Submitted to: Meeting Proceedings
Publication Type: Abstract only
Publication Acceptance Date: 9/19/2007
Publication Date: 9/19/2007
Citation: Walters, C. 2007. Biophysical Approaches to Measure and Predict Seed Longevity. Meeting Abstract for the First symposium of Translational Biology in Seeds. September 17-20, 2007, Davis, California. pp. 12. Interpretive Summary: This meeting was designed to show how fundamental research using model systems is directly applied to solve agricultural problems. Research presented by this work evaluated current methods used to predict seed longevity and demonstrated how biophysical principles are being applied to understand the mechanism of seed deterioration so that faster, non-invasive tests can be developed.
Technical Abstract: Wouldn’t it be great if we could predict seed longevity? With reliable predictive tools, we would be able to determine which seed lots to sell and which to carry over to the next year, schedule new plantings, economize on storage and packaging systems, know the long-term effects of pretreatments, obviate (or at least reduce) viability monitoring, and breed for longer living seeds. But, seed longevity is difficult to predict. Early symptoms of deterioration are masked, and then viability declines quickly. The duration of the symptomless phase and the steepness of the catastrophic phase are affected by a host of parameters that have yet to be researched. Earlier attempts to predict seed longevity measured simulated aging under warm, humid conditions. We now know that reaction dynamics under simulated conditions may not reflect conditions at which seeds are actually stored or transported. A biophysical approach based on viscoelastic properties and reaction cooperativity is used to model seed aging time courses and reliably predict the onset of rapid viability loss. Viscosity in aqueous cytoplasm is inferred from relaxation of the glassy matrix, which is calculated from heat capacity measurements or water sorption energy. Fluidity within oil bodies is inferred from the crystallization rate of triacylglycerols. Mobility within hydrophilic and lipid domains of dry seeds correlates with seed aging and temperature coefficients appear to be similar across diverse taxa. The model enables us to address moisture anomalies arising from excessively high and low humidity storage. Applications of the work may lead to single seed assessments of quality, real-time assessments of storage conditions and impact on quality, and a fundamental understanding of cellular factors that distinguish long and short- lived seeds.