Related Experiment Video
Updated: Jun 23, 2025
08:47
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
Published on: February 9, 2024
1.4K
A method for durian precise fertilization based on improved radial basis neural network algorithm
Ruipeng Tang1, Sun Wei1, Tang Jianxun2
1Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.
Frontiers in Plant Science
|June 21, 2024
Summary
This study introduces an Improved Radial Basis Neural Network Algorithm (IM-RBNNA) for precision durian fertilization. The IM-RBNNA accurately predicts soil nutrient content and yield, optimizing fertilizer plans for increased harvests and reduced costs.
Area of Science:
- Agricultural Science
- Artificial Intelligence
- Soil Science
Background:
- Durian cultivation requires precise soil nutrient management for optimal yield.
- Understanding the relationship between soil nutrients (N, P, K) and durian yield is crucial for effective fertilization strategies.
Purpose of the Study:
- To develop and evaluate an Improved Radial Basis Neural Network Algorithm (IM-RBNNA) for precision durian fertilization.
- To enhance the prediction accuracy of soil nutrient content and its correlation with durian yield.
Main Methods:
- Proposed an Improved Radial Basis Neural Network Algorithm (IM-RBNNA) incorporating the gray wolf algorithm for optimizing weights and thresholds.
- Collected soil nutrient and historical yield data to train and validate the IM-RBNNA model.
- Compared the performance of IM-RBNNA against other relevant algorithms.
Main Results:
- IM-RBNNA demonstrated superior performance over three other algorithms in predicting soil N, K, and P content, evidenced by lower average relative error and average absolute error, and a higher coefficient of determination.
- The algorithm accurately predicted the complex relationship between soil nutrients and durian yield.
Conclusions:
- The IM-RBNNA algorithm provides accurate predictions for durian soil nutrient content and yield, aiding farmers in developing effective agronomic plans.
- Efficient nutrient resource utilization through IM-RBNNA minimizes environmental impact, maximizes durian growth potential, reduces costs, and increases overall yield.
