Editor’s Note: This post was originally published in April 2023 and has been updated for accuracy and comprehensiveness.
Lately, the food system has found itself under considerable pressure. Amid a growing population, demand for nature recovery programs, and lack of resources, farmers worldwide have to mitigate crisis after crisis while providing high-quality produce.
The intensity made connectivity, sustainability, and resilience new must-have elements of modern farming, prompting agricultural enterprises to explore digital solutions capable of adopting their workflow and supply chains to those new needs.
In this article, we’ll explore top AgTech trends that define the future of sustainable farming and allow for the building of revolutionary connectivity for the agriculture industry.
Connected farming: definition and value
With the Fifth Industrial Revolution on the rise, sustainability became the industries’ answer to uncertainty and instability of the economic landscape. Instead of prioritizing profit and making the most out of present opportunities, sustainable businesses choose to be more future-oriented, embracing waste minimization, eco-friendly energy sources, preservation of biodiversity, and measures against water pollution.
Accordingly, sustainable farming is farming with tools for identifying and preventing negative ecological effects, while maintaining a stable and thriving food system.
Such measures are essential for complying with nature recovery requirements and laying the foundation for long-term, high-quality food production in a controlled, safe, and stabilized environment. The more conscious and future-proof perspective on resource management and crop-growing methods enables organizations practicing sustainable farming to ensure that by making more with less. Additionally, they contribute to building a healthier and more available food system that can be built upon and improved by the next generations of farmers.
Naturally, such an ambition requires tighter control on the state of crops, weather, harvesting window, and the health of cattle—which is why sustainable farming goes hand in hand with connected agriculture.
Agriculture industry trends that make connected farming relevant
As businesses and sectors prepare for next year's challenges, it makes sense to dive into the top-of-mind concerns and needs of farmers and agriculture employees to understand where the demand for sustainable agriculture and farming practices stems from.
- Farm stress is real
According to a recent study, the constant onslaught of farming issues has led to farmers being under intense mental stress. Health problems, risk of injury, financial problems, and external factors made farmers vulnerable to stress. The depth of this vulnerability is so severe that failing to produce a proper harvest can deteriorate farmers' mental health and end in self-harm. The amount of stressors is too much to handle—so exploring current trends in agriculture technology is crucial for preserving farmers' well-being and creating a safer and friendlier environment. - Production expenses are soaring
Speaking of less-than-positive market trends in agriculture contributing to farm stress, net farm income is expected to see a 15.9% decrease in 2023. Such a fall in profit is caused by the continuous impact of external factors, such as the pandemic and war in Ukraine, on the production costs of market volatility. As these expenses threaten to take away a chunk of potential profits, farmers take a deeper dive into sustainable agriculture trends to optimize their resource consumption, and investments and find alternatives that will help them cut costs in the long run. - Preparing for the feast-or-famine production cycle
In addition to adapting to global social and economic changes, farmers continuously stay aware of climate change, which dictates their approach to farming. As a report by FAO predicts an El Niño event (a complicated weather phenomenon connected to the warming of the oceans), farmers need to prepare for periods of drought and dry weather, adjusting their approaches to irrigation and crop monitoring.
These significant challenges will be relevant in the upcoming years, highlighting the importance of researching recent trends in agriculture technology and exploring the opportunities for applying them to farming strategies. The purpose of connected farming is dedicated to combining the most valuable innovations with long-term experience and insights of farmers willing to do their best to support the global food system.
Future trends in agriculture technology: how they contribute to connected farming?
As modern challenges require new solutions, the digital farming market continues to grow. Projected to reach $56.8 billion by 2030, it keeps introducing new opportunities for building a solid and robust connected farming ecosystem where farmers can tackle their top-of-mind concerns and gain more control over external factors that affect their harvest.
Among these technologies, there are several new additions worth mentioning:
- Digital twins for informed decision-making
The digital twin technology has made it to the list of fastest-growing trends in agriculture and beyond. A combination of IoT, data analytics, and ML, a digital twin serves as a virtual copy of a physical object, which, in the case of farming and agriculture business, can be a replication of crops, machinery, or even climate.
Climate models
Using real-time and historical data to evaluate weather patterns and predict crop response to various changes allows farmers to adapt to potential risks.
Crop models
Replicating plant behavior, growth patterns, and nutrition, providing more accurate data for irrigation, fertilization, and monitoring strategies.
Machinery models
Facilitating maintenance of agriculture machinery by providing real-time data on their state and performance, letting farmers timely run maintenance and know when to invest in replacement.
Soil models
Collecting data on soil properties to create a virtual soil model that can be monitored and used to test various farming strategies.
Currently, digital twins are being implemented by farmers across the United States and Europe, with users finding more and more applications for the technology in the context of accurate field management and equipment maintenance. With the digital twin solutions market size reaching $11.13 billion in 2022 and estimated to have a 37.5% compound annual growth rate by 2030, agriculture businesses are expected to reveal new opportunities for resource optimization and building a stable connected farming framework.
- Paving the way toward on-farm automation
Given such issues as workforce shortage and farmer aging, it's unsurprising that robotics and automated environments dominate agtech trends. While self-steering vehicles and harvesting robots remain a novelty adopted by individual agricultural businesses, AI-driven drones went from an interesting concept to one of the most popular trends in agriculture. In total, the value of drones for agriculture is expected to grow up to $8.8 billion by 2029, which is a clear sign that drone technology isn’t merely a fleeting trend, but a solution to numerous farming challenges, such as:
Pest control
Using AI algorithms to recognize potential crop threats (diseases, vermin, harmful insects) and timely notify farmers.
Irrigation optimization
Collecting data on soil moisture and sending it over to farmers, enabling them to adjust their irrigation routine.
Crop health monitoring
Gathering information on crop growth and key metrics that define crop health, thus relieving farmers from taking measurements manually.
In addition to drones, simpler technologies contribute to facilitating farming activities and compensating for the shortage of workers.
For example, automation farming software enables farmers to monitor the health and state of their livestock through apps. These apps assist with monitoring Veterinary Feed Directive requirements, receiving updates on the new regulations, and generating reports on livestock behavior and welfare. Intelligent automation can also be applied to business operations, regularly updating farm managers on stock prices and workers' status—which generally enhances labor conditions and lets farms manage their human resources more efficiently.
Such versatility and functionality made automation one of the most productive sustainable agriculture trends as it significantly reduces manual control over agricultural data systems, gathering, cleansing, and validating important data. As a result, farmers become able to see the bigger picture and explore every aspect of their facility in greater detail. With greater clarity comes a greater understanding of resource allocation and process optimization, which is the end goal of connected farming.
- ML-empowered crop management
Crop management is a multi-layered, multi-stage process requiring vast knowledge and experience to gain the best yields possible. The lack of crop knowledge at any stage (pre-harvesting, harvesting, and post-harvesting) may result in a crop failure, i.e., compromise all farmers' efforts throughout the season. For that reason, machine learning became one of the most impactful trends in agriculture, as it allowed farmers to harness data analysis and deep learning, eliminating the lack of knowledge and mitigating the risks.
Through ML models collecting data on crop state, weather, and soil, farmers can receive accurate suggestions on their next actions, such as the choice of pesticide or even a fitting crop type. Additionally, farmers can identify the most profitable crops to invest in via ML-based price and demand forecasting, thus being able to calculate their budget and inventory in advance.
- AI-based automation for livestock management
Having secured its place among top agriculture trends, AI remains the game-changer that makes a significant difference in all high-value areas. In the case of agriculture and farming, AI provided viable options for handling livestock.
Livestock management involves monitoring the health and welfare of each animal in the herd since its birth. Traditionally, farmers and workers had to manually create and keep records of health history, age, habits, and reproduction history—which is quite a tedious process, far immune to the cases of human error, data discrepancies, and other issues.
The introduction of AI-powered livestock management systems and apps enables farmers to automate recordkeeping, organize all information about each farm animal, and constantly enrich the database with new details. Therefore, farmers have an understanding of livestock well-being and can get relevant data about any animal by scanning its identification tag.
- Farm management software for labor organization
The usefulness of ERP systems isn't limited to the BFSI sector exclusively—farming and agriculture businesses benefit extremely from the ERP software's functionality, resulting in rapid farm management software market growth (expected to increase its CAGR by 11.9% by 2028).
The use of farm management software allows farmers to insert more efficiency into their activities and take them to an entirely new level of management.
Employee activity tracking
Farm managers fully see employees' schedules, rotation, and tasks. Meanwhile, employees can view reports and work-related data and send notifications.
Crop planning
With the help of a system that analyzes data on farming activities and crop results, farmers can make more informed decisions regarding crop rotation, fertilizers, approach, and pest control.
Inventory management
Farm managers see accurate numbers on their stock of fuel, pesticides, fertilizers, fuel, and farming equipment. It allows them to calculate how much inventory they need to buy to prepare for the next season.
Profit measuring
With their financial data in front of them, farmers get more control over their expenses and financial activities. Therefore, they can calculate their profits and see areas for improvement or opportunities to cut expenses.
Effectively connecting farmers to the activities within their fields, farm management software became a game-changer for agriculture businesses aiming to adapt to modern challenges and shift their operations towards sustainable farming.
- Blockchain for supply chains traceability
Agriculture supply chains are often a chaotic environment with complicated traceability. The presence of several stakeholders creates additional challenges for quality standard compliance validation, verification of yield monitoring, and crop growth phase requirements, affecting the pace of business operations.
Implementing blockchain technology into connected farming seeks to overcome these challenges and facilitate standard compliance, requirements monitoring, and traceability.
In practice, blockchain-based supply chains imply creating a transparent and immutable data storage for farmers, where all the data on crops and produce journeys is stored within one decentralized data chain. At the same time, transactions are handled with smart contracts. Within such an architecture, all stakeholders have permission-based access to the digital ledger, keeping an eye on operations and resting assured that all conditions are met, and all practices are implemented.
- Cloud computing for connected farming
One of the main obstacles between agriculture and digital transformation was the necessity to invest in large mainframes for storing agricultural data. However, cloud technology allows bypassing this obstacle and storing massive amounts of crop, livestock, and price and sales data within cloud-based platforms.
In addition, cloud computing solutions for connected farming allow farmers and workers to access important data from any place via mobile apps, thus untethering them from stationary workplaces and letting them combine data analysis and research with their farming activities.
Imbuing smart farming with cloud technology also helps improve communication between fields and facilities as workers can exchange information faster, improving decision-making and issue identification. Another significant benefit of cloud AgTech solutions is that they potentially enable farmers to connect with buyers directly, eliminating the need for middlemen in trading. By providing public access to data on crops and farm livestock, farmers offer greater visibility for their produce, attracting buyers and increasing their sales rate.
What does the future of connected farming look like?
With all the examples of AgTech solutions listed above, it's important to see what the numbers say regarding implementing technologies for connected farming.
- 2,400 million USD—the estimated price of the AI AgTech solutions market in 2026
- 41% surge in CAGR is expected for the blockchain agriculture solutions market by 2029
- 11.9% CAGR growth projected for the farm management software market in 2028
Although many AgTech digital solutions are still new to the agricultural market, farmers and workers from large-scale to medium-sized facilities promptly realize the value behind connected farming and sustainable agriculture.
For example, a cloud-based solution built on AWS allowed around 5,000 clients across 50 countries to achieve 50% water savings and 20% yield improvement—which now enables developers to update their technology with data on crop diseases and other valuable information from agricultural research, increasing its value to farmers.
These numbers and positive shifts brought by sustainable farming would undoubtedly contribute to the expansion of connected agriculture as more and more farmers will be prompted to invest in adopting existing agricultural technologies and encourage the development of new ones.
Our teams of cloud and automation professionals, data scientists, and blockchain developers are proud to contribute to the emergence of AgTech innovations by offering our expertise to farming entrepreneurs who wish to boost their productivity through connected farming.
So, if you’re looking for solutions that would upgrade your agriculture operations and grant you full traceability of your activities—let’s chat. We will ensure your facilities' smooth and successful transition to sustainability, resilience, and increased productivity.
