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Related Concept Videos

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Key Elements for Plant Nutrition

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Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
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Trapezoidal channels are widely used in irrigation systems due to their cost-effectiveness and efficiency in conveying water. Trapezoidal channels feature a flat bottom and sloping sides, making them stable and easier to construct compared to other shapes. The bottom width and side slope ratio are determined based on the required flow capacity and site conditions. The side slope is kept gentle for unlined channels to prevent soil erosion.Hydraulic parameters in channel design include the flow...
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Related Experiment Video

Updated: Jan 18, 2026

A Flexible Low Cost Hydroponic System for Assessing Plant Responses to Small Molecules in Sterile Conditions
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A robust hydroponic system for horticulture farming using deep learning, IoT, and mobile application.

Nadim Nawshad1, Md Asraf Ali1,2, Ku Nurul Fazira3

  • 1Department of Computer Science, American International University - Bangladesh, Dhaka, Bangladesh.

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Summary

This study developed an easy-to-use hydroponic system with automatic guidelines and disease detection for farmers in Bangladesh. The smart farming technology improves crop monitoring and management, boosting agricultural efficiency.

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Area of Science:

  • Agricultural Technology
  • Smart Farming Systems
  • Hydroponics

Background:

  • Limited farmer literacy poses challenges for adopting advanced hydroponic farming techniques in Bangladesh.
  • There is a need for user-friendly systems to assist farmers in monitoring and operating smart hydroponic setups.

Purpose of the Study:

  • To introduce a robust hydroponic system with automatic guidelines, monitoring, and disease detection.
  • To enhance the convenience and reduce stress in the hydroponic cultivation process for farmers.

Main Methods:

  • Hardware implementation utilizing WeMos controllers for system operation.
  • Disease detection integrated using a Deep Learning model.
  • Development of a mobile application for sensor data analysis and automated alerts.

Main Results:

  • The system achieved a high disease detection accuracy of 98.5%.
  • Approximately 80% of surveyed farmers reported the system as beneficial for cultivation, usability, and monitoring.

Conclusions:

  • The proposed system significantly enhances the operational efficiency and sustainability of hydroponic farming.
  • The technology shows potential for improved resource management and effective disease prevention strategies in agriculture.