A fitting analysis method for matching nutrient release of potassium magnesium sulfate fertilizer with crop demand

CN121980820BActive Publication Date: 2026-05-29SDIC (SICHUAN) AGRI TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SDIC (SICHUAN) AGRI TECH CO LTD
Filing Date
2026-04-03
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

In existing technologies, the application of potassium magnesium sulfate fertilizer relies on experience-based judgment, which leads to a disconnect between the amount and timing of fertilizer application and the actual nutrient requirements of crops. This results in problems such as nutrient release that is too fast or too slow, affecting crop growth and yield. Furthermore, existing analytical methods lack multi-dimensional data fusion, dynamic curve fitting, and model validation, making it difficult to achieve accurate matching.

Method used

By employing multi-dimensional data acquisition and preprocessing, a dynamic fitting analysis model is constructed using nonlinear fitting and piecewise fitting algorithms. Combining time alignment, intensity matching, and bias analysis, the model parameters are iteratively optimized using the gradient descent algorithm to generate precise fertilization optimization suggestions.

Benefits of technology

It achieves precise matching of potassium magnesium sulfate fertilizer nutrient release with crop needs throughout the entire cycle and in multiple dimensions, improving fertilizer utilization, reducing planting costs, reducing nutrient loss and non-point source pollution, and adapting to the application needs of different soil environments and crop varieties.

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Abstract

The application discloses a fitting analysis method for matching nutrient release of potassium magnesium sulfate fertilizer with crop demand, relates to the technical field of intelligent agriculture, and comprises the following steps: S1, collecting fertilizer multi-condition nutrient release and crop whole growth period nutrient demand data and performing standardized preprocessing; S2, constructing a fertilizer nutrient release dynamic curve by using a nonlinear fitting method; S3, constructing a crop nutrient demand dynamic curve by using a segmented fitting method; S4, constructing a dynamic fitting analysis model integrated with multiple modules; S5, calculating a curve matching degree and identifying time offset and intensity difference; S6, establishing an evaluation system, grading and generating fertilization optimization suggestions; and S7, verifying and iteratively optimizing the model in combination with actual crop data. The application realizes full-cycle accurate matching analysis of fertilizer nutrient release and crop demand, is comprehensive in data collection, accurate in curve fitting, detailed in analysis results, can quantitatively evaluate adaptability and generate practical fertilization suggestions, and can be continuously optimized, thereby providing scientific data support for accurate fertilization.
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