Artificial Intelligence mimics human cognitive behaviors and makes intelligent decisions in an automated fashion in various industries. It's well known that we are entering the golden era of AI. Some examples in the real world are the contributions from computer vision systems, self-driving cars, and robotic process automation. AI significantly impacts every domain, and every industry is looking to automate different jobs using intelligent frameworks.

Agriculture and farming are among the oldest occupations in the world that are still timeless today. The global population is estimated to reach 9 billion by 2025, so the demand for agricultural production practices will rise exponentially in the next few years. Land and water resources are getting depleted faster, and we need innovative methods to fulfill supply-chain demands. A good artificial intelligence online course is necessary to break into the best AI jobs in the world, especially in the agricultural sector.

Stages of Agriculture

Artificial Intelligence is used in modern-day farming to solve traditional farming challenges. Before we discuss its applications, let's explore the different stages of agriculture.

1. Soil Preparation

This is the phase where farmers prepare the soil for growing crops and seeds. Large lumps are broken down, and the fields are prepared by removing debris. Organic matter is added to the soil and fertilizers to grow the ideal produce.

2. Sowing

Sowing is done when the seeds are planted, and the distance between them is double-checked. The planting depth is also analyzed, and climatic conditions like temperature, humidity, and rainfall are all factored in.

3. Adding Manures and Fertilizers

Fertilizers are nutrients for plants and contain a mix of nitrogen, phosphorus, and potassium. Adding fertilizers and manicures to the soil ensures soil fertility and that plants grow into healthy varieties. It improves the quality of crops, adds nutrients to the soil, and provides adequate natural yield.

4. Irrigation

Irrigation ensures sufficient moisture in the soil and maintains humidity. Good irrigation practices can prevent overwatering and underwatering, which are responsible for damaging crops and impairing their growth. 

5. Weeding

Weeding is the removal of unwanted plants that grow alongside your crops. Weeding can help improve crop production, increase harvest, reduce plant diseases, and enhance crop quality.

6. Harvesting and Threshing

Laborers collect crops from fields and take them to market. This phase involves cleaning, sorting, packaging, and cooling. Threshing is the separation of grains from plants and edible components. It is a part of harvesting. However, it does not include removing the bran.

7. Storage

Storage preserves crops for later use or sale. It can include packaging and transportation and prepares farmers to handle crop deliveries during periods of famine when resources for production are not abundant or adequate.

Challenges Faced by Farmers in Agriculture for Different Farming Methods

There are many challenges faced by farmers who engage in the different methods of farming in agriculture. Pollination and deforestation result from changes in climatic conditions which can hamper the soil preparation, harvesting, and crop production processes.

Every crop has its unique nutrient profile, and any nutritional deficiencies can stunt its growth or affect overall yield. Farmers need to measure nutrient levels in soils and ensure that the quality of crops is not affected. Weed protections play a critical role, and we understand that uncontrolled weed production can lead to increased production costs, soil moisture loss, and other farming problems.

The Use of AI in Agriculture

The agriculture industry uses Artificial Intelligence to solve present-day challenges, boost revenue, and improve farmers' livelihoods. Organizing data for farmers, reducing their workloads, and improving a wide range of agriculture-related tasks throughout the supply chain are some of the many benefits of AI implementation in this field.

As technology and farming practices evolve, AI will play an indispensable role in increasing crop production without negatively impacting the quality of yields. 

Below are some important uses of AI in agriculture:

1. Weather Forecasting 

Changes in climatic conditions can make it challenging for farmers to determine when is the right time to sow seeds, prepare soils, and prepare for harvesting. AI can analyze weather conditions and give farmers real-time updates about regional climates.

2. Soil and Crop Health Monitoring

It is vital to use suitable fertilizers that can improve crop growth. Soil and crop health monitoring analyzes if soil conditions are fair and whether or not they are degrading. Due to increasing deforestation practices, it can be challenging to determine if the soil is of optimal quality. 

Nutritional deficiencies can be prevalent, and it is critical to address them before growing crops. AI can use image recognition technology to capture plant images using smartphones and predict future yields. Soil analysis by farmers can improve production practices and increase productivity rates in farming. Data about fields can be captured by drones sent in the air, and farmers can analyze this to monitor the health of their crops constantly.

3. Predictive Analytics and Precision Farming

AI applications can promote controlled farming and keep environmental conditions constant or close to the ideal ranges. Farmers can receive intelligent guidance about crop rotation, water management, wind speed, solar radiation, herbicides, and pesticides and learn how to prevent modern-day plant and soil diseases. They can get customized production plans based on land sizes, economic conditions, etc. Farmers can optimize yields down to individual rows of plants, and AI technology can help perform multiple tasks in farming. The layer of uncertainty is decreased since farmers are always informed of what's going on and can adjust their farming preferences and production mechanisms accordingly.

4. Pest Control

Pest control is one of the worst problems in agriculture and seriously jeopardizes fields. AI can send smartphone alerts to farmers, compare historical data using machine learning algorithms, and help them take the necessary precautions.

Conclusion

Artificial Intelligence helps farmers automate their production practices and shift towards precise cultivation. Agriculture is the backbone of our economy, meaning higher crop yields and ensuring optimal quality without depleting natural resources are paramount. A well-framed artificial intelligence online course lays the foundations of good AI-enabled farming practices and prepares students for rewarding careers in agriculture.

There is a demand for AI professionals and data scientists stepping into the agricultural domain, and many job vacancies are opening. If you've ever thought of pursuing a career in agriculture using AI, there is no better time to start than now.