Abstract

Smart irrigation system is a Precision Agriculture (PA) based device that can automate the irrigation process by analysing soil moisture. The sensor used is a soil moisture sensor that acts as the brain to the system, which will control the whole irrigation system. This research was conducted in the irrigation workshop at UITM Malacca, Jasin Campus, with four treatments and four replications in each treatment. The treatments were T1: manual irrigation (regular planting), T2:40% of soil moisture content, T3:45% of soil moisture content, and T4:50% of soil moisture content. The experimental design used in this study was completely randomized (crd). The parameters involved in this study were plant height, number of leaves, root length, fresh weight, and dry weight of Brassica Chinensis. The data were analyzed using SPSS statistical version 26, and the data analysis involved was average means, analysis of variance (ANOVA), and post hoc test (Bonferroni test). The result shows a significant difference between treatments for plant height, number of leaves, fresh weight, and dry weight parameter since the significance value is less than (0.05), p-value >α, 0.05. While no significant difference between treatments for root length. For all parameter measures of Brassica Chinensis, which was height, the number of leaves, length root, fresh weight, and dry weight shows that T4 had the highest mean, while T2 had the lowest mean. In conclusion, T4 (50% of soil moisture content) was the best percentage to grow a healthy plant.

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