3 Effective Applications of AI in Agriculture

Agriculture is undergoing a new phase of development owing to AI, which is being used in a variety of ways to improve productivity, from using computer vision technology for crop and soil monitoring to utilizing disease detection and predictive analytics.

Automatic Weeding

A field’s major food crop is stunted by the growth of weeds, which are unintentionally cultivated natural plants. These prevent the crop from receiving necessary light and nourishment. Weeds make the main crop more of a target for pests since they weaken the crop overall.

Farmers used to manually pull these weeds from their fields. However, with the development of AI comes a new option for farmers: autonomous weeding. Robots and machinery are used in automatic weeding to clear the field of unwanted vegetation. This is achieved with the use of laser lights.

The whole playing area is surveyed by robots and AI devices. They have cameras built inside them. In addition, weed-identification software is linked to these cameras. Once detected, the AI sends out orders to its high-powered lasers to destroy the weeds by heating them up to an unsustainable level.

Automatic Harvesting

Harvesting includes gathering useful components of crops for consumption or sale. Manual work and handpicking are essential to the traditional harvesting process. AI, on the other hand, makes use of electronic devices and computer programs for this function.

The camera is programmed with software that can identify the harvested goods. Products of harvesting can be edibles like fruits and vegetables. The machine then instructs the AI to choose and collect the desired items based on the analysis it has performed.

Recent years have seen the use of these devices for the harvesting of peppers, lettuce, tomatoes, apples, and other crops.

Moreover astounding is the fact that these machines choose and harvest only fully ripe fruits and vegetables. Predictive analysis is a step further.

For decision-making and object detection, machine learning algorithms rely on both previously collected and newly-input data.

Plant Disease Detection

The ability to detect plant and agricultural diseases is another benefit of AI technology. The internet is rife with similar artificial intelligence programs. Such software aids in the early diagnosis of issues affecting plant health. After examining the issues at hand, these programs scour the web for potential answers.

The intelligent farming solution is implemented by AI using picture recognition technology. The camera’s image of the plant is sent into an image recognition program. The program then creates data on the disease, as well as a strategy for managing it and a treatment plan.

The program Plantix fits this description. As a mobile application, it is rapidly expanding. It includes a database with data on over 100,000 images of the ailing plants.

And it can detect more than 60 different plant diseases. Tomatoes, peppers, melons, squash, and lettuce are all susceptible to a wide range of diseases, and this resource may provide information on all of them.

Conclusion

Implementing AI technologies and algorithms in agriculture is an effective and vital necessity to fulfill the rising demand for food, despite the fact that there exist hurdles.

Overuse of pesticides, physical labor, and inefficient processes are all major problems in agriculture, but AI has the potential to solve all of them. The use of AI is speeding up and improving agriculture activities.