In the quest to optimize rice cultivation, a team of researchers led by Lantian Xie from the School of Information Engineering at Huzhou University in China has developed a novel system that promises to revolutionize fertilization practices. Published in *Frontiers in Plant Science*, their study introduces a rice side-deep variable-rate fertilization control system based on real-time soil electrical conductivity (EC) detection. This innovation addresses a longstanding challenge in agriculture: the inefficiency of current fertilization devices that rely on static, experience-based settings.
The system is designed to dynamically adjust fertilizer application rates according to soil fertility, a significant leap forward in precision agriculture. “Current methods often lead to over-fertilization or under-fertilization, resulting in low fertilizer use efficiency,” explains Xie. “Our system aims to bridge this gap by providing real-time, accurate data to guide fertilization.”
The research involved a three-factor, four-level full factorial experiment to investigate the effects of soil moisture content, electrode insertion depth, and soil temperature on soil EC. Using this data, the team established an EC calibration model based on a radial basis function (RBF) neural network. This model forms the backbone of the fertilization strategy, which constructs a fertilizer application model based on real-time EC, target yield, and implement forward speed.
One of the standout features of the system is its use of an incremental proportional-integral-derivative (PID) algorithm to achieve closed-loop control of variable-rate fertilization. This ensures that the motor speed, which controls the fertilizer application rate, is precisely adjusted in real-time. The system was deployed on a pneumatic groove-wheel fertilizer metering device and tested in field experiments, demonstrating impressive performance.
The results were promising: the average relative error of EC was just 2.70%, and the maximum coefficient of variation of the fertilization system response stability was 3.98%. The system’s response time was rapid, with a maximum of 1.60 seconds and an average of 1.28 seconds. Perhaps most significantly, the average fertilizer reduction rate was 12.39%, indicating a substantial improvement in fertilizer use efficiency.
The implications for the agriculture sector are profound. Precision agriculture is increasingly recognized as a key to sustainable farming practices, and this system represents a significant step forward in that direction. By optimizing fertilizer use, farmers can reduce costs, minimize environmental impact, and improve crop yields.
Looking ahead, this research could pave the way for similar systems to be developed for other crops, further enhancing the efficiency and sustainability of agricultural practices. As Xie notes, “This study provides equipment and technical support for rice side-deep variable-rate fertilization, but the principles can be applied more broadly.”
In an era where resource efficiency and environmental sustainability are paramount, innovations like this one are not just welcome but essential. They offer a glimpse into a future where technology and agriculture work hand in hand to feed the world more sustainably.