RESEARCH OF VALUABLE ECONOMIC INDICATORS IN SOME SPECIES OF ESSENTIAL OIL PLANTS FOR BUILDING PRODUCTIVITY MODELS
Abstract
To conduct preliminary studies of valuable economic indicators of the moldavian dragonhead and summer savory in the conditions of the Central Forest- Steppe and compare them with literature data. Results. Moldavian dragonhead (Dracocephalum moldavica L.) and summer savory (Satureja hortensis L.) are promising essential oil crops. Scientists in different regions of Ukraine and abroad have been studying the biological features and economically valuable indicators of these crops. According to literature data, agrotechnical measures affect crop yield, essential oil content and plant productivity. In the conditions of the Central Forest-Steppe, the yield and mass fraction of essential oil in Dracocephalum moldavica and Satureja hortensis depended on both the sowing dates and the level of moisture within one term. Plants that received intensive irrigation had the highest yield but lower essential oil content. The maximum mass fraction of essential oil in plant raw materials in Dracocephalum moldavica was obtained in the variants of natural moisture in the first and second sowing dates (0.15 and 0.14% of freshly harvested raw materials, respectively), and in Satureja hortensis – in the second sowing date in the variant of natural moisture (0.50%). The highest yield of essential oil from one plant in Dracocephalum moldavica and Satureja hortensis was recorded in plants of the second sowing date in the variant of moderate irrigation (0.50 g and 0.78 g, respectively). Conclusion. The yield and mass fraction of essential oil in moldavian dragonhead and summer savory depend on both the sowing dates and the level of moisture within one term. Irrigation has a positive effect on plant yield. The highest yield of essential oil from one plant in both species was recorded in plants of the second sowing date in the moderate irrigation variant. The data obtained in the conditions of the Central Forest-Steppe partially agree with the data obtained in other regions and can be used to build productivity models of the studied crops
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