Issue |
BIO Web Conf.
Volume 143, 2024
The 5th International Conference on Bioenergy and Environmentally Sustainable Agriculture Technology (ICoN-BEAT 2024)
|
|
---|---|---|
Article Number | 01018 | |
Number of page(s) | 7 | |
Section | Agriculture and Forestry | |
DOI | https://doi.org/10.1051/bioconf/202414301018 | |
Published online | 25 November 2024 |
Optimization of nutrient formulation and medium flow using automatic nutrient film technique hydroponics system on mizuna (Brassica rapa Nipponisica) cultivation
1 Agrotechnology Department, Faculty of Agriculture and Animal Science, University of Muhammadiyah Malang, 65144 East Java, Indonesia
2 Alumni of Soil Science Study Program, Graduate School, IPB University, Indonesia
* Corresponding author: aniekiriany@umm.ac.id
Mizuna, or Japanese mustard greens, is a highly popular plant in Indonesia, with wide market availability and high economic price, among other green vegetables. Mizuna cultivation using an automatic nutrient film technique (NFT) hydroponic system will produce better quality and quantity and efficient use of fertilizers and electricity. This study aimed to find the best concentration of nutrients to support the growth of mizuna and determine the flow time of hydroponic media suitable for mizuna cultivation. The study was designed using RCBD with two treatment factors, namely nutrient formulation (four nutrient formulations and water as control) and medium flow time (three levels of switch-off time i.e 15, 45, and 60 min). Growth observation data were analyzed using variance (ANOVA), then the multiple comparison test was continued with the Duncan multiple range test (DMRT) at α level 5%. Different nutrient sources in this study did not significantly affect the growth variables of mizuna, but mizuna grown in a nutrient medium did significantly show better growth than control. This study found that all of the flow time treatments (15, 45, and 60 minutes off) also gave statistically similar results on the growth of mizuna in the NFT hydroponic system.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.