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HomeAP AP14871004 (superviser Dolgikh S.)

AP AP14871004 (superviser Dolgikh S.)

Brief description of the project

(2022-2024)

 

Project title: IRN AP14871004 « Investigation of phytopathological and botanical aspects of wild apple populations growing in the Northern Tien Shan ».

 Relevance. Wild plants are the originators of all cultivated plants and are an important source of genetic material for improving the quality of crops. Despite the high value of wild fruit plants, over the past decades their habitat suffers of catastrophic reduction, a decrease in biodiversity, as well as degradation of natural forests. These problems threaten the species diversity and ecosystems. The wild apple communities of Kazakhstan are based on a valuable apple species – Malus sieversii, the direct ancestor of the cultivated apple. However, in the country, up to 70% of apple forests have been reduced over the past 40 years. The wild apple populations requires conservation, rational use and regeneration.

 The goal of the project: The aim of the project is the ecological and biological study of wild apple populations on the territory of Djungarskiy and Zailiyskiy Alatau using modern molecular genetic methods, GIS and IT to maintain genetic diversity, monitor and revival demolished wild populations of apple.

 Expected results:

1)at least two articles and (or) reviews in peer-reviewed scientific journals in scientific direction of project, indexed in Science Citation Index Expanded of WoS database and (or) having a CiteScore percentile in Scopus database of at least thirty five;

either at least one article or review in peer-reviewed scientific publication in scientific direction of project, indexed in Science Citation Index Expanded of Web of Science database and (or) having a CiteScore percentile in Scopus database of at least thirty five, and at least one patent included in Derwent Innovations Index database (WoS);

at least one article or review in peer-reviewed journal recommended by Committee for Control of Education and Science Ministry of Education and Science of the Republic of Kazakhstan;

either at least one article or review in peer-reviewed scientific publication included in first quartile of impact factor in WoS database;

Intended Journals: Information Processing in Agriculture, CiteScore 2020- 9.9, Percentile -99%, Q-1 https://www.scopus.com/sources.uri; Plant Disease, CiteScore 2020- 3.0, Percentile -71%, Q-1, https://www.scopus.com/sourceid/60195; Neural Networks, CiteScore 2020 — 10.9, Percentile -97%, Q-1 https://www.scopus.com/sourceid/24804.

2) not provided

3) a patent for developed maps of two populations of wild apple trees and copyright certificate for neural network model will be obtained.

4) not provided

5) methodological manuals based on results of study will be published and disseminated, maps of populations and data on infectious background, results of forecasting development of populations will be published.

6.1) rational nature management, phytopathology, computer science, agriculture. KazNII of nature management and agricultural direction, KazNII of fundamental research in the field of geography and biology, computer science.

6.2) The results obtained during the implementation of project will reveal influence of main biotic and abiotic factors on safety of wild apple populations, predict vector of population development using modern methods of ecology, phytopathology and computer science. For the first time, accurate geoinformation mapping of two populations will be carried out with determination of GPS parameters of each tree, which will allow real-time monitoring of state of these populations and apply method to other populations of wild plants to improve quality of monitoring. The developed neural network model can be used to predict the development of other populations apple trees and retrained for study of different plant species, which will intensify sector of rational nature management and agro-industrial sector. The detection of viral pathogens in wild apple population is being carried out for the first time and resistance of the wild apple to five viruses will be shown, which will serve as the basis for studying the genetic basis of resistance to viral infections. The developed forecast model based on neural networks will make it possible to take timely measures to preserve the gene pool of the wild apple tree.

The developed complex methodology for studying populations in this project can be tested on large populations and is applicable to tracking the health of populations of wild plants in the world.

6.3) The developed complex methodology for studying development of populations of  wild apple tree can be applied to analysis of different populations of wild apple tree and other plant species in order to preserve and rational use of biodiversity. The results of study have a high potential for commercialization and can be used to provide services for forecasting the productivity of fields and orchards of cultivated plants.

6.4) studies of populations of wild plants will improve methods of their monitoring to preserve the country’s gene pool, prevent the degradation of populations of especially valuable plant species. Preservation of the wild apple gene pool will make it possible to rationally use it for targeted selection of cultivated apple varieties with high economically valuable traits. In addition, wild apple populations support beneficial insects such as bees, whose populations are declining at a catastrophic rate each year. The availability of maps of populations and results of influence of biotic and abiotic factors on their development in dynamics will lead to environmental literacy of population and will allow every citizen of country to assess the level of conservation of the country’s biodiversity.

6.5) plant material will be preserved for identification of pathogen strains and identification of genetic relationships with pathogens in the European, American and Asian regions. An atlas will be developed with a photograph and a botanical description of each tree in the population, fruits will be collected from each tree of the two populations to isolate seeds and preserve them for breeding needs.

 Scientific Supervisor of the project: Dolgikh Svetlana

 Research group: 

  1. Gritsenko D.
  2. Dzhumanova Zh.
  3. Soltanbekov S.
  4. Khusnitdinova M.
  5. Taskuzhina A.
  6. Abdrakhmanova A. 

List of publications of the project’s participants (2017-2022)

  1. Bassova, T., Khusnitdinova, M., Geldyeva, G., & Skorintseva, I. (2016). Anthropogenic disturbance of landscapes in the border area of Kazakhstan and Kyrgyzstan. International Multidisciplinary Scientific GeoConference: SGEM, 2, 45-52. Индекс цитирования – 0, DOI — 10.5593/SGEM2016/B52/S20.007
  2. Barrett, T., Feola, G., Khusnitdinova, M., & Krylova, V. (2017). Adapting agricultural water use to climate change in a post-Soviet context: Challenges and opportunities in Southeast Kazakhstan. Human ecology, 45(6), 747-762. Индекс цитирования – 16, Процентиль – 91, Квартиль- Q2
  3. Barrett, T., Feola, G., Krylova, V., & Khusnitdinova, M. (2017). The application of Rapid Appraisal of Agricultural Innovation Systems (RAAIS) to agricultural adaptation to climate change in Kazakhstan: A critical evaluation. Agricultural Systems, 151, 106-113. Индекс цитирования – 6, Процентиль – 99, Квартиль- Q1.
  4. Omasheva, M., Pozharskiy, A., Galiakparov, N. (2017). To what extent do wild apples in Kazakhstan retain their genetic integrity? Tree Genetics and Genomes. Индекс цитирования – 18, DOI -10.1007/s11295-017-1134-z
  5. Gritsenko, D., Pozharsky, A, Deryabina, N., Kassenova, A, Galiakparov N. Genetic analysis of hemagglutinin proteins of H3 and H1 subtypes in Kazakhstan // Genetika, 2019. Индекс цитирования – 0, Процентиль – 32, Квартиль- Q3 DOI: 10.2298/GENSR1902511G.
  6. Gritsenko D., Aubakirova K., Galiakrapov N. Simultaneous detection of five apple viruses by RT-PCR. International Journal of Biology and Chemistry (2020) v. 13, n. 1, p. 129-134. 2020. Индекс цитирования –0, doi: 10.26577/ijbch.2020.v13.i1.13.
  7. A.S. Pozharskiy, K. Aubakirova, D. Gritsenko, N. Galiakparov. Genotyping and morphometric analysis of Kazakhstani grapevine cultivars versus Asian and European cultivars // Genet. Mol. Res., 2020. Индекс цитирования – 0, DOI: 10.4238/gmr18482.
  8. Gritsenko, P., Gritsenko, I., Seidakhmet, A., & Kwolek, B. (2018, September). Plane object-based high-level map representation for slam. In International Conference on Computer Vision and Graphics (pp. 91-102). Springer, Cham. Индекс цитирования – 3, DOI: 10.1007/978-3-030-00692-1_9.
  9. Gritsenko, I., Seidakhmet, A., Abduraimov, A., Gritsenko, P., & Bekbaganbetov, A. (2017, August). Delta robot forward kinematics method with one root. In 2017 International Conference on Robotics and Automation Sciences (ICRAS) (pp. 39-42). IEEE. Индекс цитирования – 3, DOI: 10.1109/ICRAS.2017.8071913.
  10. Gritsenko, P. S., Gritsenko, I. S., Seidakhmet, A. Z., & Abduraimov, A. E. (2017, September). Generation of RGB-D data for SLAM using robotic framework V-REP. In AIP Conference Proceedings (Vol. 1880, No. 1, p. 060005). AIP Publishing LLC. Индекс цитирования – 0, DOI: 10.1109/ICRAS.2017.8071913.
  11. Zhigailov, A. V., Stanbekova, G. E., Nizkorodova, A. S., Galiakparov, N. N., Gritsenko, D. A., Polimbetova, N. S., … & Iskakov, B. K. (2022). Phosphorylation of the alpha-subunit of plant eukaryotic initiation factor 2 prevents its association with polysomes but does not considerably suppress protein synthesis. Plant Science, 111190. Индекс цитирования – 1, Процентиль – 92, Квартиль- Q1 PubMed: 26964019.
  12. Gritsenko, D., Zulfiya Kachiyeva, Gulzhan Zhamanbayev, Bakhytzhan DuisembekoV, Abai Sagitov. Detection of five potato viruses in Kazakhstan // IX International scientific agriculture symposium “AGROSYM 2018”., p. 611

Patents:

  1. Patent for invention No. 27409 (2014) A method for increasing the survival rate of explants of the Aport apple tree when introduced into tissue culture, Innovative patent No. 27409, Application No. 2013/0027.1
  2. Patent for invention No. 27410 (2014) A method for increasing the activity of regeneration and reproduction of the Aport apple tree in vitro.
  3. Patent for invention No. 33633 (2019) «A set of synthetic oligonucleotides for the diagnosis of fire blight on fruit crops by the LAMP method»
  4. Patent for invention No. 33634 (2019) «A set of synthetic oligonucleotides for the detection of apple viruses by RT-PCR»

Results for 2022:

  1. During the expeditions, multispectral aerial photography of wild apple populations was conducted during the flowering and fruit ripening periods in 2022. The diagnosis of collected wild apple samples for the presence of the five most dangerous apple viruses, Phytophthora plurivora, and Erwinia amylovora was performed. The infection status of the tested apple samples has been identified, and analysis of the infection status of populations was conducted. A botanical assessment of each tree in the population and an analysis of the population’s age were conducted.

Maps of two wild apple populations in the Jungar and Zailiysky Alatau territories were created in ArcGis-10.5 software, with a population size of 50-100 trees. Plant material was collected from each tree, and soil samples were analyzed.

Publications (2022): none