht, Jim, Rainey, Katy Martin, Cregan, Perry, Song, Qijian, Ramasubramanian, Vishnu, Graef, George, Nelson, Randall, Schapaugh, William, Wang, Dechun, Shannon, Grover, McHale, Leah, Kantartzi, Stella K, Xavier, Alencar, Mian, Rouf, Stupar, Robert M, Michno, Jean-Michel, An, Yong-Qiang Charles, Goettel, Wolfgang, Ward, Russell, Fox, Carolyn, Lipka, Alexander E, Hyten, David, Cary, Troy, Beavis, William D

“…Soybean is the world's leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but…”
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Predictions from algorithmic modeling result in better decisions than from data modeling for soybean iron deficiency chlorosis by Xu, Zhanyou, Kurek, Andreomar, Cannon, Steven B, Beavis, William D

“…In soybean variety development and genetic improvement projects, iron deficiency chlorosis (IDC) is visually assessed as an ordinal response variable. Linear…”
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Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population by Xavier, Alencar, Jarquin, Diego, Howard, Reka, Ramasubramanian, Vishnu, Specht, James E, Graef, George L, Beavis, William D, Diers, Brian W, Song, Qijian, Cregan, Perry B, Nelson, Randall, Mian, Rouf, Shannon, J Grover, McHale, Leah, Wang, Dechun, Schapaugh, William, Lorenz, Aaron J, Xu, Shizhong, Muir, William M, Rainey, Katy M

“…Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform…”
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High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population by Montes, Christopher M, Fox, Carolyn, Sanz-Sáez, Álvaro, Serbin, Shawn P, Kumagai, Etsushi, Krause, Matheus D, Xavier, Alencar, Specht, James E, Beavis, William D, Bernacchi, Carl J, Diers, Brian W, Ainsworth, Elizabeth A

“…Abstract Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping…”
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Genetic Characterization of the Soybean Nested Association Mapping Population by Song, Qijian, Yan, Long, Quigley, Charles, Jordan, Brandon D., Fickus, Edward, Schroeder, Steve, Song, Bao‐Hua, Charles An, Yong‐Qiang, Hyten, David, Nelson, Randall, Rainey, Katy, Beavis, William D, Specht, Jim, Diers, Brian, Cregan, Perry

“…Core Ideas 40 NAM families were developed and 5600 RILs in the families were characterized. The linkage maps for each family and a composite linkage map were…”
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Leveraging genomic prediction to scan germplasm collection for crop improvement by de Azevedo Peixoto, Leonardo, Moellers, Tara C, Zhang, Jiaoping, Lorenz, Aaron J, Bhering, Leonardo L, Beavis, William D, Singh, Asheesh K

“…The objective of this study was to explore the potential of genomic prediction (GP) for soybean resistance against Sclerotinia sclerotiorum (Lib.) de Bary, the…”
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Dynamic Programming for Resource Allocation in Multi-Allelic Trait Introgression by Han, Ye, Cameron, John N, Wang, Lizhi, Pham, Hieu, Beavis, William D

“…Trait introgression is a complex process that plant breeders use to introduce desirable alleles from one variety or species to another. Two of the major types…”
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Quark–gluon plasma and color glass condensate at RHIC? The perspective from the BRAHMS experiment by Arsene, I., Bearden, I.G., Beavis, D., Besliu, C., Budick, B., Bøggild, H., Chasman, C., Christensen, C.H., Christiansen, P., Cibor, J., Debbe, R., Enger, E., Gaardhøje, J.J., Germinario, M., Hansen, O., Holm, A., Holme, A.K., Hagel, K., Ito, H., Jakobsen, E., Jipa, A., Jundt, F., Jørdre, J.I., Jørgensen, C.E., Karabowicz, R., Kim, E.J., Kozik, T., Larsen, T.M., Lee, J.H., Lee, Y.K., Lindahl, S., Løvhøiden, G., Majka, Z., Makeev, A., Mikelsen, M., Murray, M.J., Natowitz, J., Neumann, B., Nielsen, B.S., Ouerdane, D., Płaneta, R., Rami, F., Ristea, C., Ristea, O., Röhrich, D., Samset, B.H., Sandberg, D., Sanders, S.J., Scheetz, R.A., Staszel, P., Tveter, T.S., Videbæk, F., Wada, R., Yin, Z., Zgura, I.S.

“…We review the main results obtained by the BRAHMS Collaboration on the properties of hot and dense hadronic and partonic matter produced in ultrarelativistic…”
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Genome-wide association study for oat (Avena sativa L.) beta-glucan concentration using germplasm of worldwide origin by Newell, Mark A, Asoro, Franco G, Scott, M. Paul, White, Pamela J, Beavis, William D, Jannink, Jean-Luc

“…Detection of quantitative trait loci (QTL) controlling complex traits followed by selection has become a common approach for selection in crop plants. The QTL…”
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Legumes as a Model Plant Family. Genomics for Food and Feed Report of the Cross-Legume Advances through Genomics Conference by Gepts, Paul, Beavis, William D, Brummer, E. Charles, Shoemaker, Randy C, Stalker, H. Thomas, Weeden, Norman F, Young, Nevin D

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Applying Spatial Statistical Analysis to Ordinal Data for Soybean Iron Deficiency Chlorosis by Xu, Zhanyou, Cannon, Steven B., Beavis, William D.

“…Accounting for field variation patterns plays a crucial role in interpreting phenotype data and, thus, in plant breeding. Several spatial models have been…”
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Expanding the genetic map of maize with the intermated B73 x Mo17 (IBM) population by Lee, Michael, Sharopova, Natalya, Beavis, William D, Grant, David, Katt, Maria, Blair, Deborah, Hallauer, Arnel

“…The effects of intermating on recombination and the development of linkage maps were assessed in maize. Progeny derived from a common population (B73 x Mo17)…”
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Numericware i: Identical by State Matrix Calculator by Kim, Bongsong, Beavis, William D

“…We introduce software, Numericware i, to compute identical by state (IBS) matrix based on genotypic data. Calculating an IBS matrix with a large dataset…”
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Genetic architecture of protein and oil content in soybean seed and meal by Diers, Brian W., Specht, James E., Graef, George L., Song, Qijian, Rainey, Katy Martin, Ramasubramanian, Vishnu, Liu, Xiaotong, Myers, Chad L., Stupar, Robert M., An, Yong‐Qiang Charles, Beavis, William D.

“…Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to…”
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Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction by Howard, Réka, Carriquiry, Alicia L, Beavis, William D

“…An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict…”
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Charged meson rapidity distributions in central Au + Au collisions at √sNN = 200 GeV by BEARDEN, I. G, BEAVIS, D, ENGER, E, GAARDHOJE, J. J, GERMINARIO, M, HAGEL, K, HANSEN, O, HOLM, A, HOLME, A. K, ITO, H, JIPA, A, JUNDT, F, BESLIU, C, JORDRE, J. I, JORGENSEN, C. E, KARABOWICZ, R, KIM, E. J, KOZIK, T, LARSEN, T. M, LEE, J. H, LEE, Y. K, LOVHOOIDEN, G, MAJKA, Z, BUDICK, B, MAKEEV, A, MIKELSEN, M, MURRAY, M, NATOWITZ, J, NIELSEN, B. S, NORRIS, J, OLCHANSKI, K, OUERDANE, D, PLANETA, R, RAMI, F, BOGGILD, H, RISTEA, C, RÖHRICH, D, SAMSET, B. H, SANDBERG, D, SANDERS, S. J, SHEETZ, R. A, STASZEL, P, TVETER, T. S, VIDEBAEK, F, WADA, R, CHASMAN, C, YIN, Z, ZGURA, I. S, CHRISTENSEN, C. H, CHRISTIANSEN, P, CIBOR, J, DEBBE, R

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Rate and pattern of mutation at microsatellite loci in maize by Vigouroux, Yves, Jaqueth, Jennifer S, Matsuoka, Yoshihiro, Smith, Oscar S, Beavis, William D, Smith, J Stephen C, Doebley, John

“…Microsatellites are important tools for plant breeding, genetics, and evolution, but few studies have analyzed their mutation pattern in plants. In this study,…”
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Legume Information System (LIS): an integrated information resource for comparative legume biology by Gonzales, M.D, Archuleta, E, Farmer, A, Gajendran, K, Grant, D, Shoemaker, R, Beavis, W.D, Waugh, M.E

“…The Legume Information System (LIS) (http://www.comparative-legumes.org), developed by the National Center for Genome Resources in cooperation with the USDA…”
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Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats by Asoro, Franco G., Newell, Mark A., Beavis, William D., Scott, M. Paul, Jannink, Jean‐Luc

“…Genomic selection (GS) is a method to estimate the breeding values of individuals by using markers throughout the genome. We evaluated the accuracies of GS…”
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