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Keyword: correlation coefficient

  • MECHANIZATION IN AGRICULTURE

    Statistical Analysis of Zeolite Concentration Effects on Germination and Growth of Cucumber Seedlings

    • Asya Asenova-Robinzonova
    • Lilyana Koleva
    • Elena Koleva
    Mechanization in agriculture & Conserving of the resources, Vol. 69 (2025), Issue 3, pg(s) 92-94
    • Abstract
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    Zeolite is widely applied in agriculture due to its high cation-exchange capacity, ability to improve soil fertility, and effectiveness as a slow-release carrier of nutrients. Inaddition, its porous structure allows it to retain and purify water, thereby enhancing soilmoisture balance and reducing nutrient leaching. The present study examines the influence of varying Zeolite concentrations in soil on the germination and subsequent growth dynamics of Cucumber (Cucumis sativus L.) seedlings. Experimental data were subjected to Correlation Analysis, Analysis of Variance (ANOVA), and Statistical Hypothesis testing in order to evaluate the relationship between Zeolite content and plant growth rate. The findings indicate statistically significant effects of Zeolite percentage on both germination and vegetative development, highlighting the potential of Zeolite as a soil amendment for improving Cucumber cultivation practices.

  • TECHNOLOGIES

    Determining natural gas consumption for slabs heating in a Pusher Furnace ahead of plate steel rolling

    • Ratko Ilievski
    • Aleksandar Nikoloski
    • Bobi Krstevski
    • Zoran Apostolovski
    • Alekso Janusevski
    Machines. Technologies. Materials., Vol. 19 (2025), Issue 8, pg(s) 289-292
    • Abstract
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    Natural gas serves as the primary energy source for heating slabs in the Pusher Furnace prior to their rolling into steel plates. The required quantity of natural gas for a 24-hour operational period must be estimated in advance. This study employs multifactor regression analysis to develop a straightforward yet effective predictive equation for natural gas consumption, incorporating key variables such as projected production, the number of slabs to be heated, effective operating time, and the average dimensions of the slabs over a 24-hour workday. Extensive data collected over an extended period formed the matrix for determining the regression coefficients. The resulting model demonstrates a high correlation coefficient (R² = 0.99), underscoring the accuracy of the regression equation. This indicates that the model reliably predicts natural gas consumption with minimal deviation from actual usage during a 24-hour workday.

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