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Find out how big data can solve global food insecurity issues and the different technologies used in this niche.

While the global population increases rapidly, the quantity of arable land will decrease over the next few decades. This means finding a solution for our food supply is now more important than ever.

The big question on everyone's mind is what to do about this seemingly impossible challenge. There has been a lot of talk about big data in agriculture and how it can help achieve global food security.

Understanding Big Data

So, what is big data? Big data is a term used to describe the large volume of data organizations collect and store. The data can be in many different forms, including text, images, audio, and video.

The increasing use of digital technologies has driven the growth of big data. Devices such as smartphones, tablets, and wearables generate more data than ever before. And, with the rise of the internet of things, there will be even more data in the future.

Global Food Security and The Challenges

Over the years, the world's population has been increasing rapidly. In 1950, the global population was just over 2.5 billion. Today, it is more than 7.5 billion and will reach 9.7 billion by 2050.

At the same time, the amount of arable land is decreasing. Up to 25% of the global landmass is now unfit for agriculture. This is due to soil degradation, salinization, and water scarcity.

Freshwater sources are becoming depleted, especially in the developing world. Global demand for fresh water will exceed supply by 40% by 2030.

Agricultural practices around the world are also unsustainable. We use large amounts of pesticides and fertilizers that harm our soil, rivers, lakes, and oceans. These chemicals can lead to dead zones - areas where

Of course, producing more food isn't the only answer to global food security. The way we make food also has to change if we are going to ensure sustainable growth.

Big Data Applications in Agriculture

Technology is seen as one of the key solutions to global food security. There is a lot of potential for big data and analytics to help us produce more food with fewer resources.

Some of the ways that big data can be used in agriculture include:

Precision farming

Precision farming is a technique that uses data from sensors to help farmers optimize their crops. The data is collected from weather stations, satellite imagery, and soil monitors.

This allows farmers to apply the right amount of water, fertilizer, and pesticides to each plant. It also helps to reduce waste and increases yields. The benefits of precision agriculture include:

· improved yields

· reduced inputs (water, fertilizer, pesticides)

· increased profits

· sustainable farming practices

· better quality food

Precision agriculture is essential in the developing world, where there is a lot of growth potential. It can help to increase yields while also improving quality.

Crop Monitoring

Crop losses are every farmer's nightmare. They can amount to millions of dollars in losses every year. Big data and analytics can help farmers detect crop pests and diseases early. This allows them to take action before the problem becomes too large.

Data from satellites, drones, and other sensors can create maps of agricultural land. These maps can provide information on soil type, irrigation systems, crop health, and the like.

Reducing Food Waste

According to the United Nations Food and Agriculture Organization (FAO), as much a third of the food produced in the world is wasted. This is not only a waste of resources, but it also harms the environment. Big data can help us reduce food waste by providing insights into where and why food is wasted.

Big data can be used to reduce food waste by providing real-time information on the freshness and expiration dates of food items.

This allows waste reduction by properly managing inventory and making smarter purchasing decisions. For example, if a shipment of bananas has only three days left before they expire, stores can sell them at a discount rather than let them go to waste.

Predictive Analytics

Factors like erratic rainfall and crop diseases can lead to unexpected yield losses and price spikes. Big data and predictive analytics allow us to forecast these problems and adjust accordingly.

The cost of farming is also dependent on factors like commodity prices, interest rates, the weather, and the availability of labor. Predictive analytics allows farmers to make more accurate decisions on when they should sell their crops, what they should plant, and whether they should consider alternative crops.

Predictive analytics can also help us be more effective in food distribution by predicting where shortages will occur and developing appropriate response plans.

Animal tracking

This involves using RFID tags to track the movement of animals from the time they are born until the point of slaughter. This provides a complete history of each animal and helps farmers monitor their health.

With data from different farms, it's possible to determine the best practices for feeding, breeding, and raising livestock. This can reduce costs while also improving growth rates and milk production.

Play Your Part; Leverage Data Science

Digging through piles of data is easy with the right tools, but it still takes trained experts to make sense of the information. If you're a farmer looking to increase your yields and profits and help boost the world's food production through big data, consider partnering with a technology consulting farm.

Advanced Network Professionals are a team of IT technicians experienced in data analytics and can work with you to develop a precision agriculture plan that fits your specific needs. Whether you would like to track your livestock, improve the quality of your product, or increase your yields and profits, you can take a step towards a more sustainable future.

As a leading digital marketing agency, we're passionate about helping companies reach their targets through big data and analytics. Contact us today to learn more about our services!