Perks of Implementing Big Data in Agriculture!

Data is one of the most essential commodities in today’s time. Companies and market research firms are spending a lot of money to collect and process large amounts of data. They refer to that data as “Big Data”.

Big data can be unstructured, structured, or semi-structured. Organizations mine it to gain valuable insights and information for predictive modelling, machine learning projects, and other cutting-edge analytics applications.

Experts are searching for ways of implementing big data in agriculture. Insights generated from the data can play a vital role in boosting production and preventing the global food crisis. It can change the way growers carry out farming procedures and deliver immense profit!

How Big Data Can Revolutionize the Agriculture Sector?

Farmers have followed traditional farming techniques for many centuries. They use methods taught by their predecessors to grow crops. Things have changed and old methods are not as effective as they once were. Big data in the agriculture industry can benefit farmers, who are not afraid of experiments.

It involves the use of information, technology, and analytics to deliver essential guidance to farmers. Big data can provide important details about the entire agriculture sector. Users can extract insights for specific segments to become more efficient.

Big Data processing firms are using cutting-edge data mining methods to produce beneficial information. It can reveal vital patterns that growers can follow to avoid losses, improve profit, and gain better yield.

How Big Data is Collected?

Growing population and reducing farming land have become big issues for countries across the globe. Governments and global agencies are seeking efficient plans to counter issues, such as climate change and growing food demand. Industry leaders are seeking assistance from experts using technologies, such as Big Data, IoT, cloud computing, and analytics.

IoT is pretty helpful when it comes to collecting data. Organizations are providing precision farming equipment to collect the required information. Those pieces of equipment use sensors for data collection. Sensors are installed on various farming equipment to get data related to crops, soil, air, water, seed, and other inputs.

Analysts receive real-time data from fields, which they integrate with other important details in the cloud. They use pricing models, weather data, and other information to generate insights.

Those insights and patterns help in recognizing the root cause of farming issues. Agricultural institutes, seasoned farmers, and research companies can work on new solutions. Those solutions can improve soil quality, reduce water wastage, and help farmers in saving a lot of money.

The agriculture industry is gradually adopting analytics. Many Big Data companies are working to find efficient solutions for the current farming issues. Their efforts are paying off and all the farmers may benefit from big data in Agriculture.

Is It Easy to Implement Big Data in Agriculture?

Big Data’s implementation in agriculture can be pretty beneficial. However, it comes with many challenges, such as:

• Quality of data

It is a big challenge to generate qualitative data for agriculture management information systems. Companies are relying on precision farming technologies to produce high-quality information. Reliable sensors and real-time data can resolve this issue!

• Data mining

Data complexity, unstructured data, data privacy, etc. make data mining a tough task for big data specialists. Organizations receive a huge amount of data. It is a painstaking task to structure the data and produce patterns that can be helpful in farming. Data scientists hope to receive industry-specific information to develop essential insights.

• Cost of data-producing equipment

Farmers from developed countries may easily install sensors, tools, and equipment that share important farming data. It is not easy for farmers from developing countries. The cost of precision farming equipment is a big concern for millions of farmers. Countries find it a challenging task to reduce the cost of the required equipment to gain valuable data.

Data integration from many sources is a herculean task. It is another big challenge faced by organizations trying to implement big data in agriculture. Experts are working on solutions and those solutions can be pretty beneficial for all the farmers and consumers.

What are Some Use Cases of Big Data in the Agriculture Sector?

Big data can be implemented in many interesting ways. We are still missing tools and technologies for extra insights from the enormous amount of data available. The most practical use cases of big data in agriculture are:

• Ethical use of pesticides 

Pesticides are harmful to consumers and the ecosystem. They are essential to protect the crop and get the best yields. Therefore, farmers use them whenever required to keep pests away from the crop.

Big data can help in administering the use of pesticides. Farmers can get efficient ways of using pest-removal solutions to prevent adverse effects on the soil and environment.

• Producing sufficient food for the growing population

Food shortage is a real issue. Wars, reducing farming land, and unethical farming practices led to food shortages in many countries. Big data can provide ways of improving soil health. That will lead to healthier crops and there will be more food available for people across the globe.

Big data can provide granular data on water cycles, rainfall patterns, fertilizer, and other elements of farming. It can provide more reliable information for more favourable outcomes.

• Supply chain management

Food wastage occurs due to the supply and demand gap. A better food delivery cycle should decrease to address this problem. Big data can generate insights on how often producers should bring their product to the market to get the best price and prevent wastage.

• Better use of devices, machines, and farming equipment

Experts are recommending farmers to install various sensors and buy precision farming equipment. Those devices can produce real-time data and inform farmers about crop health, soil health, irrigation timing, and monitor acres of land. It can make things much easier for farmers, who own a large farm land.

Conclusion

Big data can address many issues and improve many farming practices. Scientists are working on ways of implementing this cutting-edge solution in the agriculture sector. This unexplored territory can resolve issues consuming profits and reducing food quality and supply!