An analysis of yield dynamics in Peredovik sunflower variety in the conditions of the North Caucasus Region

Authors

  • Liubov Novikova Federal Research Center N.I. Vavilov All-Russian Institute of Plant Genetic Resources, Bol'shaya Morskaya ul., 42–44, Saint Petersburg, 190000, Russian Federation https://orcid.org/0000-0003-4051-3671
  • Vera Gavrilova Federal Research Center N.I. Vavilov All-Russian Institute of Plant Genetic Resources, Bol'shaya Morskaya ul., 42–44, Saint Petersburg, 190000, Russian Federation https://orcid.org/0000-0002-8110-9168

DOI:

https://doi.org/10.21638/spbu03.2023.204

Abstract

The results of observations for 1971–2002 were used to analyze the long-term trends of yield and the duration of the growing season in the sunflower variety Peredovik. The regression analysis has shown that the growing season duration decreases with the increase in the sum of temperatures above 15 °C. The yield of sunflower was negatively associated with the sums of temperatures and the sums of precipitation in May–August, and positively with the precipitation in April. According to the regression analysis in differences, the main factor influencing the yield variability was the hydrothermal coefficient for the period with temperatures above 20 °C, the second factor was spring precipitation. The possible presence of a non-linear trend in yield dynamics that is not related to weather and climate conditions has been revealed. With the sustained tendency of the last 30 years towards an increase in temperatures and a decrease in precipitation in April, the growing season will keep shortening and the yield decreasing.

Keywords:

sunflower, yield, growing season duration

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References

Ayvazyan, S. A., Enyukov, I. S., and Meshalkin, l. D. 1985. Applied statistics: study of dependencies. 487 pp. Finance and statistics. Moscow. (In Russian)

Belolyubtsev, A. I. and Sennikov, V. A. 2012. Bioclimatic potential of ecosystems: Textbook. 160 pp. Russian Agrarian University — Moscow Timiryazev Agricultural Academy Press. Moscow. (In Russian)

Carter, T. R. and Mäkinen, K. 2011. Approaches to climate change impact, adaptation and vulnerability assessment: towards a classification framework to serve decision-making. MEDIATION Technical Report No 2(1). 70 pp. Finnish Environment Institute (SYKE). Helsinki.

Choudhury, A. and Jones, J. 2014. Crop yield prediction using time series models. Journal of Economics and Economic Education Research 15(3):53–67.

Debaeke, P., Casadebaig, P., Flenet, F., and Langlade, N. 2017. Sunflower crop and climate change: vulnerability, adaptation, and mitigation potential from case-studies in Europe. Oilseeds & fats Crops and Lipids 24(1):D102. https://doi.org/10.1051/ocl/2016052

Donatelli, M., Srivastava, A. K., Duveiller, G., Niemeyer, S., and Fumagalli, D. 2015. Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe. Environmental Research Letters 10(7):075005. https://doi.org/10.1088/1748-9326/10/7/075005

Eliseeva, I. I., Kurysheva, S. V., Kosteeva, T. V., Pantina, I. V., Mikhailov, B. A., Neradovskaya, Yu. V., Stroye, G. G., Bartels, K., and Rybkina, L. R. 2006. Econometrics: A Textbook. I. I. Eliseeva (ed.). 576 pp. Finance and statistics. Moscow. (In Russian)

Friedt, W. 1992. Present state and future prospects of biotechnology in sunflower breeding. Field Crop Research (30):425–442. https://doi.org/10.1016/0378-4290(92)90009-X

Garcia-Lopez J., Lorite, I. J., Garcia-Ruiz, R., and Dominguez, J. 2014. Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling. Climatic Change 124(1–2):147–162. https://doi.org/10.1007/s10584-014-1067-6

Gavrilova, V. A. and Anisimova, I. N. 2017. Genealogy of the sunflower lines created on the basis of Russian varieties. Helia 40(67):133–146. https://doi.org/10.1515/helia-2017-0025

Guide to agrometeorological forecasts. 1984. Vol. 2. Technical, vegetable, fruit, subtropical crops, herbs, pasture vegetation, livestock. Yu. S. Melnik, N. V. Gulinova and S. A. Bedarev (eds). 264 pp. Gidrometeoizdat Publ. Leningrad. (In Russian)

Iler, A. M., Inouye, D. W., Schmid, N. M., and Høye, T. T. 2017. Detrending phenological time series improves climate–phenology analyses and reveals evidence of plasticity. Ecology 98(3):647–655. https://doi.org/10.1002/ecy.1690

Kaukoranta, T. and Hakala, K. 2008. Impact of spring warming on sowing times of cereal, potato and sugar beet in Finland. Agricultural and Food Science 17:165–176. https://doi.org/10.2137/145960608785328198

Lobell, D. B. and Field, C. B. 2007. Global scale climate-crop yield relationships and the impacts of recent warming. Environmental Research Letters 2(1):014002. https://doi.org/10.1088/1748-9326/2/1/014002

Menzel, A. and Sparks, T. 2006. Temperature and plant development: phenology and seasonality; pp. 70–96 in J. I. L. Morison, M. D. Morecroft (eds), Plant growth and climate change. Blackwell Publishing Ltd. https://doi.org/10.1002/9780470988695.ch4

Miller, J. F. and Fick, G. N. 1997. The genetics of sunflower; pp. 441–495 in A. A. Schneiter (ed.), Sunflower technology and production. ASA, CSSA, SSSA, Wisconsin. https://doi.org/10.2134/agronmonogr35.c9

Mishchenko, Z. A. 2009. Agro-Climatology. 512 pp. KNT Publ. Kiev. (In Russian)

Moriondo, M. and Bindi, M. 2007. Impact of climate change on the phenology of typical Mediterranean crops. Italian Journal of Agrometeorology 3:5–12.

Novikova, L. Yu., Kiru, S. D., and Rogozina, E. V. 2017. Valuable traits of potato (Solanum L.) varieties as influenced by climate change in European Russia. Agricultural Biology 52(1):75–83. https://doi.org/10.15389/agrobiology.2017.1.75eng

Novikova, L. Yu. and Naumova, L. G. 2019. Structuring ampelographic collections by phenotypic characteristics and comparing the reaction of grape varieties to climate change. Vavilov Journal of Genetics and Breeding 23(6):772–779. https://doi.org/10.18699/VJ19.551

Novikova, L. Yu., Dyubin, V. N., Seferova, I. V., Loskutov, I. G., and Zuev, E. V. 2012. Prediction of vegetation period duration in spring cereal crops varieties in the conditions of climate changes. Agricultural Biology 5:78–87. https://doi.org/10.15389/agrobiology.2012.5.78eng

Olesen, J. E., Trnka, M., Kersebaum, K. C., Skjelvåg, A. O., Seguin, B., Peltonen-Sainio, P., Rossi, F., Kozyra, J., and Micale, F. 2011. Impacts and adaptation of European crop production systems to climate change. European Journal of Agronomy 34(2):96–112. https://doi.org/10.1016/j.eja.2010.11.003

Parent, B. and Tardieu, F. 2012. Temperature responses of developmental processes have not been affected by breeding in different ecological areas for 17 crop species. New Phytologist 194(3):760–774. https://doi.org/10.1111/j.1469-8137.2012.04086.x

Pustovoit, V. S. 1975. Main directions of breeding; pp. 153–163 in Sunflower. Kolos Publ. Moscow. (In Russian)

Results of the state variety testing of sunflower. 1972. 136 pp. Kolos Publ. Moscow. (In Russian)

Richardson, A. D., Anderson, R. S., Arain, M. A., Barr, A. G., Bohrer, G., Chen, G., Chen, J. M., Ciais, P., David, K. J., Desai, A. R., Dietze, M. C., Dragoni, D., Garrity, S. R., Gough, C. M., Grant, R., Hollinger, D., Margolis, H. A., McCaughey, H., Migliavacca, M., Monson, R. K., Munger, J. W., Poulter, B., Raczka, B. M., Ricciuto, D. M., Sahoo, A. K., Schaefer, K., Tian, H., Vargas, R., Verbeeck, H., Xiao, J., and Xue, Y. 2012. Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis. Global Change Biology 18(2):566–584. https://doi.org/10.1111/j.1365-2486.2011.02562.x

Seiler, G. J. and Gulya, T. J. 2016. Sunflower: Overview. In Reference Module in Food Science. USDA ARS. USA. https://doi.org/10.1016/B978-0-08-100596-5.00027-5

Sirotenko, O. D. 2012. Basics of agricultural meteorology. Vol. 2. Methods of calculations and forecasts in agrometeorology, Book 1. Mathematics models in agrometeorology. 136 pp. All-Russian Scientific Research Institute of Hydrometeorological Information — World Data Center. Obninsk. (In Russian)

Sirotenko, O. D., Pavlova, V. N., and Abashina, E. V. 2007. Modeling of the influence of observed and predicted climate changes on the productivity and sustainability of agriculture in Russia and the near abroad. Problems of agrometeorology in the context of global climate change. The works of FSBE ARRIAM 36:45–62. (In Russian)

Sunflower varieties (State variety testing results for 1958–1961). 1962. 118 pp. Izd-vo sel'skokhoziaistvennoi literatury, zhurnalov i plakatov Publ. Moscow. (In Russian)

Vukolov, E. A. 2004. Fundamentals of statistical analysis. Workshop on statistical methods and operations research using STATISTICA and EXCEL packages. 464 pp. Forum Publ. Moscow. (In Russian)

Wenjiao, S., Fulu, T., and Zhao, Z. 2013. A review on statistical models for identifying climate contributions to crop yields. Journal of Geographical Sciences 23(3):567–576. https://doi.org/10.1007/s11442-013-1029-3

Yue, X., Unger, N., Keenan, T. F., Zhang, X., and Vogel, C. S. 2015. Probing the past 30-year phenology trend of US deciduous forests. Biogeosciences 12(15):4693–4709. https://doi.org/10.5194/bg-12-4693-2015

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Published

2023-06-27

How to Cite

Novikova, L., & Gavrilova, V. (2023). An analysis of yield dynamics in Peredovik sunflower variety in the conditions of the North Caucasus Region. Biological Communications, 68(2), 97–104. https://doi.org/10.21638/spbu03.2023.204

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