This study aimed to define an optimal sowing date of winter wheat in the steppe zone of South Ural and West Siberia. The effects of climatic factors were determined by analyzing modern climatic resources and experimentally testing in the conditions of the central zone in Orenburgskaya oblast. Research from the All-Russian Scientific- Research Institute of Hydro-meteorological Information – World Data Center (RSRIHI-WDC) served as a source of archival meteorological data for 2009-2019. Experimental data were collected through field work on the south chernozem in the Central zone of Orenburgskaya oblast for 2019-2020. Digital material was processed using statistical analysis. It was confirmed that in the Central zone of Orenburgskaya oblast under modern climatic conditions, the period between 25-30 August is the most acceptable date to sow winter wheat. If sowing occurs at later dates, there is a risk of not obtaining the required amount of effective temperatures, which can result in disunited sparse shoots, bushes that are not fully formed, and low phytometric parameters, and therefore a low realization of climatically secured productivity. These results could be more widely tested in other steppe regions of Ural and West Siberia with a prospect to introduce the results into zonal recommendations for production. Keywords: climatic resources, productivity reserves, winter wheat
Aim. Verification of scientific concepts regarding the spatial heterogeneity of field agrocenoses. Identification of the variability of phytometric and structural crop ndicators and determination of the degree of their influence on the yield and quality of winter wheat grain in the steppe zone of the Orenburg Urals.Material and Methods. Establishment of field experiments, related observations and counts in accordance with the methodology of state variety crops testing and B.A.Dospekhov's guidelin. Monitoring of winter wheat crops was carried by measuring the vegetation index (NDVI) with a Green Seeker Handheld Crop Sensor, Model HCS‐100 (Trimble, USA). Determination of grain quality indicators was conducted according to GOST 9353‐2016 Wheat – Technical Conditions. Microsoft Office Excel was employed for the correlation and regression analysis of experimental data. Results. Analysis of the intra‐field heterogeneity of winter wheat agrocenoses in terms of yield and grain quality was conducted. The dependences of yield and grain quality on the principal crop phytometric and structural parameters were defined and expressed in the form of regression equations.Сonclusion. The results of the studies attest to the growth of reserves of grain yield to 3.0 t/ha and grain quality to class I‐II class in zonal climatic conditions of optimization of environmental factors to the level of the best basic plots by levelling out field soil heterogeneity. This is possible by restoring the fertility of anthropogenically‐degraded soil through the introduction of landscape‐adaptive and resource saving farming systems, soil protective and soil restorative crop rotation, differentiated application of organic and mineral fertilizers and selection of the most adaptive varieties. We also advise the introduction of intelligent ‘digital technologies’ aimed at fuller implementation of the genetic potential of cultivated varieties with careful consideration of natural resources and the preservation of biological diversity.
Состояние окружающей среды в Российской Федерации и в степных регионах, в частности, характеризуется высоким уровнем антропогенной нагрузки. В результате хозяйственной деятельности человека природные экосистемы степей России долгое время подвержены антропогенному воздействию. В статье предложена методика оценки уровня антропогенной нагрузки на основе сопряжённого анализа показателей и индексов шести групп факторов (блоков) антропогенной нагрузки по 17 степным регионам России. По каждому из блоков рассчитаны многомерные средние индексы, сумма которых представляет собой интегральный индекс, отражающий уровень антропогенной нагрузки в субъектах исследуемой территории. Построена картосхема, отображающая пространственное распределение групп факторов и интенсивность антропогенного прессинга на природную среду. В результате выявлено, что на исследуемой территории значение интегрального индекса растёт в юго-восточном направлении и наибольшая антропогенная нагрузка отмечается в Краснодарском крае -4.6 и Белгородской области -4.2. Отмечена высокая сила связи между показателями валового регионального продукта и общими уровнями антропогенной нагрузки степных регионов России, которая характеризуется коэффициентом корреляции -0.95.Ключевые слова: степные регионы России, антропогенная нагрузка, интегральный индекс, коэффициент корреляции, селитебная нагрузка, загрязнение атмосферного воздуха, нагрузка на водный бассейн, сельскохозяйственная нагрузка, транспортная нагрузка, образование отходов производства и потребления ВведениеОценка степени прямого и косвенного воздействия человека и его хозяйственной деятельности на природу составляет одну из актуальных задач в решении проблемы устойчивого развития степных регионов России. В настоящем исследовании в качестве степных мы рассматриваем 17 субъектов РФ, доля биома степей в которых значительна [1].Природные экосистемы обширной территории от Республики Крым до Алтайского края, протянувшейся почти на 4 тыс. км с запада на восток, постоянно подвержены влиянию антропогенных факторов. Зачастую, оценивая антропогенную нагрузку, исследователи ограничиваются показателями, характеризующими «очаговый» тип воздействия -урбанизированность (плотность городского населения) и степень техногенного загрязнения (плотность вредных атмосферных А.А. ЧИБИЛЁВ (мл.) и др.
Modern climatic resources of model regions (Orenburg oblast and Altai Krai) were identified and their agricultural assessment was made to explain scientifically development and implementation of approaches of rational environmental management to agricultural use of farming lands in the post-virgin land regions of Ural and West Siberia. Open access special data on climatic research have served as a source of meteorological information. Commonly accepted methods of the statistical analysis were used to process digital content. It was ascertained that under a total aridity within the studied regions their modern climatic resources had a line of special features. Altai Krai is characterized by more favorable conditions for spring crops vegetation due to predominant precipitation during the summer months and less favorable conditions for winter crops, especially against the background of cooling during the winter months. In Orenburg oblast, increasing aridity of the summer months may prevent complete actualization of productive potential of spring crops and formation of full-grown shoots of winter crops. Introduction of nature-similar technologies in landscape-adaptive systems of agriculture was considered as the principal way to use effectively climatic resources.
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