Models of sunflower productivity formation and their efficiency in the conditions of the north-eastern Forest-Steppe of Ukraine
Abstract
Sunflower crops for the production of marketable products are in all regions of Ukraine, in particular in the zone of the northern Forest-Steppe and Polissya. This zone differs significantly by soil conditions from the regions of traditional crop distribution. This condition requires theoretical generalization and experimental research to develop a model of sunflower varieties with a high level of adaptability to new growing conditions
In general, the assessment of the level of adaptability of genotypes to the conditions of the zone using basic cultivation technologies is provided by demonstration landfills. The most complete range of domestic and foreign sunflower hybrids focused on the area of North-Eastern Forest-Steppe and Polissya is presented at the demonstration site of the Institute of Agriculture of the Northeast NAAS. The research was conducted within the program to develop the model of the variety for the conditions of the North-Eastern Forest-Steppe and Polissya of Ukraine, (state registration number - 0116U001506). The study was performed in 2016‒2020 at the Institute of Agriculture of the Northeast NAAS of Ukraine and Sumy National Agrarian University. Hybrids (28‒56) of different originators were tested annually.
The general dynamics of sown areas, yield and gross production of sunflower in Sumy region in 2016‒2020 is analyzed. It was established that higher crop yields compared to the average in the country, led to the increase in the annual growth in areas under sunflower from 2‒5 % in 2010 to 11‒16 % in 2019 and 2020.
Currently, the share of sunflower crop in the structure of arable land in the region is 25.4% compared to the average of 19.7% in Ukraine Maintaining such dynamics in the near future may be the main limiting factor for productivity growth. If such dynamics will be maintained in the near future, it may become the main limiting factor for productivity growth.
According to the results of the analysis of weather conditions in 2016 2020, indicators of vegetative and generative development of plants of different genotypes at the demonstration site, the 2-level algorithm for realizing the generative potential of hybrids was proposed. It was determined by the length of their growing season and their place in the groups with different models of yield formation It was found that in years close to the average long-term difference in one day of the growing season was proportional to the yield ‒ 34 kg, in drier and hotter years the value increases to 50 kg/ha.
The ability of hybrids to provide the estimated average yield (for 3 years or more) was defined as the basic level of their adaptability to the conditions of the zone. The minimum values of indicators with a high level of correlation with the parameters of plant productivity are determined. According to the results of the analysis of values of indicators, their stability in different weather conditions the difference in algorithms of formation of productivity is established. The parameters of groups of hybrids of the model of productivity formation which provided higher than the basic level of adaptability to the conditions of the zone were analyzed.
It was established that the model with a satisfactory level of adaptability is realized due to a slight excess of the values of the basic indicators of the parameters that determine the development of the leaf apparatus of plants and the structure of their productivity. Models with a higher level of adaptability are characterized by a significant excess of baseline values for several or most indicators.
References
2. Cecconi, F., & Baldini, M. (1999). Genetic analysis of some physiological characters in relation to plant development of a sunflower - Helianthus annuus L. diall cross. Helia, 14, 93‒100.
3. Derzhavnij reєstr sortіv roslin, pridatnih dlja poshirennja v Ukraїnі na 2010 rіk [State register of plant varieties suitable for distribution in Ukraine for 2020]. [Electronic resource]. Access mode: https://minagro.gov.ua/storage/app/uploads/public/ 5d6/4fa/731/5d64fa731fd02026374899. pdf (data zvernennja 04.10.2020) (in Ukrainian).
4. Zelenskij, M. I., & Agaev, M. G. (2007). Nekotrye tendencii jevoljucionnoj izmenchivosti fotosinteza kul'turnyh rastenij [Some trends in the evolutionary variability of photosynthesis of cultivated plants]. Trudy po prikladnoj botanike, genetike i selekcii, 164, 361–377 (in Russian).
5. Nichiporovich, A. A. (1996). Fotosintez i voprosy povyshenija urozhajnosti rastenij [Photosynthesis and issues of in-creasing plant productivity]. Vestnik selskohozjajstvennoj nauki, 19(2), 1−12 (in Russian).
6. Musіyenko, M. M., Parshikova, T. V., & Slavnij, P. S. (2001). Spektrometrichnі metodi v prakticі fіzіologіі, bіohіmіі ta ekologіі roslin [Spectrometric methods in the practice of plant physiology, biochemistry and ecology]. Fіtocentr, Kyiv (in Ukraini-an).
7. Carenko, O. M., Zlobіn, Ju.A., Skljar, V. G., & Panchenko, S. M. (2000). Kompjuternі metodi v sіlskomu gospodarstvі ta bіologіi [Computer Methods in Agriculture and Biology]. Unіversitetska kniga, Sumi (in Ukrainian).
8. Rostova, N. S. (2002). Korreljacii: struktura i izmenchivost [Correlations: structure and variability]. Izdatelstvovo S-Peterb. Un-ta, SPb (in Russian).
9. Lakin, G. F. (1980). Biometrija [Biometrics]. Vysshaja shkola, Moscov (in Russian).
10. Departament agropromyslovogo rozvytku Sums'koi' Oblderzhadministacii' [Department of agro-industrial develop-ment of Sumy administration]. [Electronic resource]. Access mode: http://www.apk.sm.gov.ua / index.php/uk/ 2013-04-18-21-50-12. pdf. (data zvernennja 10.11.2020) (in Ukrainian).
11. Trocenko, V. І., & Zhatova, G. O. (2015). Etapi formuvannja produktivnostі roslin ta urozhajnіst posіvіv sonjashniku [Stages of formation of plant productivity and yield of sunflower crops]. Vіsnik centru naukovogo zabezpechennja APV Harkіvskoї oblastі, 18, 165–173 (in Ukrainian).
12. Trocenko, V. І., & Zhatova, G. O. (2018). Parametri fotosintetichnogo aparatu sonjashniku v modeljah sortіv dlja zoni pіvnіchno-shіdnogo Lіsostepu ta Polіssja [Parameters of photosynthetic sunflower apparatus in varieties models for the area of the northeast Forest-Steppe and Polissia]. Vіsnik Sumskogo NAU, 8(35), 53‒58 (in Ukrainian).
13. Zhemchuzhin, V. Ju. (2009). Formuvannja urozhaju sonjashniku rіznih naprjamіv vikoristannja zalezhno vіd umov mіneralnogo zhivlennja [Formation of sunflower crop of different directions of use depending on the conditions of mineral nutri-tion]. Vіsnik Lvіvskogo NAU: Agronomіja, 13, 367‒371 (in Ukrainian).
14. Melnik, A. V. (2004). Porіvnjalnij analіz koreljacіj morfologіchnih oznak ta produktivnostі sonjashniku [Comparative analysis of correlations of morphological features and sunflower productivity]. Vіsnik Sumskogo NAU, 1(8), 82‒84 (in Ukraini-an).
15. Kirichenko, V. V. (2005). Selekcija i semenovodstvo podsolnechnika (Helianthus annuus L.) [Selection and seed production of sunflower (Helianthus annuus L.)]. Magda, Harkіv (in Russian).
16. Zhuchenko, A. A. (1990). Adaptivnoe rastenievodstvo (jekologo-geneticheskie osnovy) [Adaptive crop production (ecological and genetic basis)]. Shtiinca, Kishinev (in Russian).
17. Yegorov, B., Turpurova, T., Sharabaeva, E., & Bondar, Y. (2019). Prospects of using by-products of sunflower oil production in compound feed industry. Journal of Food Science Technology Ukraine, 13, 106–113. doi: 10.15673/fst.v13i1.1337
18. Bartholomew Saanu Adeleke & Olubukola Oluranti Babalola (2020). Oilseed crop sunflower (Helianthus annuus) as a source of food: nutritional and health benefits Food Sci Nutr. Sep., 8(9), 4666–4684. Published online 2020 Jul 31. doi: 10.1002/fsn3.1783
19. Canavar, Öner, Ellmer, F. & Chmielewski, F.M. (2010). Investigation of yield and yield components of sunflower (Helianthus annuus L.) cultivars in the ecological conditions of Berlin (Germany). Helia, 33, 117‒129. doi: 10.2298/HEL1053117C
20. Hassan, F., Cheema, M.A., Qadir, G. & Azim, C.M. (2005). Influence of seasonal variations on yield and yield com-ponents of sunflower. Helia, 28(43), 145‒152. doi: 10.2298/HEL0543145F
21. Angadi, S. V. & Entz, M. H. (2002). Agronomic performance of different stature sunflower cultivars under different levels of interplant competition. Can. J. Plant Sci. 82, 43‒52.
22. Abdelsatar, Mohamed & Fahmy, R. & Hassan, T. (2015). Genetic control of sunflower seed yield and its compo-nents under different edaphic and climate conditions. Egyptian Journal of Plant Breeding, 19, 103‒123.
23. Marinkovic, R., Jockovic, M., Jeromela, A., Jocić, S., Ciric, M., Balalic, I. & Sakac, Z. (2011). Genotype by environ-ment interactions for seed yield and oil content in sunflower (H. annuus L.) using AMMI model. Helia, 34, 79‒88. doi:10.2298/HEL1154079M.
24. Demurin, Y., & Borisenko, O. (2011). Genetic collection of oleic acid content in sunflower seed oil. Helia, 34, 69–74. doi: 10.2298/hel1155069d
25. Goryunova, S. V., Goryunov, D. V., Chernova, A., Martynova, E., Dmitriev, A. E., Boldyrev, S., Ayupova, A., Mazin, P. V., Gurchenko, E., Pavlova, A. S., Petrova, D. A., Chebanova, Y. V., Gorlova, L. A., Garkusha, S. V., Mukhina, Z. M., Saven-ko, E. G. & Demurin, Ya. N. (2019). Genetic and Phenotypic Diversity of the Sunflower Collection of the Pustovoit All-Russia Research Institute of Oil Crops (VNIIMK). Helia, 42. doi: 10.1515/helia-2018-0021
26. Kaya, Y. (2020). Sunflower Production in Blacksea Region: The Situation & Problems. International Journal of Inno-vative Approaches in Agricultural Research, 4(1), 147‒155. doi: 10.29329/ijiaar.2020.238.15
27. Balalić, I., Branković, G., Miklič, V., Jocić S. & Šurlan-Momirović, G. (2013). Sunflower mega-environments in Serbia revealed by GGE Biplot Analysis. Ratar Povrt., 50(2), 1‒10. doi: 10.5937/ratpov50-4041
28. Ahmed, S.B.M & Abdella, A.W.H. (2009). Genetic yield stability in some sunflower (Helianthus annuus L.) hybrids under different environmental conditions of Sudan. Journal of Plant Breeding and Crop Science, 1, 016‒021. doi: 10.5897/JPBCS.9000070
29. Aksyonov, I. (2007). Effect of cultivation measures on index of photosynthesis and yield of sunflower. Helia, 30(47), 79‒80. doi: 10.2298/HEL0747079A
30. Li, S.-T., Duan, Y., Guo, T.-W., Zhang, P.-L., He, P., & Majumdar, K. (2018). Sunflower response to potassium ferti-lization and nutrient requirement estimation. Journal of Integrative Agriculture, 17(12), 2802–2812. doi: 10.1016/S2095-3119(18)62074-X