4.5 Article

Use of Student's t statistic as a phenotype of relative consumption preference of wheat (Triticum aestivum L.) grain

Journal

JOURNAL OF CEREAL SCIENCE
Volume 65, Issue -, Pages 285-289

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jcs.2015.08.003

Keywords

Wheat; Flavor; Statistics; Quality

Funding

  1. Ardent Mills LLC [58-2090-5-010]
  2. ARS [ARS-0428800, 813719] Funding Source: Federal RePORTER

Ask authors/readers for more resources

Whole-grain wheat (Triticum aestivum L) products provide essential nutrients to humans, but bran attributes may hinder consumption. Differences in grain attributes including flavor/aroma can be identified using the house mouse (Mus musculus L.) as a model system. A potential application of this model system is to identify genes or quantitative trait loci (QTLs) conferring consumption-related traits using genetic mapping. These analyses require a quantitative phenotype to test marker trait associations. Two-choice feeding trials are common in consumption studies, but do not provide an independent, quantitative phenotype. The objective of this study was to examine the use of 'check' varieties against which to compare sample varieties to generate Student's t values for use as phenotypic values. Two checks, which had previously been identified as Yummy and yucky (Y, y) were compared against each sample variety. The resulting t values provided an independent quantitative phenotype of the sample varieties. Published by Elsevier Ltd.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Chemistry, Applied

Evaluation of commercial -amylase enzyme-linked immunosorbent assay (ELISA) test kits for wheat

Alecia M. Kiszonas, Craig F. Morris

CEREAL CHEMISTRY (2018)

Article Chemistry, Applied

Microwave fixation enhances gluten fibril formation in wheat endosperm

Jose M. Orenday-Ortiz, Craig F. Morris

CEREAL CHEMISTRY (2018)

Article Chemistry, Applied

Relationships between Falling Number, α-amylase activity, milling, cookie, and sponge cake quality of soft white wheat

Alecia M. Kiszonas, Douglas A. Engle, Leonardo A. Pierantoni, Craig F. Morris

CEREAL CHEMISTRY (2018)

Article Agronomy

Development of haplotype-specific molecular markers for the low-molecular-weight glutenin subunits

Maria I. Ibba, Alecia M. Kiszonas, Craig F. Morris

MOLECULAR BREEDING (2018)

Article Chemistry, Applied

Color characteristics of white salted, alkaline, and egg noodles prepared from Triticum aestivum L. and a soft kernel durum T-turgidum ssp. durum

Alecia M. Kiszonas, Dongyun Ma, Eugene Patrick Fuerst, Jeff Casper, Doug A. Engle, Craig F. Morris

CEREAL CHEMISTRY (2018)

Article Food Science & Technology

Mapping kernel texture in a soft durum (Triticum turgidum subsp. durum) wheat population

Maria Itria Ibba, Alecia M. Kiszonas, Deven R. See, Daniel Z. Skinner, Craig F. Morris

JOURNAL OF CEREAL SCIENCE (2019)

Article Food Science & Technology

Genetic analysis of a unique 'super soft' kernel texture phenotype in soft white spring wheat

Neeraj Kumar, Jose M. Orenday-Ortiz, Alecia M. Kiszonas, Jeffrey D. Boehm, Craig F. Morris

JOURNAL OF CEREAL SCIENCE (2019)

Article Food Science & Technology

Influence of Soft Kernel Texture on Fresh Durum Pasta

Jessica C. Murray, Alecia M. Kiszonas, Craig F. Morris

JOURNAL OF FOOD SCIENCE (2018)

Article Veterinary Sciences

Serum Melatonin Values in Normal Dogs and Dogs with Seizures

Stephanie Ann Thomovsky, Annie Vivian Chen, David M. Deavila, Alecia M. Kiszonas

JOURNAL OF THE AMERICAN ANIMAL HOSPITAL ASSOCIATION (2019)

Article Food Science & Technology

Identification of loci and molecular markers associated with Super Soft kernel texture in wheat

Neeraj Kumar, Alecia M. Kiszonas, Maria Itria Ibba, Craig F. Morris

JOURNAL OF CEREAL SCIENCE (2019)

Article Plant Sciences

Selecting High-Performing and Stable Pea Genotypes in Multi-Environmental Trial (MET): Applying AMMI, GGE-Biplot, and BLUP Procedures

Sintayehu D. Daba, Alecia M. Kiszonas, Rebecca J. McGee

Summary: By analyzing data from advanced yield trials of three classes of peas, it is found that BLUP model has better predictive accuracy compared to any AMMI model, but may not always identify the best genotype across environments. Therefore, AMMI and GGE statistical tools can fill this gap and help understand genotype performance across environments.

PLANTS-BASEL (2023)

Article Agronomy

Agronomic Traits in Durum Wheat Germplasm Possessing Puroindoline Genes

A. M. Kiszonas, R. Higginbotham, X. M. Chen, K. Garland-Campbell, N. A. Bosque-Perez, M. Pumphrey, M. N. Rouse, D. Hole, N. Wen, C. F. Morris

AGRONOMY JOURNAL (2019)

Review Chemistry, Applied

Wheat breeding for quality: A historical review

Alecia M. Kiszonas, Craig F. Morris

CEREAL CHEMISTRY (2018)

No Data Available