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Mathematical Model Of Plant Growth In Different Led Light Conditions Regine D. Pantone et... al...

Contributor(s): Material type: TextPublication details: November 2024Description: 24 pages .,; illustrations, 28cmContent type:
  • text
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  • unmediated
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Online resources: Dissertation note: thesis College of Science University of Rizal System-Morong 2024 Summary: This research investigates the effects of different light conditions on plant growth, focusing on garlic (Allium sativum). By designing an experiment to expose garlic plants to various light spectra, including red, blue, and violet LEDs, as well as natural sunlight, the study aims to gather comprehensive data on growth parameters such as plant height, leaf area, biomass, and concentrations of beneficial compounds like allicin. A predictive mathematical model, using a sixth-degree polynomial (6th poly), utilizes this data to describe the relationship between light conditions and plant growth, incorporating key variables such as light intensity, spectrum, and photoperiod. This research seeks to optimize agricultural practices by providing insights into how different light conditions can enhance plant growth and improve crop yields, thereby contributing to more efficient and sustainable farming methods.
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Theses and dissertations Morong College Library Reference Not for loan URSMOR-CL-7017

thesis College of Science University of Rizal System-Morong 2024

This research investigates the effects of different light conditions on plant growth, focusing on garlic (Allium sativum). By designing an experiment to expose garlic plants to various light spectra, including red, blue, and violet LEDs, as well as natural sunlight, the study aims to gather comprehensive data on growth parameters such as plant height, leaf area, biomass, and concentrations of beneficial compounds like allicin. A predictive mathematical model, using a sixth-degree polynomial (6th poly), utilizes this data to describe the relationship between light conditions and plant growth, incorporating key variables such as light intensity, spectrum, and photoperiod. This research seeks to optimize agricultural practices by providing insights into how different light conditions can enhance plant growth and improve crop yields, thereby contributing to more efficient and sustainable farming methods.

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