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РЕАКЦИЯ СОРТОВ ЯЧМЕНЯ НА ИЗМЕНЕНИЯ ПОГОДНЫХ УСЛОВИЙ ПО МНОГОЛЕТНЕЙ
ДИНАМИКЕ УРОЖАЙНОСТИ
Лисицын Е.М.
Федеральный Аграрный Научный Центр Северо-Востока
Киров, Российская Федерация
REACTION OF BARLEY CULTIVARS TO CHANGES OF WEATHER CONDITIONS BASED ON
MULTI-YEAR YIELD DYNAMICS
Lisitsyn E.
Federal Agricultural Research Center of the North-East,
Kirov, Russian Federation
АННОТАЦИЯ
Для прогноза изменений продукционного процесса растений в зависимости от погодных условий в конкретной климатической зоне необходимо количественное описание связи наиболее существенных факторов с урожаем. В предлагаемой работе данные по урожайности ячменя (Hordeum vulgare L.) сортов Абава и Эколог на четырех участках Кировской области, расположенных в разных агроклиматических районах, за 2008-2019 гг. обработаны с помощью метода множественной регрессии. Установлено, что линейная аппроксимация тренда изменения изучаемых параметров не является удовлетворительной и не может быть использована для прогноза. Один и тот же сорт на разных участках одной области может по-разному (по направлению и силе) реагировать на изменение погодных условий. С другой стороны, в одной и той же местности разные сорта одной и той же культуры могут совершенно по-разному реагировать на изменение погодных условий.
ABSTRACT
To predict changes in the production process of plants depending on weather conditions in a particular climatic zone, a quantitative description of the relationship of the most significant factors with crop productivity is necessary. In the proposed article, data on barley (Hordeum vulgare L.) yields of cv. Abava and Ecologist in four different agro-climatic areas of the Kirov region for 2008-2019 processed using the multiple regression method. It was found that the linear approximation of the change trend of the studied parameters is not satisfactory and cannot be used for the forecast. The same variety in different areas of the same region can react differently (in direction and strength) to changes in weather conditions. On the other hand, in the same area, different varieties of the same crop can react in completely different ways to changes in weather conditions.
Ключевые слова: температура воздуха, вегетационный сезон, линейный тренд, множественная регрессия, осадки, продуктивность, сортоиспытытельная станция.
Keywords: air temperature, growing season, linear trends, multiple regression, precipitation, productivity, varietal testing station.
Introduction
One of the major tasks facing agricultural meteorology is prediction of changes in production process of plants depending on weather conditions in a specific climatic zone. The choice of the most essential factors, the quantitative description of their link with productivity will make the analysis of the processes taking place in an agrophytocenosis, successful and practically significant. However there is no now uniform approach to carrying out similar analytical works. So, some authors use data, average for the whole country, or for its certain areas (Pavlova, 2009; Kharlamova, Silantyeva, 2011), generalizing productivity data on separate plant species or even to their specific groups - fodder, grain, or vegetable. Other authors, whose approach seems to us more logical and reasonable, consider change of economic and valuable traits of specific plant varieties for the long period of observations. So, in article (Seferova et al., 2011), changes of values of economic traits of soybean cv. Komsomolka in 36 years of observations in the conditions of Krasnodar Territory at the Kuban
experimental station of VIR are investigated. Group of authors from the All-Russian institute of plant industry (Novikova et al., 2012) made long-term observations of several cultivars of oats and spring wheat in four zones with contrast climatic conditions. At the same time authors, suggesting to use statistical methods of correlation and regression analyses, point to a possibility of distortion of their results in connection with the existing agrotechnical trends. Thus, the aim of our work is to pay attention to influence of the choice of a specific cultivar of agricultural crop to the received results of the regression analysis and conclusions which can be made of them.
Material and methods
Spring barley is one of the main grain crops cultivated in the Kirov region; one of largest Russian breeding center on grain crops is located here (Shchennikova et al., 2011). Data are used on productivity of two barley (Hordeum vulgare L.) cultivars Abava and Ecol-ogist on four State varietal testing stations of the Kirov region (Zuyevka, Slobodskoj, Sovetsk, and Yaransk)
located in different agro-climatic areas for 2008-2019. Trends in dynamics of weather parameters and indicators of barley productivity were calculated with use of the tabular Excel 2010 Microsoft Office calculator, the equations of multiple regression were calculated in the StatSoft Statistica 10 software.
Results and discussion
As an example of the received graphs, data on productivity of the studied barley cultivars on Sovetsk and Yaransk State varietal testing stations are provided on the figure.
In the figure linear trends of productivity and the equation of these trends for each of cultivar are shown also. From this graphs it is possible to make two im-
portant methodical conclusions.
a) Soviet State varietal testing station
b) Yaransk State varietal testing station
Figure. Dynamics ofproductivity of barley cultivars on Sovetsk and Yaransk State varietal testing stations of the
Kirov region for 2008-2019
First, it is visible that linear trends can not match in the direction in different districts of the area: when plants of spring barley in the conditions of the Sovietsk reduce productivity rather sharply, then in the conditions of Yaransk the same two cultivars show gradual increase in productivity. On Slobodskoj State varietal testing station the trend of decrease in productivity of spring barley is also traced, but here on Zuyevka station only cv. Abava shows decrease. In other words, depending on what cultivar and on what State varietal testing station we will take in the analysis, one can see both increase in productivity in connection with climate change, and its decrease, or lack of that influence. This observation will not be coordinated with conclusions (Novikova et al., 2012) that at synchronously observed crops and cultivars the similar reaction to change of weather conditions is shown. Respectively, the data received by us allow to doubt correctness of total consid-
eration of separate crops or groups of crops for assessment of the impact of climate change on plants productivity.
Secondly, the given equations of a linear trend of change of productivity have rather low coefficients of determination - at best they explain about 36% of variation of a final indicator. Let's notice here, as for such indicators as air temperature on months of growing season and the amount of precipitation, linear trends of change during 2008-2019 on all four State varietal testing stations had low coefficients of determination (to 40%). In other words, dynamics of change of air temperature and a rainfall is far from linear approximation.
To find out the nature of link between temperature of a growing season, the amount of precipitations and productivity of plants of spring barley, it is need to use method of multiple regression and to analyze the received equations (tables 1 and 2).
Table 1
Coefficients at members of the equation of multiple regression of productivity on the air temperature and an
Month State varietal testing station
Zuyevka Slobodskoj Sovetsk Yaransk
Air temperature
May 29.792 1.350 9.448 5.552
June 13.444 0.128 1.166 1.562
July -46.310 0.471 5.318 -0.563
August -44.092 -5.167 -38.105 -6.005
September -97.458 0.668 -16.533 -0.197
Precipitation
May -6.601 0.753 1.737 -0.554
June -0.286 0.399 0.259 0.196
July 3.048 0.194 -0.862 0.186
August 2.074 -0.041 -0.003 0.250
September 1.175 0.145 0.273 -0.029
Provided data show that in general air temperature has much greater influence on the result, than precipitation. At the same time both weather parameters sometimes have opposite impact on productivity of different
cultivars. So, on Slobodskoj State varietal testing station the increase of air temperature in June and July is led to increase in productivity of cv. Abava and, on the contrary, reduces productivity of cv. Ecologist.
Table 2.
Coefficients at members of the equation of multiple regression of productivity on the air temperature and an
Month State varietal testing station
Zuyevka Slobodskoj Sovetsk Yaransk
Air temperature
May 25.286 1.253 -3.098 2.392
June 11.381 -3.639 -10.676 3.346
July -36.428 -0.573 -2.432 -2.862
August -36.358 -2.466 4.327 -0.917
September -80.075 5.458 5.267 -1.303
Precipitation
May -5.301 0.576 -1.174 -0.500
June -0.252 0.271 -0.601 0.198
July 2.537 -0.076 0.166 0.098
August 1.619 -0.010 0.270 0.073
September 0.938 0.381 0.076 0.048
Air temperatures for all the time of vegetation on Sovetsk varietal testing station have opposite effect on the studied cultivars. Weather conditions of Zuyevka varietal testing station are closest on the nature of influence on productivity of both cultivars of spring barley, and on Yaransk varietal testing station force of influence of these parameters on plants of each of barley cul-tivars differs considerably.
Conclusion
Thus, the carried-out analysis of influence of weather conditions on productivity of spring barley in 2008-2019 showed that, first, air temperature had stronger impact on plants, than precipitation. Secondly, linear approximation of a trend of change of the studied parameters is not satisfactory and cannot be used for the forecast. Thirdly, the same cultivar on different varietal testing stations can differently (in the direction and force) reacts to change of weather conditions of growing season. Fourthly, in the same area the different cul-tivars of the same crop can react to change of weather conditions absolutely differently.
References
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3. Pavlova V.N. A problem of assessment of the impact of climate changes on productivity of the agrosphere of Russia: methodology, models, calculation results // News of the Samara scientific center of the Russian Academy of Sciences. 2009. T.11, No. 1(7). P. 1543-1548.
4. Seferova I.V., Novikova L.Yu., Nekrasov A.Yu. Varietal soybean reaction assessment Komso-molka on climate changes in Krasnodar Territory // Oil-bearing crops. Scientific and technical bulletin of the All-Russian Research Institute of oil-bearing crops. 2011. No. 1. P. 72-77.
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