Onion (<i>Allium cepa</i>L.) Seedling Emergence Patterns can be Explained by the Influence of Soil Temperature and Water Potential on Seed Germination

Finch‐Savage, W. E.; Phelps, K.

doi:10.1093/jxb/44.2.407

Cited by 99 publications

(66 citation statements)

References 19 publications

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“…Variation in emergence times is generated by assuming a normal distribution of cotyledon protrusion rates and of shoot elongation rates in the population, with a constant coefficient of variation f gr . This accords with the findings of Finch-Savage & Phelps (1993), who reported that the normal distribution applied to rates provided the best fit to the emergence data of onion seedlings. In a constant environment, a normal distribution of pre-emergence growth rates generates a skew distribution of emergence times that exactly resembles a Gompertz curve when plotted cumulatively.…”

Section: Induction Of Dormancysupporting

confidence: 92%

Modelling field emergence patterns in arable weeds

2000

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A model was developed to simulate weed emergence patterns after soil cultivation. In the model, the consecutive processes of dormancy release, germination and pre-emergence growth were modelled in separate modules. Input variables of the model were : date of soil cultivation, soil temperature and soil penetration resistance. Output variables of the model were : seedling density and timing of seedling emergence. The model was parameterized for Polygonum persicaria, Chenopodium album and Spergula arvensis with data from previous field and laboratory experiments. The model was evaluated with data from an experiment, in which emergence of P. persicaria, C. album and S. arvensis was monitored in field plots that were cultivated once only, at one of five dates in the spring. At the same time as the field observations on seedling emergence, seasonal changes in seed dormancy of the buried weed seeds were assessed by testing the germination of seed lots that were buried in envelopes. From a comparison between field observations and simulated data, it appeared that the model overestimated the rate of dormancy release in spring, whereas germination and pre-emergence growth were simulated well. In general, therefore, both the numbers of emerging seedlings and the timing of emergence could be predicted accurately, when dormancy was not simulated but introduced from experimental data. Improvement of predictions of field emergence of weeds should mainly focus on increasing the precision of the simulation of dormancy release. Close correlations were found between seedbed temperature and both the extent and rate of seedling emergence, but analysis with the simulation model revealed that they were only partly based on causal relationships, so that they have limited predictive value.

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Section: Induction Of Dormancysupporting

confidence: 92%

Modelling field emergence patterns in arable weeds

2000

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“…Our estimates of base moisture potential for each population fraction, c b (g), were approximately normally distributed around the median value as might be expected for seeds (Bradford, 2002). The c b (50) estimate of À1.56 MPa found here was within the estimates from seed germination studies using crop species which ranged from À1.10 to À1.96 MPa (Gummerson, 1986;Finch-Savage and Phelps, 1993;Kebreab and Murdoch, 1999). In the field trials, 5-6% volumetric water, which is about À1.5 MPa based on moisture release curves for the sandy loam used here (Brady, 1974), seems to be the critical moisture level below which development ceases.…”

Section: Discussionsupporting

confidence: 72%

“…The number of units required to reach a particular stage of development is referred to as the hydrothermal time constant and can be used by biological modelers to predict when a species will be at a particular phenological stage in a region where temperature and moisture levels are known. Although this model has successfully been used to describe seed germination times across a range of suboptimal temperatures and water potentials (Gummerson, 1986;Finch-Savage and Phelps, 1993), other studies have found it unsatisfactory for certain species due to a significant interaction between temperature and moisture effects (Kebreab and Murdoch, 1999).…”

Section: Introductionmentioning

confidence: 99%

Hydrothermal and thermal time models for the invasive grass, Arundo donax

Graziani

Steinmaus

2009

Aquatic Botany

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“…Hydrothermal time (Gummerson, 1986), provides a basis for describing such patterns, and has been extended to whole populations for lettuce (Lactuca sativa) and tomato (Lycopersicon esculentum) by Bradford (1990) and Dahal & Bradford (1994), respectively. Finch-Savage & Phelps (1993) have shown that a simple model of emergence, based on threshold water potential and temperature, can account for varying patterns of seedling emergence in onion (Allium cepa). A similar approach has also been applied successfully to processes outside seed biology, such as the forecasting of conidial production by sclerotia of Botrytis squamosa (Clarkson et al, 2000).…”

Section: mentioning

confidence: 99%

Modelling the germination of Stellaria media using the concept of hydrothermal time

Grundy¹,

Phelps²,

Reader³

et al. 2000

New Phytologist

121

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The germination characteristics of Stellaria media (common chickweed) were investigated over a range of constant temperatures and degrees of moisture stress in order to assess the suitability of hydrothermal time as a basis for modelling germination under field conditions. Maximum percentage germination occurred over a much narrower temperature range around the optimum temperature than previously seen for cultivated crop seed. The entire final percentage germination response to temperature in water was well described by two probit curves, and this model was extended to describe the data at all water potentials at a temperature close to the optimum. The implications of the reduction in germination at nonoptimal temperatures are discussed with respect to the interpretation of germination progress curves and conditional dormancy. After adjusting for maximum percentage germination, a hydrothermal time model was found to fit the data set well within the conditions normally encountered in horticultural seedbeds. This separation of the final percentage germination presents a flexible modelling approach that allows for the different levels of dormancy typically expressed within weed populations. By contrast with many previously reported species, S. media had a synchronous germination rate within the population at any given temperature\water potential combination. This synchronous germination of at least a proportion of the population over a wide range of temperature and water potentials might have ecological significance for the opportunistic germination behaviour of this weed species.

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Onion (Allium cepaL.) Seedling Emergence Patterns can be Explained by the Influence of Soil Temperature and Water Potential on Seed Germination

Cited by 99 publications

References 19 publications

Modelling field emergence patterns in arable weeds

Modelling field emergence patterns in arable weeds

Hydrothermal and thermal time models for the invasive grass, Arundo donax

Modelling the germination of Stellaria media using the concept of hydrothermal time

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