Catfish Cultivation Biofloc Pond in Integrated Agricultural System

Description

This dataset offers a comprehensive glimpse into the growth of catfish within biofloc ponds, which are standardized at dimensions of 1.5 meters in both diameter and height. The primary focus of this study lies in meticulously assessing water quality, facilitated by the deployment of sensors designed to measure critical parameters such as water temperature, pH levels, total dissolved solids, electrical conductivity, and turbidity. Moreover, external sensors for temperature and relative humidity are strategically positioned to capture environmental conditions within the biofloc pond accurately. Data collection is conducted at three distinct times during the day—morning, afternoon, and evening—to ensure thorough representation of daily fluctuations. The process of obtaining data on catfish growth entails a systematic approach, involving regular weighing of catfish specimens and manual calculations of both living and deceased individuals on a weekly basis. Covering a duration of 69 days and spanning 11 weeks from June 1, 2023, to August 8, 2023, the dataset encompasses observations from three separate biofloc ponds. The deliberate integration of methodologies for environmental monitoring and growth assessment forms the bedrock of this dataset, offering valuable insights into the dynamic interplay between biofloc pond conditions and catfish growth over a specific timeframe. With its potential for reuse across diverse research domains such as aquaculture, environmental science, and data-driven modeling, this dataset serves as a pivotal resource for researchers delving into the intricate relationship between biofloc pond dynamics and catfish development.

Steps to reproduce

AM2301 sensors were employed for monitoring air temperature and humidity, while DS18B20, DFRobot analog pH, DFRobot analog turbidity sensor, DFRobot analog TDS sensor, and DFRobot analog electrical conductivity sensor were used for water temperature, pH, turbidity, total dissolved solids (TDS), and electrical conductivity measurements. All sensors were integrated into a singular enclosure, each equipped with a dedicated data reception box. The NodeMCU functioned as the controller for data acquisition from the sensors. Readings were recorded three times in a day and subsequently transmitted to distinct channels on the Thingspeak server. The comma-separated value (CSV) file was performed to construct the comprehensive dataset on the Thingspeak server. The enumeration of catfish and determination of individual weights were conducted manually and documented in Microsoft Excel files.

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