Abstract
This article compares the production and growth times of three types of lettuce and in three cultivation systems NFT-I, RF and soil with Worm Humus. Additionally, it describes the NFT-I cultivation system, which is a cultivation technique supported by the Internet of Things (IoT). NFT-I allows to measure and store the data of three parameters: ambient temperature, pH level and electrical conductivity; the advantage is that this system allows notifying the farmer about the current status of each variable and notifying through the social network Telegram (through bots). The methodology used was to start the planting process in the three systems on the same day, then the NFT-I system was saving data read by the sensors, and later measurements were made of the time and growth of each of the planted lettuces. The results show that this system can reduce electricity consumption by 91.6%; on the other hand, it helps farmers monitor plant growth. On the other hand, regarding the harvest time, it can be verified that the RF system, NFT-I and land were harvested in 61, 69 and 105 days respectively, which shows that RF is the most efficient; In terms of size, the number of leaves, length and width, RF is also of better size than the NFT-I crop and soil. Finally, in these times of confinement due to the coronavirus disease (COVID-19), in which the economy has slowed and the needs are multiple, this NFT-I system could help people create their vegetable growing system of quickly and cheaply.
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Acknowledgments
Thanks to the Micaela Bastidas National University of Apurímac for supporting the financing for the execution of this project, which was the winner of the III contest of basic and applied research projects for teachers with the funding of mining canon.
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Ibarra, M.J., Alcarraz, E.W., Tapia, O., Kari, A., Ponce, Y., Pozo, R.S. (2022). IoT Computing for Monitoring NFT-I Cultivation Technique in Vegetable Production. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-82196-8_47
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