000			02967ntm a2200337 i 4500
003			MY-KuUP
005			20260609115914.0
006			t||||fr|||| 000 0
007			ta
008			260609t20242024my a|||fr|||| 000 0 eng d
020			_aTHE0010563 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKKP .S86 2024 r Bc.
100	0		_aSunita Anne A/P Rayappa Pillai, _eauthor.
245	1	0	_aEffects of turbidity and pH in an aquaponic system / _cSunita Anne A/P Rayappa Pillai
264		1	_aKuantan, Pahang : _bUMPSA, _c2024
264		4	_c© 2024
300			_ax, 54 pages : _billustrations ;
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Chemical and Process Engineering Technology
502			_aFinal Year Report (Bachelor of Chemical Engineering Technology) -- Universiti Malaysia Pahang Al-Sultan Abdullah - 2024
504			_aInclude bibliographical reference
520	3		_aAquaponic systems, combining aquaculture and hydroponics, have emerged as a sustainable method for integrated food production. This study focuses on the automated monitoring of turbidity and pH levels over time in an aquaponic system, investigating the correlation between these variables. The introduction highlights the significance of water quality in aquaponics, emphasizing the need for continuous monitoring to ensure optimal conditions for both fish and plants. The objective of this study is to investigate the impact of turbidity and pH levels on the performance of an aquaponic system. Through a smart and sustainable approach, the research aims to contribute valuable insights to enhance aquaponic practices. The methodology involves the integration of Arduino ESP32-based automation with sensors for turbidity and pH. The system is designed to make real-time adjustments based on the collected data, fostering a dynamic and responsive environment. Results indicate that pH levels remain relatively stable, while turbidity exhibits variations over the observed period. The correlation coefficient between turbidity and pH is determined to be 0.730358, signifying a moderately strong positive correlation. The discussion delves into the implications of this correlation, emphasizing the need for further investigation into the factors influencing water quality dynamics in aquaponics. In conclusion, the study advocates for continuous sensor calibration, expanded automation features, and community engagement to fortify the resilience and sustainability of automated aquaponic systems. Recommendations include integrating additional parameters for a comprehensive understanding, employing data analytics, and fostering a collaborative community for knowledge exchange.
610	2	0	_xDissertations
650		0	_aUniversities and colleges _xDissertations
856			_uhttps://umpir.ump.edu.my/id/eprint/47342
942			_2lcc _cPSM
999			_c104950 _d104956