Agriculture involves a number of processes and stages, the lion’s share of which are manual. By complementing adopted technologies, AI can facilitate the most complex and routine tasks. It can gather and process big data on a digital platform, come up with the best course of action, and even initiate that action when combined with other technology.
Combining artificial intelligence and agriculture can be beneficial for the following processes:
The role of AI in the agriculture information management cycle
* Analyzing market demand
AI can simplify crop selection and help farmers identify what produce will be most profitable.
*Farmers can use forecasting and predictive analytics to reduce errors in business processes and minimize the risk of crop failures.
By collecting data on plant growth, AI can help produce crops that are less prone to disease and better adapted to weather conditions.
*Monitoring soil health
AI systems can conduct chemical soil analyses and provide accurate estimates of missing nutrients.
AI can monitor the state of plants to spot and even predict diseases, identify and remove weeds, and recommend effective treatment of pests.
AI is useful for identifying optimal irrigation patterns and nutrient application times and predicting the optimal mix of agronomic products.
With the help of AI, it’s possible to automate harvesting and even predict the best time for it.