Application of pH and TDS Sensors to Optimize the Growth of Green Lettuce (Lactuca sativa L.) in a Hydroponic System

Abstract

Green lettuce (Lactuca sativa L.) is one of the leafy vegetables that is widely cultivated because it has a relatively short harvest time and high nutritional value, especially as a source of fiber, vitamin A, and vitamin K. This study aims to improve the growth of green lettuce using a DFT (Deep Flow Tecnique) hydroponic system equipped with IoT-based pH and TDS sensors. This study used a completely randomized design (CRD) with two treatments, namely P1 (50% AB Mix + 50% POC) using pH and TDS sensors and P2 (50% AB Mix + 50% POC) without pH and TDS sensors, each with two replications and nine samples per replication. The results showed that the use of pH and TDS sensors significantly increased plant height (32.44 cm), number of leaves (23.66 strands), leaf area (422.8 cm2), wet weight (236.4 g) and dry weight (23.41 g) compared to the manual method. Data analysis using an unpaired t-test at a 5% significance level showed significant differences in most growth parameters. IoT technology has proven effective in increasing the efficiency and productivity of hydroponic systems by providing real-time nutrients according to plant needs. This research supports the development of IoT technology for sustainable agriculture, while also having a positive impact on production efficiency and resource savings.