4 technologies changing the future of agriculture

 Finding ways to leverage on technology to increase agriculture sustainable growth will be a key objective in the coming 10 years.The world population is expected to grow from 7.3 billion today to 8.2 billion by 2025, and 9.7 billion by 2050.Globally, humankind needs to produce 70% more food than is currently produced. This extra demand contrast with the decreasing of human agriculture labor due to urbanization and aging population.

Nevertheless, several companies are investing in new technologies that could provide higher productivity and efficiency in the way we manage agriculture today.

There are four technologies that are changing the face of agriculture worldwide by bringing mobile broadband, cloud and mobility in order to help farmers to accelerate productivity. 

1. Precision Agriculture

Precision agriculture is an farming management process that gather, measures, and responds to inter and intra-field variability in crops to optimize resource and yield. This process requires the combination of mobile communications, sensors, robotics, and big data analytics.

 The foundation of precision agriculture is the collection of data with sensors. Temperature, weather, nitrate content, soil quality, and overall plant health can all be measured using periodic or continuous samples from land equipment or drones.

The value comes from running data analysis in order to make better decisions or complement farm management information system . With more data from sensors and machine learning abilities this technology will involved into artificial intelligence soon. The integration of farm robotics, tractors, drones, soil sensors will allow decisions to be completely automated in the future allowing for a strong improvement in productivity. 

MyAgCentral example

MyAgCentral is unique in the market, offering fully integrated cloud-based software that manages everything from day-to-day operations to forward-looking yield and financial modeling through a single, easy to use, visually rich interface.

MyAgCentral connects all of a grower’s data, machinery, equipment, tanks, and processes into a single, easy-to-use, secure, cloud-based system. With MyAgCentral, any farmer can easily access manage their data and use that data to make better decisions. The systeml also enables all members  to easily share information, automate work processes, see the status of work orders, and centralize data storage. Growers, seed dealers, equipment dealers, fertilizer dealer, coops, and industry specialist like agronomists, crop scouters, and crop insurance agents can all benefit from the simplicity of sharing information using MyAgCentral.

2. Drones 

The development of drones for agriculture is fast. . New capabilities added like Accelerators, gyroscopes, magnetometers, GPS, radios and microprocessors, and high-resolution cameras at a reasonable price are making them affordable and relevant.  Even today, many activities are already completed by drones like crop monitoring, aerial mapping, seeding and leaves health analysis. In the future, computerized vision will allow drones to do real time analysis of crop for seeding or pesticide usage purposes. With all information available ,drones will be able to learn different yield optimization strategies creating so called "learning farms" concept. 

Sensefly example

Sensefly drones ( part of Parrot company) can capture highly accurate images of farm fields, covering up to hundreds of hectares/acres in a single flight. Without the cost and hassle of manned services. At a far greater resolution than satellite imagery provides, even when there is cloud cover. By using image processing software farmers can then transform these shots into one large 'orthomosaic' image. Apply algorithms like Normalized Difference Vegetation Index (NDVI) to this image and you create a reflectance map of their crop.This map is the key to boosting yields, cutting costs, and driving your business forwards. It highlights exactly which areas of crop need closer examination – meaning less time spent scouting, and more time treating the plants that need it.

3.Unmanned Vehicles

Unmanned ground vehicle (UGV) leverage on vision sensors and machine vision systems to navigate across different environment without the need of a driver. Despite today there are several cases of unmanned vehicles using laser transponders but in the near future, existing tractors will performing repetitive, time-consuming tasks, leaving farmers time to manage other more critical operations reducing equipment costs, lowering operating costs and increasing yields.

For instance, Unmanned Tractors can can address one of the most pressing problems in agriculture today - a lack of qualified labor during peak season needs. The system can be installed on existing tractors to make it truly autonomous without relying on GPS. It can be trained to do countless repetitive field tasks on its own.

ATC example 

Autonomous tractor company (ATC) has created a new navigation technology for existing tractors. AutoDrive is an autonomous navigation system available for tractors. It offers highly precise, repeatable accuracy that addresses the issues farmers face with GPS-based units: no reception dead spots, no problems with sunspots or other interference. It relies on ATC’s proprietary Laser-Radio Navigation System (LRNS) for sub-inch positioning data and FieldSmart artificial intelligence software that allows farmers to “train” the tractor without programming. Sonar systems provide full perimeter safety and pan-tilt cameras communicate via cellular to allow farmers to monitor progress and remotely resolve issues at any time.

4. Big open data

One of the biggest trends we will see in the future of agriculture will be the use of data, specially in a shared digital economy. The opportunities that can be created by farmers sharing their crops data across the globe are enormous. This could be key to meet the global pressures of a growing population and food demand, yield improvements need to be widely adopted.

The value of open big data to agricultural companies is similar to other areas of the digital economy like internet, where the value of data sharing is bigger than the value of an individual proprietary data piece. This is specially valid for smaller farms that need to share data in order to achieve comparable yields to larger industrial farms.

Syngenta example

In April 2015, agriculture company Syngenta published its first open datasets as part of The Good Growth Plan, with a view to improving global resource efficiency, soil and biodiversity conservation, and the prosperity of small farms in developing countries.

The data Syngenta is collecting from real-world farms in more than 40 countries is a unique resource with the potential to help understand what could make the world’s big and small farms more productive and efficient. Turning the data into knowledge and insight takes time and expertise.By publishing data Syngenta help to collaborate better, be accountable as a trustworthy partner, improve the rigor of  data analysis, and track the effectiveness of their value proposition.