Using Monte Carlo Simulation to Optimize Vitamin C Production in Brassica oleracea Using Abiotic Plant Stress

Overview

As the world population increases, so does the global demand for food. Simultaneously the quality of Earth’s farmland is declining. To fill this need, the agricultural industry has been revolutionized through vertical farms (VF), where crops are grown indoors without sunlight or soil. However, there’s a downside as experiments have shown that VF crops contain less Vitamin Ccompared to conventionally grown crops. The lack of stress in the typical VF environment inhibits the ascorbate-glutathione cycle in the plants, which is the pathway to Vitamin Cproduction. This study aims to grow Brassica oleracea in stress-controlled environments (in the form of wind, heat and drought) and to use that data to find the ideal combination of stress levels to optimize Vitamin Cproduction using Monte Carlo Simulation. It was hypothesized that the Vitamin Clevels of Brassica oleracea could be increased and raised to a level equal or superior to that conventionally farmed. The secondary hypothesis is that the optimal combination of stress levels can be found using Monte Carlo simulation. After a t-test and regression analysis, the Vitamin Clevels of all groups were proven to be statistically significantly lower (alpha = 0.05) than that of the control group except the group P3G1 (eight hours of daily wind and 32.2o C), which was non-inferior to the control, therefore the null hypothesis is rejected in favor of the alternate. The simulation successfully identified the optimal stress combination of 11 hours of wind stress at 35oC. Further testing is needed.

Competition history

• JSHS 2022 Category not listed

Resources

• National JSHS abstract book ↗

Related projects

Closest projects by meaning, across every fair and year in the corpus.