Smart Farming: How Algorithms Help Agronomists

29 Jan, 2020

by Ivanna Bashmat, Tech Lead at N-iX

Every year the world population is growing and this sets new challenges for agro-industry to produce enough goods. With IT, new opportunities are available for agro-industry: now plant breeding, disease prevention and soil analysis are enhanced by the power of digital technology.

Agriculture is one of the oldest industries on the planet and humankind accumulated a massive amount of knowledge in this sphere. Even without digital technologies, agro companies are doing incredible things. Yet today they see the value Information Technologies can bring them. The things we are doing together with our partners in the agro-industry are world-changing. Agro businesses today have access to satellite imagery, soil analysis and a lot of other information that allows farmers to monitor farms and crops, detect plant diseases faster and eradicate them before the damage is done. All these technologies are transforming the industry and it’s great to be part of it.


Prediction is one of the most valuable technology applications used for agro-industry development. Based on satellite imagery, historical weather data, and forecast, crop diseases can be spotted at the early stages, which reduces the impact of the disease and costs of beating it. One of the solutions our team is working on uses terabytes of satellite data to make recommendations and predictions helping farmers to produce better yields. So precision farming is already affecting the industry and with the advancement of technology, it’s going to get more and more accurate. Virtually any industry nowadays is trying to benefit from big data analytics, data science, and machine learning. I believe these technologies have great potential in precision agriculture and can solve many issues the industry is facing.

Also, there are a lot of interesting technologies in smart farming. For example, we are developing a solution that ensures uninterrupted control of crop growth thanks to automation and mobile technologies. So a farmer doesn’t need to go to the field and check the state of the crop they can log into the app and see everything on the phone. In addition, they can take photos of the crops, upload them to the app and instantly send to the person responsible for solving this issue. So I think predictive analytics and smart farming are among the key tech drivers of the sector.

Our team at N-iX is working on several solutions for Origin Enterprises, a huge agro group. The enterprise is doing incredible things in agriculture, they do a lot of research, and provide farmers with data and insights that help them harvest better yields. However, at some point, the company realized that they needed to invest in digital technologies to offer more value to their customers and stay competitive. They acquired Ag Space and our team became an integral part of Origin Digital. This allowed Origin to grow its tech capabilities, particularly in expanding its data-driven crop management solutions for customers and agronomists. 

We are developing software both for common tasks, like creating reports about issues found on the field, and complicated ones, for example, satellite imagery analysis, yield predictions, smart planning for nutrients, etc. 

Nowadays satellites are creating terabytes of data daily. Our goal is to provide access to this data in a structured and efficient way. We cooperate with different satellite providers, get loads of data from them, and use NVDI imagery to enable businesses to make data-driven decisions. An agronomist or a farmer can access not only satellite images but also a wide range of analytics based on them, which helps them track crop growing progress and find pests and diseases. 

Another great feature of the solution is nutrient planning and wise distribution of nutrients based on soil analysis to reduce costs and increase yield. It helps the farmers and the agronomists to determine which nutrient to use in a concrete situation. There are a dozen of input parameters and different strategies you can use organic nutrients as much as possible, you need to understand that some nutrients may be not available, like different kinds of manure. Also, the app takes into account delivery costs and helps farmers minimize them.

dsc_7338-7The prediction models available in the app are based on NVDI imagery, soil analysis, weather data and also the basic input information provided by the farmers. All this combined enables the farmers and the agronomists to get accurate estimates about yield and adjust nutrient application as needed to achieve their goals.

The solutions we are working on are used across the globe, and the problems in different regions are different. The challenges the farmers in Africa face are not the same as in the UK but the app serves them equally well. For instance, the farmer in the UK spots a disease on a certain plant, takes photos, uploads them into the app, assigns the tasks and gives recommendations on how to solve the issue. While in Africa the tasks are totally different – whether it’s an elephant that died in the field or a broken fence. The solution we are working on helps to report these problems and solve them faster.

It’s hard for me to talk about the agro-industry in general as I’m not really the expert in the field. I can only speak from a technological perspective. From our projects at N-iX, I can say that forward-looking agro-businesses are looking for ways to enhance their IT capabilities. They build their own digital departments and make partnerships with software development vendors and 3rd party providers to innovate and adopt digital technologies. Those who do it sooner, have more chances to succeed. 

As for agritech, there are a lot of technologies on the market, such as sensors, IoT, drones and other kinds of hardware, Artificial Intelligence and Machine Learning, robotics. However, it’s important to adopt technologies that can really solve specific agriculture problems. Companies need to realize what will fit their business needs and whatnot, and we are trying to help them in that.

Agro-industry looks not only in the direction of developing software but hardware as well. The reason for that is a very complicated process of getting input data for any type of analysis. 

Satellite images might be expensive and you have to rely on third-party providers. Also, you need to take into account weather conditions, the time when the picture was made, satellite view angle and many other parameters. This is why the industry is looking for other sources of data and effective ways of analyzing it. 

This industry requires a massive amount of knowledge and I definitely didn’t expect it. Before that, I had worked in healthcare and I thought that it was a pretty complicated domain. And then I got into agriculture and it has so many nuances. So I realize that, maybe, healthcare is not as big as I thought. 

Besides, it involves a lot of business analysis and many business models are used in agro-industry. You know that a plant can get a disease. While the agronomists know that when this plant is growing and it has 3 leaves, and they spot the disease on the fourth leaf, and this disease has a certain incubation period and it only appears on the fourth leaf, so it got it at that point. So it’s mind-blowing how much analysis is made. Every detail matters and you need to take it into account. You gather and process a lot of data which seems to have no value separately on its own but together it makes a difference and it’s very innovative.

Above all, it brings great value to all of us, to the humankind. You understand that the population of the Earth is growing and people need to have more food to survive. And this is a great chance for farmers to get investments to develop the industry. So you realize that you bring real value to people.

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