Key Application of Machine Vision to Agriculture

With the continuous development of technology, agriculture is steadily moving towards a new digital era. Agricultural intelligent perception technology, centered on machine vision, has emerged as a driving force for the advancement of smart agriculture. This article will introduce the key technologies and application of machine vision to agriculture.

The Key Application of Machine Vision to Agriculture

The wide application of machine vision to agriculture not only heralds profound changes in production methods but also promotes further upgrading of industrial structures. Undoubtedly, this plays a crucial role in enhancing the degree of agricultural modernization and ensuring sustainable agricultural development.

Application of Machine Vision to Agriculture

Crop Monitoring and Management

Machine vision systems can be used to detect the growth and health status of crops. By capturing and analyzing images of plants, farmers can determine if there are pest problems, if irrigation or fertilization is needed, and when to harvest.

Soil Analysis

Machine vision can be used to analyze soil quality and characteristics. This helps in deciding the best planting and fertilization plans.

Sowing and Planting

Automated machine vision systems can be used for precise sowing and planting. They can identify cultivation points in the soil, ensuring that plants are sown at the predetermined spacing and depth.

Harvesting and Picking

Machine vision technology can aid in the automated harvesting and picking of fruits, vegetables, and other agricultural products. Vision systems can determine when fruits or vegetables are ripe for efficient harvesting.

Pest Monitoring and Management

Machine vision can detect pests on crops, helping farmers to take early control measures and reduce losses.

Precision Fertilization and Irrigation

Machine vision systems can detect nutrients and moisture in the soil, aiding in precision fertilization and irrigation to improve resource utilization efficiency.

Plant Protection Drones and Autonomous Machines

Drones and autonomous machines equipped with machine vision systems can autonomously patrol fields, capture high-resolution images, and analyze vegetation and soil data.

The precision of modern machine vision systems enables plant protection drones to monitor the macro conditions of crops. This allows agricultural experts to take timely measures to prevent losses due to disease, pests, or adverse environmental conditions.

For example, when growing cotton, spraying defoliants is a critical step. The traditional method involves using tractors to spray in the fields, but this can damage the cotton, and areas with high cotton growth are inaccessible. Drones equipped with machine vision systems can efficiently and eco-friendly apply pesticides.

They avoid damaging the cotton and automatically adjust the pesticide amount based on the terrain and crop distribution. Compared to traditional methods, drones significantly reduce pesticide usage and labor, enhancing operational efficiency and effectiveness.

Data Analysis and Decision Support

The data generated by machine vision systems can be processed through data analysis algorithms, helping farmers make more informed decisions to improve yield and quality.

Smart Agricultural Machinery

The application of machine vision to agricultural machinery, such as intelligent harvesting robots, can operate autonomously and perform precise operations based on visual data.

Monitoring Environmental Factors

Machine vision can also be used to monitor weather conditions and other environmental factors to help determine the best agricultural practices.

In summary, application of machine vision to agriculture helps improve agricultural production efficiency, quality, and sustainability while reducing resource waste and environmental impact. This is crucial for meeting the growing global food demand and agricultural sustainability.