Some aspects of seed germination in vegetables. 1. The determination and application of heat sums and minimum temperature for germination

Bierhuizen, J.F.; Wagenvoort, W.A.

doi:10.1016/0304-4238(74)90029-6

Cited by 107 publications

(49 citation statements)

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“…Clearly germination rates differ between cultivars (Corbineau, Picard & Co# me, 1994), but it is likely that in carrots, bases do not vary greatly as a very similar Ψ b (k0n81 MPa ; Ross & Hegarty, 1979) and a similar T b (1n4 mC ; Bierhuizen & Wagenvoort, 1974) were recorded for cvs unrelated to those used here. In the experiments presented, a seed lot from a closely related genotype was selected for constant environment experiments (cv.…”

Section: Threshold Germination Models Under Constant Conditionsmentioning

confidence: 63%

“…However, under good horticultural practice, soil temperature and water potential are arguably the major influences on the timing and pattern of seed germination and seedling emergence in the field. The threshold models of thermal time (Bierhuizen & Wagenvoort, 1974 ;Garcia-Huidobro, Monteith & Squire, 1982) and hydrothermal time (Gummerson, 1986 ;Dahal & Bradford, 1994 ;Bradford, 1995) have been developed to describe the germination responses of a population of seeds to temperature and water potential under constant conditions, but little is known of their descriptive ability under field conditions.…”

Section: mentioning

confidence: 99%

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Germination and post‐germination growth to carrot seedling emergence: predictive threshold models and sources of variation between sowing occasions

Finch‐Savage¹,

Steckel²,

Phelps³

1998

New Phytologist

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Cumulative germination curves were recorded for carrot (Daucus carota L.) seeds at a range of constant temperatures (T ) and water potentials (Ψ) in the laboratory and under variable soil conditions in 15 seed-bed environments in the field. A single base temperature (T b ), a distribution of base water potentials (Ψ b (G)) for percentiles (G) of the population and the hydrothermal time constant (H g ) were determined from laboratory data. Although less effective at low Ψ, it was possible, using these germination parameters, to satisfactorily describe the effect of T and Ψ on germination rates under constant conditions according to the threshold models of thermal and hydrothermal time. These models were applied to field data with the condition that the germination process ceased if T T b for thermal time and additionally Ψ Ψ b (G) for hydrothermal time.Neither model accurately predicted germination patterns in the field. However, the pattern of germination was adequately described in most situations by a modified threshold model in which the predicted progress towards germination was unaffected by soil Ψ, provided it remained above Ψ b (G), and was therefore more rapid under variable seed bed conditions than hydrothermal time. In this modified threshold model, the condition Ψ Ψ b (G) had to be fulfilled at the initiation of radicle extension before germination occurred. This result implies that the initiation of radicle growth operates as a moisture-sensitive step that can determine germination and seedling emergence timing under variable soil-moisture conditions.Seedling emergence was also recorded in the field and used to determine, separately, the impact of germination and post-germination growth on the variation in seedling emergence patterns. The analysis suggests that delays in seedling emergence occur largely in the germination phase, but that seedling losses and variation in the spread of seedling emergence times within the population occur largely during the post-germination growth phase.

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Section: Threshold Germination Models Under Constant Conditionsmentioning

confidence: 63%

Section: mentioning

confidence: 99%

Germination and post‐germination growth to carrot seedling emergence: predictive threshold models and sources of variation between sowing occasions

Finch‐Savage¹,

Steckel²,

Phelps³

1998

New Phytologist

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“…1/t 50 for 50% germination) generally increase linearly between the minimum or base temperature (T b ) and the optimum temperature (T o ), as in the degree-days or thermal time model, θ T (g) = (T -T b ) t g , where θ T (g) is the thermal time required from imbibition until radicle emergence of fraction or percentage g and T is the temperature at which the seeds are imbibed. The thermal time model has been applied extensively to describe seed germination timing in response to temperature (Bierhuizen and Wagenvoort, 1974;Garcia-Huidobro et al, 1982;Covell et al, 1986;Dahal et al, 1990;Alvarado and Bradford, 2002). Since all seeds in a population do not germinate simultaneously, germination rates of seed populations (rather than of specific percentages) can be analysed by transforming the cumulative germination percentages to probits and plotting versus a log time scale (Covell et al, 1986;Dahal et al, 1990).…”

Section: Germination and Respiration Responses To Temperature (Thermamentioning

confidence: 99%

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

Bello

Bradford

2016

Seed Sci. Res.

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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.

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“…The germination rate usually increases linearly with temperature within the suboptimal temperature range (Hegarty 1973, Bierhuizen & Wagenvoort 1974, Dau & Labouriau 1974, Thompson & Fox 1976, Whashitani & Takenaka 1984, Perez & Moraes 1990. As shown in the fi gure 2, up to 35 °C the germination rates increased linearly with temperature, the intercept is at 9 °C which differs from the experimental minimum that is between 10 ° and 15 °C.…”

Section: Discussionmentioning

confidence: 99%

Isothermal seed germination of Adenanthera pavonina

Zpevak¹,

Gualtieri²,

Buckeridge

2012

Braz. J. Bot.

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-(Isothermal seed germination of Adenanthera pavonina). This work reports aspects of seed germination at different temperatures of Adenanthera pavonina L., a woody Southeast Asian Leguminosae. Germination was studied by measuring the fi nal percentages, the rate, the rate variance and the synchronisation of the individual seeds calculated by the minimal informational entropy of frequencies distribution of seed germination. Overlapping the germinability range with the range for the highest values of germination rates and the minimal informational entropy of frequencies distribution of seed germination, we found that the best temperature for the germination of A. pavonina seeds is 35 °C. The slope μ of the Arrhenius plot of the germination rates is positive for T < 35 °C and negative for T > 35 °C. The activation enthalpies, estimated from closely-spaced points, shows that |∆H-| < 12 Cal mol -1 occur for temperatures in the range between 25 °C and 40 °C. The ecological implication of these results are that this species may germinate very fast in tropical areas during the summer season. This may be an advantage to the establishment of this species under the climatic conditions in those areas.

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Some aspects of seed germination in vegetables. 1. The determination and application of heat sums and minimum temperature for germination

Cited by 107 publications

References 1 publication

Germination and post‐germination growth to carrot seedling emergence: predictive threshold models and sources of variation between sowing occasions

Germination and post‐germination growth to carrot seedling emergence: predictive threshold models and sources of variation between sowing occasions

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

Isothermal seed germination of Adenanthera pavonina

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