Artificial intelligence model-guided efficient cotton planting method

Abstract

The present invention relates to the interdisciplinary field of intelligent agricultural planting and artificial intelligence (AI), and in particular to an AI model-guided efficient cotton planting method. The method includes the following steps: S1: multi-source heterogeneous data collection and preprocessing; S2: multi-task AI model training and optimization; S3: personalized planting strategy output; S4: field execution and data feedback; and S5: dynamic model iteration. The AI model-guided efficient cotton planting method constructs an integrated hybrid model of "environmental perception-growth prediction-strategy generation", realizes full-cycle precise management and control of cotton planting oriented by multi-objective functions, solves the problems of traditional planting relying on experience, serious resource waste, and lagging pest and disease prevention and control, is applicable to different varieties including upland cotton and sea-island cotton, adapts to large-scale planting in different cotton-growing regions including the Yellow River Basin, the Yangtze River Basin and the inland northwest, and is particularly suitable for modern cotton fields with high requirements for yield, quality, and resource conservation

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