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Featured researches published by Peter R. Thomison.


Plant Genetic Resources | 2003

Amino acid composition of TopCross high-oil maize grain

Peter R. Thomison; D. J. Barker; Allen B. Geyer; L. D. Lotz; Howard J. Siegrist; T. L. Dobbels

Increased amino acid content in high-oil maize (Zea mays L.) grain may add further value to its use in livestock rations, especially if this enhanced amino acid content is consistent across varying growing conditions. Most high-oil maize (HOM) grown in the USA utilizes the TopCross system which involves planting a blend (TC Blend) of two types of maize. Field experiments and on-farm studies were conducted in 1997 and 1998 to compare the amino acid profile of grain from HOM TC Blends with that of their normal-oil maize (NOM) counterparts across a range of production environments in Ohio. In 1997, the composition of four amino acids (lysine, methionine, glycine and arginine) was significantly higher in HOM compared to NOM grain. In 1998, nine amino acids (lysine, methionine, glycine, arginine, asparagine, threonine, serine, cysteine and tryptophan) were greater in HOM than in NOM grain. Lysine and methionine content in HOM grain averaged 12 and 13% higher than in NOM grain in both years. The number of amino acids significantly affected by the grain parent was greater than that for maize type each year. A significant maize type × grain parent interaction for a limited number of amino acids suggest that TC Blend grain parents may affect the consistency of amino acid composition in HOM grain. Results of this study demonstrate that the levels of several amino acids, including economically important lysine and methionine, were consistently greater in HOM than in NOM grain across a range of production environments. Modelling with livestock ration balancing software showed that the additional amino acids and oil in HOM added 12–20% to its value as livestock feed.


BMC Research Notes | 2018

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets

Naser Alkhalifah; Darwin A. Campbell; Celeste M. Falcon; Jack M. Gardiner; Nathan D. Miller; Maria C. Romay; Ramona L. Walls; Renee Walton; Cheng-Ting Yeh; M. Bohn; Jessica Bubert; Edward S. Buckler; Ignacio A. Ciampitti; Sherry Flint-Garcia; Michael A. Gore; Christopher Graham; Candice N. Hirsch; James B. Holland; David C. Hooker; Shawn M. Kaeppler; Joseph E. Knoll; Nick Lauter; Elizabeth C. Lee; Aaron J. Lorenz; Jonathan P. Lynch; Stephen P. Moose; Seth C. Murray; Rebecca J. Nelson; Torbert Rocheford; Oscar Rodriguez

ObjectivesCrop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F’s genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available.Data descriptionDatasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.


Crop Management | 2014

Seed Tape Effects on Corn Emergence under Greenhouse Conditions

Ramarao Venkatesh; Peter R. Thomison; Colette K. Gabriel; Mark A. Bennett; Elaine M. Grassbaugh; Matthew D. Kleinhenz; Scott A. Shearer; Santosh K. Pitla

Seed tape has recently received attention as an alternative planting system for smallholder farmers in underdeveloped regions of South America, Africa, China, and India (Mateus, 2014). Seed companies are also developing seed-tape planting systems for germplasm evaluations (Deppermann et al., 2013). Although seed tape has been promoted as a method for ensuring uniform seed spacing and plant density of smallseeded flowers, herbs, and vegetables (Chancellor, 1969), little or no information is available on the use of seed tape for largerseeded row crops and its effect on crop emergence. The objective of this study was to compare the emergence of corn seed embedded in tape to seeds planted by hand and to determine seed tape effects on rate of corn emergence. Experiments were conducted in 2013 in greenhouses at Ohio State University and consisted of two treatments. Corn seed embedded in tape made of biodegradable cellulose, which is the material most widely used by seed tape manufacturers, was compared with seeds planted by hand. Two corn hybrids were used in the study—Pioneer brand 37Y14 treated with fludioxonil, mefenoxam, azoxystrobin, thiabendaz, and thiamethoxam and DeKalb DKC 65-63 treated with difenoconazole, fludioxonil, mefenoxam, and thiamethoxam. Seed tape and seeds were hand planted 2 inches deep in flats with commercial top soil (Fig. 1). Greenhouse temperature was maintained at 70 to 75°F, and metal halide lamps provided approximately 220 mmol–1 m–2 s–1 supplemental photosynthetic photon flux for a 16-h daily photoperiod. Corn emergence was recorded at the first appearance of coleoptile and monitored for approximately 2 weeks. Mean emergence time (MET) and emergence rate index (ERI) were used to measure how quickly and uniformly the corn emerged after planting. Multiple emergence counts were taken and used to calculate MET and ERI (Karayel and Ozmerzi, 2002). Treatments were arranged in a randomized complete block design replicated three times for each run. The experiment was repeated eight times (total of 24 replications), and a total of 240 seeds was used for each treatment (120 Published in Crop Management DOI 10.2134/CM-2014-0051-BR


Agronomy Journal | 2002

Delayed planting effects on flowering and grain maturation of dent corn

Robert L. Nielsen; Peter R. Thomison; Gregory A. Brown; Anthony L. Halter; Jason Wells; Kirby L. Wuethrich


Agronomy Journal | 2014

Predicting Maize Phenology: Intercomparison of Functions for Developmental Response to Temperature

Saratha Kumudini; Fernando H. Andrade; Kenneth J. Boote; G. A. Brown; K.A. Dzotsi; G. O. Edmeades; Tom Gocken; M. Goodwin; A. L. Halter; Graeme L. Hammer; Jerry L. Hatfield; James W. Jones; Armen R. Kemanian; Soo-Hyung Kim; Jim R. Kiniry; Jon I. Lizaso; Claas Nendel; R. L. Nielsen; B. Parent; Claudio O. Stöckle; François Tardieu; Peter R. Thomison; Dennis Timlin; Tony J. Vyn; Daniel Wallach; Haishun Yang; Matthijs Tollenaar


Agronomy Journal | 2003

Topcross high oil corn production: Select grain quality attributes

Peter R. Thomison; Allen B. Geyer; L. D. Lotz; Howard J. Siegrist; T. L. Dobbels


Field Crops Research | 2016

Can crop simulation models be used to predict local to regional maize yields and total production in the U.S. Corn Belt

Francisco J. Morell; Haishun Yang; Kenneth G. Cassman; Justin van Wart; Roger W. Elmore; Mark A. Licht; Jeffrey A. Coulter; Ignacio A. Ciampitti; Cameron M. Pittelkow; Sylvie M. Brouder; Peter R. Thomison; Joseph G. Lauer; Christopher Graham; Raymond E. Massey; Patricio Grassini


Crop Management | 2004

Nitrogen Fertility Effects on Grain Yield, Protein, and Oil of Corn Hybrids with Enhanced Grain Quality Traits

Peter R. Thomison; Allen B. Geyer; Bert L. Bishop; John R. Young; Edwin Lentz


Agronomy Journal | 2011

Corn Response to Harvest Date as Affected by Plant Population and Hybrid

Peter R. Thomison; Robert W. Mullen; Patrick E. Lipps; Tom Doerge; Allen B. Geyer


Agronomy Journal | 2005

Early-Season Defoliation Effects on TopCross High-Oil Corn Production

T. F. Mangen; Peter R. Thomison; Stephen D. Strachan

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Christopher Graham

South Dakota State University

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Haishun Yang

University of Nebraska–Lincoln

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Roger W. Elmore

University of Nebraska–Lincoln

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