digital agriculture

The AI agricultural revolution – a fertile ground for growth

Agriculture and farming are some of the oldest and most important professions in the world. Humanity has come a long way over the millennia in how we farm and grow crops with the introduction of various agricultural technologies. 

Food security and agricultural challenges

As the world population continues to grow and land becomes scarcer, people have needed to get creative and become more efficient about how we farm, using less land to produce more crops and increasing the productivity and yield of those farmed acres. 

Global trends are influencing food security, poverty, and the overall sustainability of food and agricultural systems.

The bottom line – agricultural outputs must improve 

According to the World Government Summit Report called Agriculture 4.0 – The Future Of Farming Technology,  four determinants of challenges for agriculture in the coming years were highlighted:

  • Demographics
  • Scarcity of natural resources
  • Climate change
  • Food waste

The report states that, due to continuously growing demand, by 2050 we will need to produce 70 percent more food. 

About 800 million people worldwide suffer from hunger and  8 percent of the world’s population (or 650 million) will still be undernourished by 2030. 

The world’s population is assumed to be nearly 10 billion by 2050, boosting agricultural requirements. At present, about 37.7% of the total land surface is used for crop production. 

The challenges of water and fertilizer supply, and the loss of land, against the backdrop of global warming, at an age of population growth, are bringing mankind to a point where it must adapt and innovate to survive. 

Just as in the era leading up to the first agricultural revolution, our way of living and consumption does not allow the status quo to continue as is.

Agriculture 4.0

Agriculture 4.0

Agriculture 4.0, which is akin to Industry 4.0 is a term for the next big trends facing the industry, including a greater focus on tools for precision agriculture, and Agri Tech, the internet of things (IoT), and the use of big data to drive greater business efficiencies in the face of rising populations and climate change.

Global spending on smart, connected agricultural technologies and systems, including AI use in agriculture and machine learning, is projected to triple in revenue by 2025, reaching $15.3 billion.

IoT-enabled Agricultural (IoT Ag) monitoring is agriculture’s fastest-growing technology segment projected to reach $4.5 billion by 2025.

What is artificial intelligence?

At its simplest form, artificial intelligence is the science and engineering of making intelligent machines. Advanced algorithms are used to create expert systems that make predictions or classifications based on input data.

Using AI in agriculture

Agriculture 4.0 will no longer depend on solely applying water, fertilizers, and pesticides uniformly across entire fields. 

Instead, by using AI in agriculture, as part of Agriculture 4.0, farmers will use the minimum quantities required for production and target specific areas to produce better yields more efficiently and profitably

Farms and agricultural operations will have to run very differently, primarily due to advancements in agricultural technology such as sensors, devices, machines, and information technology. 

AI has several applications in today’s agriculture:

  • Improving crop yield prediction – using real-time sensor data and visual analytics data from drones.
  • Optimizing pesticide application – Optimize the right mix of biodegradable pesticides and limit their application to only the field areas that need treatment to reduce costs while increasing yields.
  • Price forecasting for crops based on yield rates – predict total volumes produced are invaluable in defining pricing strategies for a given crop
  • Finding irrigation leaks, optimizing irrigation systems – measuring how effective frequent crop irrigation improves yield rates are all areas AI in agriculture contributes to improving farming efficiencies.
  • Yield mapping to find patterns – using large-scale data sets for crop planning
  • Improving pest management – pioneering drone data combined with in-ground sensors to improve pest management.
  • Identifying animal or human breaches – Monitoring every crop field’s real-time video feed identifies animal or human breaches, sending an alert immediately.
  • Solving labor shortages – businesses cannot find enough employees and turn to robotics for hundreds of acres of crops while also providing an element of security around the perimeter of remote locations
  • Improving the track-and-traceability  – assisting agricultural supply chains by removing roadblocks for getting fresher safer crops to market on time and with a traceable history.
  • Monitoring livestock’s health – By monitoring vital signs, daily activity levels, and food intake, ensuring their health is one of the fastest-growing aspects of AI and machine learning in agriculture. 

Precision agricultural tools

Robotic systems and AI will allow farms to be more profitable, efficient, safe, and environmentally friendly.

Types of agricultural technology and precision agricultural tools

Future agricultural technology will use precision agricultural tools and sophisticated technologies including AI, robots, drones, the Internet of Things (IoT), temperature sensors, aerial site images, ground/soil sensors for pH and moisture levels, GPS for geo-mapping, and location.

Advanced management of these devices which all have different outputs, formats, and data types require sophisticated tools and software to integrate with vast amounts of Big Data and volumes of research information to provide useful live information to the farmer.

This is where Agmatix comes into the picture. Agmatix’s mission is to harmonize and standardize all agronomic data and turn it into actionable insights, making it universally accessible.

Agmatix digital crop advisor 2.0

Agmatix Digital Crop Advisor 2.0 is a data-driven decision support system using large amounts of available data to optimize day-to-day crop management.

As the world’s first single engine that drives the agronomic innovation cycle from research and experimental data into meaningful real-life action, the Agmatix technology creates a new data language that can read and interpret thousands of the different data points commonly used across the agricultural industry.

The unique system then provides agronomists and farmers with the vital information needed to make better crop management decisions to increase yields and crop quality. 

Our vision is a world where high-quality and standardized agronomic data is available, supporting Ag professionals globally to overcome obstacles in improving sustainable food production and quality through crop nutrition optimization.

Graphs on ipad

Disruptive technology

Agmatix’s disruptive technology collects, defines, and categorizes data from multiple sources to standardize, harmonize, and facilitate agronomic research, field trials, and a plethora of relevant data, providing the agronomist or farmer with a smart tool to facilitate precise digital agricultural growing practices.

Our Field Trial Management technology digitally manages field trials including data collection and analysis from start to finish. Agmatix’s technology platform has now digitized above 25 million agronomic measurements from over 50,000 different field trials, covering 70 different crop types with multiple geolocations (North America, south America, Europe, AIPAC) and multiple ag domains.

Agmatix is revolutionizing agricultural practices

A.I. can help mankind tackle the many challenges that await it in providing produce for an ever-growing population, in an age of natural resource shortages and global warming. 

Our innovative technology platform uses agronomy data science and advanced AI technology to convert agronomic data into actionable insights at the field level.

Agmatix’s revolutionary approach aims to solve the lack of agronomic data standardization resulting in dramatically improved agricultural practices, crop yields, and nutritional quality while promoting sustainable agriculture in an ever-hungrier world which requires 50% more food by 2050.