Quercus robur L. is a valuable wood species having long ontogeny and promising to create long-living artificial plantings of recreational and ameliorative purposes in the steppes zone of Russia and other countries. In this work we have performed the genotyping of varieties of Quercus robur L. obtained from collection of Botanical Garden of Southern Federal University using intersimple sequence repeat (ISSR) molecular markers. The most polymorphic ISSR-marker (GA) 8YC was found in the collection. The polymorphic DNA markers identified in the present study can be used for the future breeding works to obtain valuable genotypes of Quercus genus. In addition we have performed DNA fingerprinting of the prospective sample of the variety Q. robur var. tardiflora Czern.

Far-Red Spectrum of Second Emerson Effect: A Study Using Dual-Wavelength Pulse Amplitude Modulation Fluorometry

Hibiscus moscheutos L. ‘Berry Awesome’ is a complex hybrid of the new Proven Winners Summerific series of varieties with highly ornamental characteristics. Micropropagation of highly ornamental varieties is important for mass production of planting material for commercial purposes. The traditional methods for propagating Hibiscus varieties, such as cuttings or seed propagation, however, do not guarantee high rates of production of high-quality seedlings. To solve this problem, an attempt was made to develop protocols for micropropagation of Hibiscus moscheutos L. ‘Berry Awesome’ in vitro on agar and liquid medium using a bioreactor system, followed by ex vitro adaptation of the regenerants. The optimal method for sterilization of nodal explants as well as the optimal composition of the initiation medium for shoot proliferation and rooting were determined. For micropropagation on a liquid medium, a rocker-type bioreactor was used, and its advantages over micropropagation on an agar medium were demonstrated. The results showed that the best sterilization method for nodal segment explants was as follows: pretreatment by rinsing with running tap water, sterile water, and distilled water for 70 min and soaking for 5 min in a mixture of solutions of ethyl alcohol (96%), hydrogen peroxide (38%), and water in a ratio of 1:1:2. In this case, live and sterile explants accounted for 62.6%. The optimal initiation medium for axillary buds in nodal segments was the Murashige and Skoog (MS) medium supplemented with 0.1 mg L⁻¹ N-(2-chloro-4-pyridinyl)-N’-phenylurea (CPPU), which resulted in 73.3% of axillary buds being induced. The optimal solid proliferation medium was MS medium supplemented with 0.1 mg L⁻¹ CPPU with a proliferation coefficient of 5.8. In a liquid medium, the optimal concentration of CPPU was 0.05 mg L⁻¹ with a proliferation coefficient of 9.2. The best medium for rooting/shoots with agar and in bioreactors was MS medium with the addition of 0.1 mg L⁻¹ indole-3-butyric acid (IBA). The highest rooting rate was 99.0% in both types of media, and the survival rate of plantlets was 88.7% in solid media and 98.7% in the bioreactor.

The development of remote methods for identifying plant light stress (LS) is an urgent task in agriculture and forestry. Evergreen conifers, which experience winter light stress (WLS) annually, are ideal subjects for studying the mechanisms of light stress and developing identification methods. Proximal hyperspectral imaging (HSI) was used to identify WLS in Platycladus orientalis. Using the random forest (RF), the spectral characteristics of P. orientalis shoots were analysed and the conditions ‘Winter Light Stress’ and ‘Optimal Condition’ were classified with high accuracy. The out-of-bag (OOB) estimate of the error rate was only 0.35%. Classification of the conditions ‘Cold Stress’ and ‘Optimal Condition’—with an OOB estimate of error rate of 3.19%—can also be considered successful. The conditions ‘Winter Light Stress’ and ‘Cold Stress’ were more poorly separated (OOB error rate 15.94%). Verifying the RF classification model for the three states ‘Optimal condition’, ‘Cold stress’ and ‘Winter Light Stress’ simultaneously using data from the crown field survey showed that the ‘Winter Light Stress’ state was well identified. In this case, ‘Optimal condition’ was mistakenly defined as ‘Cold stress’. The following vegetation indices were significant for identifying WLS: CARI, CCI, CCRI, CRI₅₅₀, CTRI, LSI, PRI, PRI_m1, modPRI and TVI. Therefore, spectral phenotyping using HSI is a promising method for identifying WLS in conifers.