Wheat Grain Hardness Among Chromosome 5D Homozygous Recombinant Substitution Lines Using Different Methods of Measurement

1999 ◽  
Vol 76 (2) ◽  
pp. 249-254 ◽  
Author(s):  
Craig F. Morris ◽  
Victor L. DeMacon ◽  
Michael J. Giroux
2005 ◽  
Vol 110 (7) ◽  
pp. 1259-1267 ◽  
Author(s):  
Bryan Clarke ◽  
Sadequr Rahman

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

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

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

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

2008 ◽  
Vol 43 (No. 2) ◽  
pp. 35-43 ◽  
Author(s):  
D. Mikulíková

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.


2021 ◽  
Vol 247 ◽  
pp. 01010
Author(s):  
Vitaliy Fedotov ◽  
Sergey Solovykh

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.


PLoS ONE ◽  
2020 ◽  
Vol 15 (9) ◽  
pp. e0225293
Author(s):  
Nathalie Geneix ◽  
Michèle Dalgalarrondo ◽  
Caroline Tassy ◽  
Isabelle Nadaud ◽  
Pierre Barret ◽  
...  

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