A glycine to serine change in puroindoline b is associated with wheat grain hardness and low levels of starch-surface friabilin

1997 ◽  
Vol 95 (5-6) ◽  
pp. 857-864 ◽  
Author(s):  
M. J. Giroux ◽  
C. F. Morris
Keyword(s):  
Grain Hardness ◽  
Wheat Grain ◽  
Low Levels

A microarray analysis of wheat grain hardness

2005 ◽  
Vol 110 (7) ◽  
pp. 1259-1267 ◽  
Author(s):  
Bryan Clarke ◽  
Sadequr Rahman
Keyword(s):  
Microarray Analysis ◽  
Grain Hardness ◽  
Wheat Grain

Increased Wheat Grain Hardness Conferred by Novel Puroindoline Haplotypes from Aegilops tauschii

Crop Science ◽  
2010 ◽  
Vol 50 (5) ◽  
pp. 1718-1727 ◽  
Author(s):  
Nicholas P. Reynolds ◽  
John M. Martin ◽  
Michael J. Giroux
Keyword(s):  
Aegilops Tauschii ◽  
Grain Hardness ◽  
Wheat Grain

Characterization of Genes Encoding Wheat Grain Hardness from Chinese Cultivar GaoCheng 8901

2004 ◽  
Vol 81 (2) ◽  
pp. 287-289 ◽  
Author(s):  
Z. Pan ◽  
W. Song ◽  
F. Meng ◽  
L. Xu ◽  
B. Liu ◽  
...  
Keyword(s):  
Grain Hardness ◽  
Wheat Grain ◽  
Genes Encoding

Wheat puroindolines interact to form friabilin and control wheat grain hardness

2003 ◽  
Vol 108 (6) ◽  
pp. 1089-1097 ◽  
Author(s):  
A. C. Hogg ◽  
T. Sripo ◽  
B. Beecher ◽  
J. M. Martin ◽  
M. J. Giroux
Keyword(s):  
Grain Hardness ◽  
Wheat Grain ◽  
And Control

scholarly journals Contamination of Wheat Cultivated in Various Regions of Poland during 2017 and 2018 Agricultural Seasons with Selected Trichothecenes and Their Modified Forms

Toxins ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 88 ◽  
Author(s):  
Marcin Bryła ◽  
Edyta Ksieniewicz-Woźniak ◽  
Tomoya Yoshinari ◽  
Agnieszka Waśkiewicz ◽  
Krystyna Szymczyk
Keyword(s):  
Natural Occurrence ◽  
Strongly Correlated ◽  
Wheat Grain ◽  
Fusarium Spp ◽  
Percentage Occurrence ◽  
Immunoaffinity Columns ◽  
Low Levels ◽  
Modified Forms ◽  
Ratio Range

Cross-interaction of antibodies within the immunoaffinity columns used in this study facilitated the simultaneous determination of nivalenol (NIV), deoxynivalenol (DON), their glucoside derivatives (NIV-3G, DON-3G), and 3-acetyl-deoxynivalenol (3-AcDON) in wheat grain harvested in various regions of Poland. In Poland, 2018 was a warm, dry agricultural season, and hence, was relatively less favourable for cereal cultivation than 2017. Data on the natural occurrence of NIV-3G in wheat grain are among the first published in the literature. DON was the most frequently found mycotoxin in the tested samples; the percentage occurrence of DON-positive samples was 92% in 2017 and 61% in 2018. Moreover, DON concentrations were generally higher in 2017 samples (5.2–1670.7 µg/kg) than those in 2018 samples (range 5.0–461.7 µg/kg). A similar pattern was found for DON-3G. However, no statistically significant differences between the samples from the two agricultural seasons were observed for the other three mycotoxins that were analysed, and their concentrations were generally considerably lower. DON was strongly correlated with DON-3G (correlation coefficient r = 0.9558), while NIV was strongly correlated with NIV-3G (r = 0.9442). The percentage occurrence of NIV-3G- and DON-3G-positive samples was 14% in 2017 and 49% in 2018. The NIV-3G/NIV ratio was 5.9–35.7%, while the DON-3G/DON ratio range was 3.2–53.6%. In 2018, wheat samples from Southern Poland exhibited statistically significantly higher levels of DON than those from Northern Poland. The dry and hot summer of 2018 not only reduced wheat yields, but also limited development of Fusarium spp. Therefore, grain harvested that year was generally contaminated with relatively low levels of mycotoxins. Lower levels of DON were also accompanied by lesser amounts of DON-derivatives.

Wheat grain hardness: multigenic basis and its implications

2012 ◽  
Vol 4 (3) ◽  
pp. 136-136
Author(s):  
M. Bhave ◽  
E. Palombo ◽  
A. Ramalingam ◽  
A. Niknejad ◽  
D. Webster
Keyword(s):  
Grain Hardness ◽  
Wheat Grain

scholarly journals The effect of friabilin on wheat grain hardness: a review

2008 ◽  
Vol 43 (No. 2) ◽  
pp. 35-43 ◽  
Author(s):  
D. Mikulíková
Keyword(s):  
Active Form ◽  
Surface Protein ◽  
Grain Texture ◽  
Grain Hardness ◽  
Wheat Grain ◽  
Wheat Varieties ◽  
In The Wild ◽  
Tillage System ◽  
Grain Softness ◽  
Endosperm Texture

A wheat marketing system established the primary classification of hexaploid wheat based on the endosperm texture, i.e. hardness or softness of the grain. Hardness affects a range of characters including the milling (tempering, milling yield, flour particle size, shape and density of flour particles), baking and end-use properties. Wheat grain hardness is largely controlled by genetic factors but it can also be affected by the environmental and other factors. The endosperm texture is primarily associated with the <i>Hardness</i> (<i>Ha</i>) locus on the short arm of chromosome 5D. It is regulated by friabilin. This 15 kDa starch surface protein complex is present in larger amounts in soft wheats compared to hard ones and consists of three major polypeptides: puroindoline a (<i>Pina</i>), puroindoline b (<i>Pinb</i>) and grain softness protein 1 (<i>Gsp-1</i>). The soft grain texture in wheat is a result of both puroindoline genes being in the wild type active form and bound to starch. When one of the puroindolines is either absent or altered by mutation, then the result is a hard texture. Gene sequence variation and mutation of both puroindoline genes account for the majority of variation in the wheat grain texture. The latter may serve as the potential for improvement of milling and baking wheat quality. However, many wheat varieties have the intermediately (mixed) hard endosperm and there is a wide variation between soft and hard grain texture. Grain hardness is affected by a number of factors beyond genetics including N management, tillage system, pest infestations, environment (location of growth, temperature and rainfall during the growing season) and their interactions, and factors such as moisture, gliadin composition, and content of lipids, starch and pentosans.

scholarly journals Modernization of information-measuring systems for grain processing

2021 ◽  
Vol 247 ◽  
pp. 01010
Author(s):  
Vitaliy Fedotov ◽  
Sergey Solovykh
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Artificial Neural Networks ◽  
Grain Hardness ◽  
Wheat Grain ◽  
Measuring Systems ◽  
Information Measuring ◽  
Grain Processing ◽  
Artificial Neural

The paper discusses the basic operation principles of information-measuring systems for optimization wheat grain processing. The quality of grain processing products (cereals, flour, etc.) is influenced by both weather and climatic factors and grinding technologies. The modern development of information technologies makes it possible to modernize the existing information-measuring systems for grain processing and create new ones through the development of algorithms for analyzing the physical characteristics of the grain mass. During the study, test grinding of wheat grains of different varieties was carried out in a laboratory mill. To increase the yield of the finished product, digitalization of the selection of optimal grain separation modes was used. The obtained mathematical models allow predicting the quality of grain separation in separators of various types. The digitalization of the grain processing industry includes the use of artificial neural networks to analyze images of the grain mass using computer vision algorithms. It is promising to increase the information content of granulometric analysis using modern intelligent (information-measuring) systems. For the classification of wheat according to the milling properties, it is proposed to use the grain hardness. The studies used computer vision and artificial neural networks to find and organize the particles of grain grinding by geometric properties. The characteristics of the contours of the images of the grinding particles were taken into account. The values obtained by the developed information-measuring system were compared with that obtained using the Russian State Standard GOST methods. The error in assessing the grain hardness by the new method does not exceed 3.5%. The use of modern information tools allows improving the quality of wheat grain processing.

scholarly journals Relationships between puroindoline A-prolamin interactions and wheat grain hardness

PLoS ONE ◽  
2020 ◽  
Vol 15 (9) ◽  
pp. e0225293
Author(s):  
Nathalie Geneix ◽  
Michèle Dalgalarrondo ◽  
Caroline Tassy ◽  
Isabelle Nadaud ◽  
Pierre Barret ◽  
...  
Keyword(s):  
Grain Hardness ◽  
Wheat Grain ◽  
Puroindoline A
Sign in / Sign up

Export Citation Format

Share Document