Investigation of Morphological Responses of Barassica Rapa Var.parachinensis (Choysum) within an Automated Urban Farming

Choy, Mun Kit (2025) Investigation of Morphological Responses of Barassica Rapa Var.parachinensis (Choysum) within an Automated Urban Farming. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

This research presented in this document investigates the development and application of a hydroponic farming system aimed at optimizing the growth of Brassica rapa var. parachinensis (Choy sum). The study primarily focuses on the influence of different nutrient solution flow rates on the morphological characteristics and nitrate accumulation in the plant. Throughout the experiment, variables such as light intensity and photoperiod are kept constant to ensure that the effects of the flow rates on plant growth are accurately measured. Data was collected over 45 days, where the growth parameters such as leaf width, leaf length, stem width, and root length were recorded every five days. The study also employed machine learning techniques, specifically using Roboflow, to analyze plant growth stages based on images captured at regular intervals. One of the key findings from the study is that a lower flow rate of nutrient solution resulted in reduced nitrate accumulation in the plants, which is significant for ensuring consumer safety, as high nitrate levels in leafy greens can pose health risks. The higher flow rate led to faster growth and more robust plant development, while the slower flow rate produced more compact plants with lower nitrate concentrations. This suggests that nutrient solution flow rate can be optimized based on specific agricultural goals, whether prioritizing growth rate or nutritional safety. Factors such as consistent environmental controls and accurate data collection contributed to the validity of the results. However, other variables like temperature and nutrient concentration could influence plant growth, suggesting that further studies should explore these aspects. Future research is recommended to expand the scope of the study to different crop types and environmental conditions, as well as to enhance the application of machine learning models for better growth predictions. The findings from this research provide valuable insights for improving urban farming techniques, especially in controlled environments like hydroponics, where resource efficiency and sustainable food production are critical. In conclusion, this study contributes original knowledge to the field of urban agriculture, particularly in the application of automated hydroponic systems for growing Choy sum. The results offer practical implications for optimizing water flow rates in hydroponic systems, improving both crop yield and nutritional quality. This research not only advances scientific understanding but also offers practical solutions for urban food production, emphasizing sustainability and health-conscious farming practices.