Single-seed oxygen consumption measurements and population-based threshold models link respiration and germination rates under diverse conditions

Abstract

Seed germination is responsive to diverse environmental, hormonal and chemical signals. Germination rates (i.e. speed and distribution in time) reveal information about timing, uniformity and extent of germination in seed populations and are sensitive indicators of seed vigour and stress tolerance. Population-based threshold (PBT) models have been applied to describe germination responses to temperature, water potential, hormones, ageing and oxygen. However, obtaining detailed data on germination rates of seed populations requires repeated observations at frequent times to construct germination time courses, which is labour intensive and often impractical. Recently, instruments have been developed to measure repeatedly the respiration (oxygen consumption) of individual seeds following imbibition, providing complete respiratory time courses for populations of individual seeds in an automated manner. In this study, we demonstrate a new approach that enables the use of single-seed respiratory data, rather than germination data, to characterize the responses of seed populations to diverse conditions. We applied PBT models to single-seed respiratory data and compared the results to similar analyses of germination time courses. We found consistent and quantitatively comparable relationships between seed respiratory and germination patterns in response to temperature, water potential, abscisic acid, gibberellin, respiratory inhibitors, ageing and priming. This close correspondence between seed respiration and germination time courses enables the use of semi-automated respiratory measurements to assess seed vigour and quality parameters. It also raises intriguing questions about the fundamental relationship between the respiratory capacities of seeds and the rates at which they proceed toward completion of germination.

Hydrothermal sensitivities of seed populations underlie fluctuations of dormancy states in an annual plant community

“…Thus, physiological or functional characterization of seed biology must be based on the distribution of physiological states or germination behaviors among seeds in a population (Roberts , Bradford ). The characteristic right‐skewed sigmoid pattern of cumulative germination percentages of a seed population under a wide range of conditions can be well described by population‐based models utilizing a normal frequency distribution of parameters (Bello and Bradford , Bradford ). Such models can characterize not only the average behavior, but also the variability among individuals in their germination timing, which is a critical component of an opportunistic versus a bet‐hedging strategy and sets the stage for the subsequent phenotypic and fitness variation in the germinants.…”

“…Such models can characterize not only the average behavior, but also the variability among individuals in their germination timing, which is a critical component of an opportunistic versus a bet-hedging strategy and sets the stage for the subsequent phenotypic and fitness variation in the germinants. These models are collectively referred to as "population-based threshold" (PBT) models, notably the thermal time (TT), hydrotime (HT), and hydrothermal time (HTT) models (Garcia-Huidobro et al 1982, Gummerson 1986, Bradford 1990, Alvarado and Bradford 2002, Batlla and Benech-Arnold 2015, Donohue et al 2015, Bello and Bradford 2016.…”

Measuring metabolic rates of small terrestrial organisms by fluorescence-based closed-system respirometry

“…The signal to noise ratio is significantly reduced in quiescent seeds compared with germinating seeds, and to compensate for this we have measured more than one individual seed per chamber. This may offset some of the intrinsic utility suggested for repeated-measures fluorometric respirometry in making single seed measurements (as per Bello and Bradford, 2016), but this is countered somewhat by our ability to measure many replicate chambers at once. Finally, the interactions between seed dormancy status and MR is not well understood (Dalziell and Tomlinson, 2017), and the relationship between seed dormancy and germination/respiration is unclear (Bello and Bradford, 2016;Booth and Sowa, 2001;Bradford et al, 2007;Footitt and Cohn, 1995).…”

“…Once the respirometry chamber is sealed, however, and assuming the chamber is rigid, changing water vapour pressure affects P O2 and O 2 mole fraction in opposite directions. Effectively, changes in P O2 and mole fraction of O 2 balance each other out, which is the previously unreported basis of how the Q 2 fluorescence analyser measures P O2 independent of chamber humidity (Bello and Bradford, 2016;Bradford et al, 2013;Van Asbrouck and Taridno, 2009).…”

“…The automation of such repeated measurements has recently been specifically developed for measuring O 2 consumption in an aerial closed respirometry system of seeds (Bradford et al, 2013) and leaf tissue of Arabidopsis (Scafaro et al, 2017). Previous studies have used standardised O 2 depletion as a proxy for MR of seeds from highly selectively bred cultivars; for example, in relation to the seed quality of tomato and lettuce varieties (Bello and Bradford, 2016;Bradford et al, 2013). Here, we refine the handling and processing of closed-system fluorometric data to calculate MR in traditional units (e.g.…”