Granule size distribution of wheat starch is an important characteristic that can affect its chemical composition and functionality. Two types of wheat cultivars, the hard and soft wheat cultivars, grown at Tai＇an Ex...Granule size distribution of wheat starch is an important characteristic that can affect its chemical composition and functionality. Two types of wheat cultivars, the hard and soft wheat cultivars, grown at Tai＇an Experimental Station of Shandong Agricultural University, Taian, Shandong, China, were examined in this study. The granule size distribution and amylose contents in wheat grains were studied and compared, and relationships between the properties were identified. A clear bimodal distribution of granule size was shown in all wheat cultivars. Volume distribution of starch granules shows the typical bimodal with peak values in the ranges of 5.6-6.1μm and 20.7-24.9μm, respectively. Also, granule surface area distribution was bimodal with peak values in the ranges of 2.4-3.2μm and 20.7-24.9μm, respectively. Number distribution of granules was a typical population with a peak value in the range of 0.54-1.05μm. Contributions from the granules 〈 2.8μm and 〈 9.9μm to the total volume were in the ranges of 94.2-95.1% and 99.7-99.9% of total number, respectively. Proportions of granules〈2.8μm, 2.8-9.9μm, 9.9-22.8μm, and 22.8-42.8μm were in the ranges of 12.9-14.3%, 28.4-31.1%, 33.5-35.6%, and 19.7-22.7% for hard wheat, and 10.3-13.9%, 26.6-28.1%, 32.7-34.6%, and 24.2-27% for soft wheat. Hard wheat had greater B-type granules （ 〈 9.9μm）, and had fewer granules of 22.8-42.8μm than soft wheat. Amylose content was positively related to volume percentage of granules 22.8-42.8μm, and negatively related to volume percentage of granules 2.8-22.8μm.展开更多
In this study,we revealed the differential proteins from the wheat endosperms using proteomic analysis and investigated their surface properties.The pattern of the polypeptides obtained from the Yangmai-15 and Yangmai...In this study,we revealed the differential proteins from the wheat endosperms using proteomic analysis and investigated their surface properties.The pattern of the polypeptides obtained from the Yangmai-15 and Yangmai-16 wheat varieties were compared using two-dimensional polyacrylamide gels.In addition,we compared the characteristics of the grain such as grain hardness,protein content,wet gluten,dough development time,dough stability,gliadin and glutenin contents between Yangmai-15 and Yangmai-16,and the results were significantly different.Notably,216 and 197 protein spots were separated from Yangmai-15 and Yangmai-16,respectively.The isoelectric points of the identified proteins ranged from 4 to 10 and the molecular weights of proteins varied from 10 to 100 kDa.Further,21 and 8 specific differential protein spots were identified fromthe flour of Yangmai-15 and Yangmai-16,respectively.The surface properties of identified peptides consisted of hydrophobic or hydrophilic residues,as well as randomly scattered residues.The proteomic analysis of the wheat endosperms provides a novel insight into the biochemical basis for the differences in physicochemical properties between the soft and hard wheat varieties.展开更多
By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and ...By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.展开更多
基金the National Key Technologies R&D Program for High-Yielding of Food Crops,China(2006BAD02A09)the Program for Changjiang Scholars and Innovative Research Team in University,Ministry of Education(IRT0635)the Academy Doctoral Subject Scientific Research Foundation,Ministry of Education,China(20060434006)
文摘Granule size distribution of wheat starch is an important characteristic that can affect its chemical composition and functionality. Two types of wheat cultivars, the hard and soft wheat cultivars, grown at Tai＇an Experimental Station of Shandong Agricultural University, Taian, Shandong, China, were examined in this study. The granule size distribution and amylose contents in wheat grains were studied and compared, and relationships between the properties were identified. A clear bimodal distribution of granule size was shown in all wheat cultivars. Volume distribution of starch granules shows the typical bimodal with peak values in the ranges of 5.6-6.1μm and 20.7-24.9μm, respectively. Also, granule surface area distribution was bimodal with peak values in the ranges of 2.4-3.2μm and 20.7-24.9μm, respectively. Number distribution of granules was a typical population with a peak value in the range of 0.54-1.05μm. Contributions from the granules 〈 2.8μm and 〈 9.9μm to the total volume were in the ranges of 94.2-95.1% and 99.7-99.9% of total number, respectively. Proportions of granules〈2.8μm, 2.8-9.9μm, 9.9-22.8μm, and 22.8-42.8μm were in the ranges of 12.9-14.3%, 28.4-31.1%, 33.5-35.6%, and 19.7-22.7% for hard wheat, and 10.3-13.9%, 26.6-28.1%, 32.7-34.6%, and 24.2-27% for soft wheat. Hard wheat had greater B-type granules （ 〈 9.9μm）, and had fewer granules of 22.8-42.8μm than soft wheat. Amylose content was positively related to volume percentage of granules 22.8-42.8μm, and negatively related to volume percentage of granules 2.8-22.8μm.
基金the financial support of the National Natural Science Foundation of China(No.31771897,31871852,and 31772023)
文摘In this study,we revealed the differential proteins from the wheat endosperms using proteomic analysis and investigated their surface properties.The pattern of the polypeptides obtained from the Yangmai-15 and Yangmai-16 wheat varieties were compared using two-dimensional polyacrylamide gels.In addition,we compared the characteristics of the grain such as grain hardness,protein content,wet gluten,dough development time,dough stability,gliadin and glutenin contents between Yangmai-15 and Yangmai-16,and the results were significantly different.Notably,216 and 197 protein spots were separated from Yangmai-15 and Yangmai-16,respectively.The isoelectric points of the identified proteins ranged from 4 to 10 and the molecular weights of proteins varied from 10 to 100 kDa.Further,21 and 8 specific differential protein spots were identified fromthe flour of Yangmai-15 and Yangmai-16,respectively.The surface properties of identified peptides consisted of hydrophobic or hydrophilic residues,as well as randomly scattered residues.The proteomic analysis of the wheat endosperms provides a novel insight into the biochemical basis for the differences in physicochemical properties between the soft and hard wheat varieties.
基金supported by the National Natural Science Foundation of China(30030090)the National 863 Program,China(2001AA115420,2001AA245041).
文摘By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.
