The timing of the germination of seeds is highly responsive to inputs from the environment. Temperature plays a key role in the control of germination, with low temperatures acting to stimulate this developmental transition in many species. In Arabidopsis, extensive gene expression changes have been reported at the whole seed level in response to cold, while much less is known about their spatial distribution across the diverse cell types of the embryo. In this study we examined the spatiotemporal patterns of promoter activity and protein abundance for key gibberellic acid (GA) and abscisic acid (ABA) factors which regulate the decision to germinate both during a time course of germination and in response to cold. Low temperature stimulated the spatial relocalization of these factors to the vasculature. The response of these seeds to dormancy-breaking stratification treatments therefore stimulates the distribution of both positive (GA) and negatively acting (ABA) components to this same cell type. This altered spatial pattern persisted following the transfer of seeds to 22°C, as well as after their rehydration, indicating that this alteration is persistent. These observations suggest that the vasculature plays a role in the low temperature-mediated stimulation of germination in this species, while novel cell types are recruited to promote germination in response to stratification.

The effects of cold atmospheric plasma (CAP) of dielectric barrier discharges on the wettability, imbibition and germination of Leucaena leucocephala were investigated. It was established that CAP treatment markedly hydrophilized the seed coat, especially at longer treatment times. From the profile of the imbibition curve and visual observation, it was possible to verify that there are two resistance barriers to water penetration: integument surface and region of the macrosclereid cell wall (light line). Although the plasma interacts only in the integument, increasing the density of hydrophilic sites increases the capacity of water absorption, producing enough driving force to overcome the second resistance barrier. The existence of these two barriers changes the three-phase pattern generally observed during seed germination. Despite an increase in imbibition, the plasma treatment conditions used in this work, were not enough to overcome completely the dormancy barrier.

Cultivated northern wild rice (NWR; Zizania palustris L.) has been bred and studied since the 1950s. One challenge facing researchers is the lack of storage options, due to the seed's unorthodox behaviour. This study evaluated varying storage temperature and moisture conditions for the maintenance of seed viability and dormancy breaking in Minnesota-grown NWR. First, seeds were placed in non-submerged, freezing storage (NSFS) for 12–26 weeks, then in submerged, cold storage (SCS) for 2 weeks. The addition of SCS increased germination (%G) relative to NSFS alone (<0.1% NSFS, 15% NSFS and SCS), indicating that NSFS does not kill seeds but also does not break seed dormancy. Next, the required length of SCS was evaluated by placing seeds in NSFS for 12 weeks and then in SCS for 2–14 weeks. A longer SCS period increased %G from 3 to 79%, at 2 and 14 weeks of SCS, respectively. Lastly, seeds were placed in NSFS, followed by SCS, at varying intervals over a 29-week period. Across lines, germination increased from 20 to 76% between 4 and 7 weeks of SCS, respectively, then plateaued. The results of this study indicate that NSFS could be used to store NWR seeds, but at least 7 weeks in SCS is required to overcome dormancy. Additionally, while NSFS did not break seed dormancy, physiological changes related to stratification processes were occurring in non-submerged, freezing conditions. Results also suggest that the genotypic variation in NWR could be utilized for selection to improve germination and storage viability.

Information about seed dormancy cycling and germination in relation to temperature and moisture conditions in the natural environment is important for the conservation and restoration of rare species, including Begonia guishanensis and Paraisometrum mileense, two sympatric perennial limestone (karst) species. Dry afterripening (DAR) and wet and dry (WD) cycles at 15/5 and 25/15°C as well as moist chilling (MC) at 15/5°C were used to mimic the natural environment at different times of the year. A field experiment was conducted to monitor seasonal changes in germination responses of the seeds. About 40–65% of B. guishanensis and 5% of P. mileense seeds were dormant at maturity. DAR at 25/15 and 15/5°C as well as MC and WD cycles at 15/5°C alleviated dormancy for B. guishanensis but not P. mileense, and WD cycles at 25/15°C induced a deeper conditional dormancy for both species. Seeds of B. guishanensis exhibited dormancy cycling in the field, with increased dormancy under natural WD cycles at relatively high temperatures during the transition from the dry to the wet season in April to May and decreased dormancy during the wet season from June to October. KNO3 mitigated the dormancy-inducing effect of both artificial and natural WD cycles at relatively high temperatures for B. guishanensis. The field experiment indicated that seeds of B. guishanensis may be able to form a persistent soil seed bank, while almost all seeds of P. mileense germinate at the beginning of the wet season in the field.

Only a few studies have been performed on seed germination of perennial ephemeral species native to the cold deserts of central Asia. We hypothesized that seeds of the cold desert perennial ephemeral Leontice incerta exhibit versatility in the timing of germination, that is, having the capacity to germinate at any time in summer, autumn and next spring. At dispersal in late May, only about 30% of the seeds could germinate; thus, a high percentage of the seeds was dormant. Seeds had a fully developed embryo, and dry storage, cold stratification, warm stratification and gibberellin promoted germination; we concluded that they have non-deep physiological dormancy. Seeds buried under natural conditions during summer germinated to 57–86% in autumn (late October) when exhumed and incubated at 5/2–25/15°C. However, seeds were sown in soil exposed to natural temperature and (low) precipitation did not germinate until next spring when the soil was moist. Thus, like various cold desert annuals, seeds of the perennial L. incerta can germinate in summer, autumn and next spring, depending on the availability of soil moisture (rainfall). Rainfall in cold deserts can play an important role in shaping seed germination traits of desert plants.

In the tetraploid Tulipa sylvestris we found larger and heavier seeds that germinated around 28 days earlier than those of the diploid ancestor Tulipa pumila. The faster germination of the tetraploid species is linked to the faster growth of embryos, which reached their final length much earlier than the embryos of the diploid species. In conclusion, we argue a cautionary approach when dealing with comparative studies on ploidy level and germination to avoid misinterpretation of results when set against the natural conditions.

The prediction of seed longevity (P50) is traditionally performed by the use of the Probit model. However, due to the fact that the survival data are of binary origin (0,1), the fit of the model can be compromised by the non-normality of the residues. Consequently, this leads to prediction losses, despite the data being partially smoothed by Probit and Logit models. A possibility to reduce the effect of non-normality of the data would be to apply the principles of the central limit theorem, which states that non-normal residues tend to be normal as the n sample is increased. The Logit and Probit models differ in their normal and logistic distribution. Therefore, we developed a new estimation procedure by using a small increase of the n sample and tested it in the Probit and Logit functions to improve the prediction of P50. The results showed that the calculation of P50 by increasing the n samples from 4 to 6 replicates improved the index of correctness of the prediction. The Logit model presented better performance when compared with the Probit model, indicating that the estimation of P50 is more adequate when the adjustment of the data is performed by the Logit function.

Seed lot heterogeneity is often evaluated through the range between germination percentages of four seed samples, considering normal and binomial approximations for calculating the tolerated range (S). In this paper, an exact test for the germination count range (R) is derived based on the hypergeometric and the binomial probability model for germination count. Through Monte Carlo simulations, the empirical distribution of R is built to evaluate the quantiles of the exact distributions. Moreover, a power analysis is performed by simulation. Sample size and germination rate effects are evaluated. In lots with a high germination rate, the proposed test based on the hypergeometric model is about 20% more powerful than the test based on the S-value. A table containing the critical values is presented and recommended to be used in off-range heterogeneity testing.

Hydrothermal time (HTT) models describe the time course of seed germination for a population of seeds under specific temperature and water potential conditions. The parameters of the HTT model are usually estimated using either a linear regression, non-linear least squares estimation or a generalized linear regression model. There are problems with these approaches, including loss of information, and censoring and lack of independence in the germination data. Model estimation may require optimization, and this can have a heavy computational burden. Here, we compare non-linear regression with survival and Bayesian methods, to estimate HTT models for germination of two clover species. All three methods estimated similar HTT model parameters with similar root mean squared errors. However, the Bayesian approach allowed (1) efficient estimation of model parameters without the need for computation-intensive methods and (2) easy comparison of HTT parameters for the two clover species. HTT models that accounted for a species effect were superior to those that did not. Inspection of credibility intervals and estimated posterior distributions for the Bayesian HTT model shows that it is credible that most HTT model parameters were different for the two clover species, and these differences were consistent with known biological differences between species in their germination behaviour.