May reflect the common practice of modern agriculture, but it is no longer a single crop planting method, but is combined with technologies such as crop intercropping, robots, drones and precision agriculture to minimize the use of chemical fertilizers and plant protection products.
Pre-production: detect and analyze soil components, select appropriate varieties and fertilization strategies to screen and improve crop genes, and use image recognition technologies such as improving taste, enhancing insect resistance, and increasing yield to identify crop varieties, disease degrees and weed growth to achieve intelligent prevention and management of diseases, pests and weeds;
In production: Machine learning processes satellite image data to predict the impact of changes in weather and environment on crops, respond in advance and plant accurately, provide a standardized growth environment for each crop, and ensure its appearance;
Post-production: Computer vision robotic arm to carry out pre-sales quality inspection, classification and packaging of agricultural products·Big data analysis to understand market conditions and formulate sales strategies; artificial intelligence algorithm + multi-objective path optimization mathematical model to intelligently optimize logistics distribution paths and supply chain.