The global bottom line of agriculture as an industry has been a hotly debated topic. The agriculture sector emits massive amounts of CO2 and other greenhouse gasses every single day and is one of the primary forces for climate change. However, that’s not the result of agriculture itself, but the lack of efficient ways to control the waste produced by the methods currently used.
The solution to this problem is two things: regenerative agriculture and data science. By combining these two things, industries as a whole can significantly decrease their carbon footprint without losing the efficiency they have become accustomed to. Today, we will be discussing what these two things mean for agriculture and why combining them is beneficial for global agriculture.
What is Regenerative Agriculture?
Regenerative agriculture is a new system of farming procedures, policies, and principles that are focused on rehabilitating and enhancing all the resources that farming currently uses.
Instead of focusing on how to “consume” resources (i.e. depleting fuel, water, and fertilizer), this system is focused on looking for ways to efficiently use those resources and make them as reusable as possible.
There are five main principles in regenerative agriculture, which are:
Low or No Till
To achieve the best soil quality, the disturbance of soil must be minimized or nonexistent. In this way, the soil is allowed to naturally generate organic matter. This new and healthy soil is thus much healthier and more resilient than over-tilled soil. It’s a simple principle, but it is the foundation of all agriculture to have healthy soil, as that’s what plants and by extension, animals need to thrive.
Protect The Soil’s Surface
Things such as raindrops and direct sunlight greatly affect the health of the soil. To prevent this, a layer of growing crops or other organic residue acts as armor against these threats. Raindrops are harmful not because of any specific chemicals, but the kinetic force with which they impact the soil. The force disrupts the natural flow of soil and makes it less absorbent. The same goes for too much sunlight drying out the soil.
Keep Living Roots In The Soil
This is one of the more difficult principles, but it is no less vital. Living roots feed the beneficial bacteria and fungi that keep farmers’ crops and soil healthy. These tiny organisms all rely on living roots to survive, and their health directly correlates with the overall health of farmer’s field’s crops. It’s all crucial to maintaining the ecosystem of farmer’s crops and the animals around them.
Diversify farmer’s Crops
Monocultures are not a healthy thing for the environment. A diverse ecosystem is needed to have a fruitful and self-sufficient farm, and the best way to do this is by diversifying farmers’ crops. Companion cropping (pairing two different crops in the same field) and cover cropping (crops that aren’t necessarily used for harvest, but add much-needed biodiversity to the field’s soil).
Let Animals Graze Freely
Instead of stuffing livestock into tightly packed warehouses or barns, farmers should integrate animals into the fields. Their presence promotes soil fertility by eating pests, weeds and having a stress-free environment for animals to go about their business (i..e. Natural fertilizer, healthy animal mating, etc.)
What is Data Science?
In simple terms, data science is the use of programming and mathematics to gather beneficial information from raw data. It streamlines the gathering and analysis of information that would take several days manually and makes it so it occurs in only a few minutes.
For farmers, data science is an incredibly beneficial tool that lets farmers see their farms’ yield, consumption of resources, and cost of overall production, among other things.
How Does Data Science Help Regenerative Agriculture?
There are several ways with which data science is beneficial to the principles of Regenerative Agriculture.
Make Data Accessible
Data science can gather all of that data and present it to farmers in a way that helps them make informed decisions. Instead of having to sift through tons of handwritten reports of a farm’s status and the success of your regenerative agriculture practices, it can be presented much simpler.
An analytical approach to regenerative agriculture is needed to measure the practical effects of your efforts. After all, regenerative agriculture is a tricky process at first, and concrete data that farmers can easily understand is key to a successful farm.
Minimize Waste
The primary function of all farmland is to provide food, and data science can help farmers find the precise amount of resources needed for maximum yield without overextending their resources where it’s not needed.
Instead of working with averages, data science gives you much more precise numbers about how much resources are needed for a yield. This not only saves resources but also reduces the overall waste produced by industrial agriculture, which makes it crucial for sustainability management.
Climate Prediction Models
The fruits of agriculture are directly related to the climate. There’s a reason why farming is a seasonal business, and that’s simply because certain crops only grow in certain parts of the year. For maximum yield, crops need to be planted at just the right time.
In addition, simple things such as weather forecasts are important for the daily upkeep of crops. Data science can forecast the weather accurately, giving farmers an edge on what to do with their farms ahead of time.
Autonomy
Data science is very helpful for providing data to machines so they learn what the best way to farm is. While this benefit is only in its theoretical early stages, the best example is automatic irrigation and self-driving farming vehicles.
The endgame of technology and farming should be fully automated, especially for en masse food production. Through data science and regenerative agriculture, the industry is moving towards an efficient yet eco-friendly form of agriculture.
Conclusion
Regenerative agriculture has been proven to be an incredibly beneficial set of principles to follow all across the globe, especially for massive farming projects. Additionally, the vast amount of mathematical issues needed to pull it off is possible thanks to advanced data science. Farms are changing, and to save the environment, they need to make the change as soon as possible.
Author Bio:
I am a freelance writer from Manila. I find joy in inspiring and educating others through writing. That’s why aside from my job as a language evaluator for local and international students, I spend my leisure time writing about various topics such as lifestyle, technology, and business.