Seed Water Concentration and Accumulation of Protein and Oil in Soybean Seeds

Crop Science

Borrás, Lucas¹  Westgate, Mark E.²  Rotundo, José L.¹  Poeta, Florencia B.¹ 

[1] Departamento de Producción Vegetal, Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, S2125ZAA, Zavalla, Santa Fe, Argentina$$;Agronomy Dep., Iowa State Univ., Ames, IA 50011$$

关键词: Burgess Shale;    Naraoia;    trilobites;    gills;    exopod;    functional morphology;   

DOI  :  10.2135/cropsci2014.03.0204

学科分类：农业科学（综合）

来源: Crop Science

【 摘 要 】

Seed development is partitioned into a ‘lag’ phase, a ‘seed filling’ phase, and a ‘maturation’ phase. Transitions between phases correspond to seed water concentration (WC) values that are fairly consistent within species. For soybean (Glycine max L.), linear seed filling begins at approximately 85% (WCL) and maximum dry weight is attained at approximately 60% (WCM). While such WC values benchmark the progress of seed development, their utility for establishing onset and duration of individual seed chemical component accumulation is not known. Our objectives were (i) to determine WCL and WCM for seed protein, oil, and residual (mostly carbohydrates), (ii) to assess stability across genotypes and environments, and (iii) to investigate their relationship with the duration of accumulation. The WCL and WCM for oil, protein, and residual were significantly different. Values were higher for residual and lower for oil. Since seeds desiccate throughout their development, residual accumulation was initiated first, followed by protein, then by oil. The parameter WCL was more stable across genotypes than was WCM. Genotypes with lower WCM values had a longer duration of component accumulation. Increasing assimilate supply per seed decreased WCL for all seed components, but had little impact on WCM. Our results indicate that a water relations framework can be used to characterize accumulation patterns of individual seed components across genotypes and environments, providing a common basis for modeling the composition of soybean seeds.

【 授权许可】

Unknown