The Relationship Between Grain-Protein Content of Wheat and Barley and Temperatures During Grain Filling

1994 ◽  
Vol 21 (6) ◽  
pp. 869 ◽  
Author(s):  
R Correll ◽  
J Butler ◽  
L Spouncer ◽  
C Wrigley
Keyword(s):  
Protein Content ◽  
South Australia ◽  
Grain Filling ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Climate Data ◽  
Wheat Grain ◽  
Protein Levels ◽  
Australian Standard ◽  
The Relationship

This paper compares the relationship between temperatures at grain filling and grain-protein content for wheat and barley. Two similar statistical models have been developed using historical grain and climate data to reliably predict the protein content of wheat and barley at grain receival sites. Protein levels were predicted using multiple regressions with the same regression coefficients for all sites. The locality effect is absorbed in the regression intercept derived for each site. Australian Standard White (ASW) wheat data for 109 silos throughout South Australia for the years 1971-1991 were analysed in relation to rainfall and temperatures at the closest weather station. Rainfall from May to September was associated with a decrease in ASW wheat grain protein, and more importantly, the number of days in October above 30�C were positively associated with an increase in wheat grain-protein levels. Analysis of protein data from malting varieties of barley (1982-1991) from 160 South Australian hundreds (districts of about 260 km2) again showed that increased rainfall between July and September was associated with decreased grain protein. However, the dominating influence was the number of days in a row in November above 35�C, which was consistently associated with increased grain protein. This makes an interesting comparison with wheat where October temperatures were more important despite barley being harvested earlier than wheat.

scholarly journals Factors Affecting the Storage Grain Protein Content of Tetraploid Wheat (Triticum turgidum L.) and Their Management

2019 ◽  
pp. 1-8
Author(s):  
Anteneh Agezew Melash
Keyword(s):  
Protein Content ◽  
Protein Concentration ◽  
Triticum Turgidum ◽  
Tetraploid Wheat ◽  
Grain Filling ◽  
Sowing Date ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain ◽  
Factors Affecting

This review work aims to evaluate the factors affecting the storage grain protein content of tetraploid Wheat (Triticum turgidum L.) and their management. For commercial production of tetraploid wheat, grain protein content is considered very important. As the grain receive great market attention due to protein premium price paid for farmers, mainly above 13% that will give about 12% of protein in the milled semolina. However, this review state that grain protein content of tetraploid wheat is sensitive to environmental conditions prevailing before and during grain filling, crop genetics and cultural practices. This and associated problems universally call agronomic based alternative solution to ameliorate protein concentration in durum wheat grain. This could be modified through manipulating seeding rates, selection crop varieties, adjusting nitrogen amount and fertilization time and sowing date. The decision of time of nitrogen application however should be made based on the interest of the farmers. If the interest gears towards grain yield, apply nitrogen early in the season and apply the fertilizer later if heading for better protein concentration.

scholarly journals Linkage and Association Mapping Identifies Loci and Develops Kompetitive Allele Specific PCR Markers for Improving Wheat Grain Protein Content

2021 ◽  
Author(s):  
Peng Jiang ◽  
Peng Zhang ◽  
Lei Wu ◽  
Yi He ◽  
Chang Li ◽  
...  
Keyword(s):  
Association Mapping ◽  
Protein Content ◽  
Large Scale ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain ◽  
Breeding Lines ◽  
Specific Pcr ◽  
Allele Specific ◽  
Allele Specific Pcr

Abstract Wheat grain protein content (GPC) is an important quality indicator. The GPC of wheat grown in the middle and lower reaches of the Yangtze River is often low. Marker-assisted selection (MAS) is an effective tool for improving quantitative traits; however, except Gpc-B1, most markers have not been effectively applied in GPC improvement, although many related loci have been identified. Linkage analysis using a recombinant inbred line population from the cross of core parents of Ningmai 9 and Yangmai 158 and association mapping using the local cultivated varieties were performed and nine candidate intervals were identified. The appropriate kompetitive allele specific PCR (KASP) markers associated with GPC were successfully developed and applied in 1163 F4 breeding lines. Three markers, Kgpc-2B, Kgpc-2D, and Kgpc-4A, were validated to be significantly related to GPC by large-scale association mapping, and they were combined to achieve the highest efficiency to enhance GPC. We applied these markers in 164 F6 breeding lines and obtained 15 lines with high GPC, indicating their high selective efficiency. Further, strategies for gene exploration in the three significant intervals were proposed. These results were expected to provide a novel route for improving GPC in wheat quality breeding.

scholarly journals Evaluation of grain characteristics of domestic wheat (Triticum aestivum L.) obsolete cultivars and landraces

2020 ◽  
Vol 15 (1) ◽  
pp. 3-9
Author(s):  
Danijela Kondić ◽  
Sanja Oručević Žuljević ◽  
Đurađ Hajder ◽  
Enez Selimbegović
Keyword(s):  
Protein Content ◽  
Triticum Aestivum L ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Thousand Grain Weight ◽  
Grain Width ◽  
Banja Luka ◽  
Grain Surface ◽  
The Relationship ◽  
Obsolete Cultivars

The research on wheat accessions was carried out in order to evaluate their grain characteristics. Experiment was set in the agro-ecological conditions of Banja Luka in two experimental years (2015/16 and 2016/17). Ten obsolete wheat cultivars (Brkulja, Ličanka, Partizanka, Vuka, Talijanka, Šiđanka, Orašanka, Lozničanka, Dokučajevskaja and Nemcitaevskaja) and two landraces (Podrašnica and Previja) were used. Following grain characteristics were evaluated: grain length (mm), grain width (mm), grain thickness (mm), grain volume (mm3), grain surface area (mm2), thousand grain weight (g) and grain protein content (%). Significant interactions were found for most of these traits. The relationship between traits was established by correlation analysis. In this study genotypes Brkulja and Šiđanka showed promising for most of the grain characteristics, while Vuka and Partizanka obtained the highest grain protein content.

Prediction method of single wheat grain protein content based on hyperspectral image

2016 ◽  
Vol 45 (s1) ◽  
pp. 123002
Author(s):  
吴静珠 Wu Jingzhu ◽  
刘 倩 Liu Qian ◽  
陈 岩 Chen Yan ◽  
刘翠玲 Liu Cuiling
Keyword(s):  
Protein Content ◽  
Hyperspectral Image ◽  
Prediction Method ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain

scholarly journals Multi-Temporal and Spectral Analysis of High-Resolution Hyperspectral Airborne Imagery for Precision Agriculture: Assessment of Wheat Grain Yield and Grain Protein Content

2018 ◽  
Vol 10 (6) ◽  
pp. 930 ◽  
Author(s):  
Francelino A. Rodrigues ◽  
Gerald Blasch ◽  
Pierre BlasDefournych ◽  
J. Ivan Ortiz-Monasterio ◽  
Urs Schulthess ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
High Resolution ◽  
Grain Yield ◽  
Protein Content ◽  
Precision Agriculture ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain ◽  
Multi Temporal

Prediction of winter wheat grain protein content by ASTER image

2008 ◽  
Author(s):  
Wenjiang Huang ◽  
Xiaoyu Song ◽  
Jihua Wang ◽  
Zhijie Wang ◽  
Chunjiang Zhao
Keyword(s):  
Winter Wheat ◽  
Protein Content ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain ◽  
Aster Image

Grain yield of wheat in rotation with pea, vetch or medic grown with three systems of management

1990 ◽  
Vol 30 (5) ◽  
pp. 645 ◽  
Author(s):  
JH Silsbury
Keyword(s):  
Grain Yield ◽  
Protein Content ◽  
Green Manure ◽  
Wheat Yield ◽  
South Australia ◽  
Grain Protein Content ◽  
Wheat Crop ◽  
Grain Protein ◽  
Green Manure Crop ◽  
Legume Crop

Pea (Pisum sativum L. cv. Alma), vetch (Vicia sativa L. cv. Languedoc) and annual medic (Medicago truncatula Gaertn. cv. Paraggio) were grown at Brinkworth, South Australia, in 1987 in large (0.75 ha) plots and subjected to 3 systems of management: (i) ploughing in at flowering as a green manure crop, (ii) harvesting for grain and ploughing in the dry residues, and (iii) harvesting for grain and removing the residues. A wheat crop was sown over the whole area in the following season (1988) and the effects of type of legume and management on grain yield and grain protein content were measured. The management system imposed on the legume had a highly significant (P<0.01) effect on the grain yield of the following wheat crop, but there were no significant differences between the 3 legumes in their effects on wheat yield or on grain protein content. Ploughing in the legumes as a green manure crop at flowering added about 100 kg/ha more nitrogen (N) to the soil than allowing the legumes to mature, harvesting for seed, and removing residues. Incorporating the dry residues rather than removing them added about 26 kg N/ha. The green manure crop significantly increased subsequent wheat yield (by 49%; P<0.001) and protein content of the grain (by 13%; P<0.05) compared with the treatment in which the legumes were harvested for grain and all residues removed; incorporating the dry residues increased yield by 10%. It is concluded that the amount of N added during the legume phase in a rotation is more important than the kind of legume from which the N is derived. The occasional use of a dense legume crop as a green manure may rapidly add a large amount of N to a soil to be slowly exploited by following grain crops.

scholarly journals Combining Genomic and Phenomic Information for Predicting Grain Protein Content and Grain Yield in Spring Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Karansher S. Sandhu ◽  
Paul D. Mihalyov ◽  
Megan J. Lewien ◽  
Michael O. Pumphrey ◽  
Arron H. Carter
Keyword(s):  
Grain Yield ◽  
Protein Content ◽  
Spring Wheat ◽  
Grain Filling ◽  
Grain Protein Content ◽  
Spectral Information ◽  
Grain Protein ◽  
Growth Stages ◽  
Prediction Ability ◽  
Secondary Traits

Genomics and high throughput phenomics have the potential to revolutionize the field of wheat (Triticum aestivum L.) breeding. Genomic selection (GS) has been used for predicting various quantitative traits in wheat, especially grain yield. However, there are few GS studies for grain protein content (GPC), which is a crucial quality determinant. Incorporation of secondary correlated traits in GS models has been demonstrated to improve accuracy. The objectives of this research were to compare performance of single and multi-trait GS models for predicting GPC and grain yield in wheat and to identify optimal growth stages for collecting secondary traits. We used 650 recombinant inbred lines from a spring wheat nested association mapping (NAM) population. The population was phenotyped over 3 years (2014–2016), and spectral information was collected at heading and grain filling stages. The ability to predict GPC and grain yield was assessed using secondary traits, univariate, covariate, and multivariate GS models for within and across cycle predictions. Our results indicate that GS accuracy increased by an average of 12% for GPC and 20% for grain yield by including secondary traits in the models. Spectral information collected at heading was superior for predicting GPC, whereas grain yield was more accurately predicted during the grain filling stage. Green normalized difference vegetation index had the largest effect on the prediction of GPC either used individually or with multiple indices in the GS models. An increased prediction ability for GPC and grain yield with the inclusion of secondary traits demonstrates the potential to improve the genetic gain per unit time and cost in wheat breeding.

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