2023 was a challenging and rewarding year in agriculture.
The global industry continued to focus on adapting to extreme weather events while overcoming supply chain issues with inputs like fertilizers. As part of the wider impetus to feed the world’s growing population, agronomic researchers and engineering teams worked to develop smart Agtech tools and technologies that address the efficiency and productivity of production agriculture.
The latest agronomic products and technologies are fueling the urgent transition towards economically viable sustainable agriculture. Major trends in agriculture in 2024 are expected to build on many of the important themes in 2023, with an increased emphasis on generative artificial intelligence (Gen AI), digital twins, and regenerative agriculture.
The Internet of Things, open databases, and cloud technology are helping turn big data into a useful – and accessible – tool – for creating groundbreaking agronomic solutions. These include digital crop monitoring tools, agriculture data enrichment, field data software, and other advanced crop modeling solutions.
These technologies are anticipated AgTech trends in 2024, as agronomists, researchers, and data scientists harness emerging technologies for use across the entire agriculture value chain. AgTech is a rapidly expanding market and agroinformatics trends top the list of important new developments in the high-tech space. The coming year is expected to create exciting opportunities for innovation in the AgTech industry.
1: Generative Artificial Intelligence in AgTech
Of all the 2024 trends in digital agriculture, the role played by Gen AI, or generative AI, is likely to be one of the most significant. The potential of Gen AI on the global general economy is already being calculated in trillions of dollars. There is a historic opportunity to improve productivity, eliminate waste and inefficiency, and even open new markets. AI may eventually account for 75% of the value of customer operations, marketing and sales, software engineering, and research and development.
Every aspect of the food industry, from the various agricultural sectors to the diverse food production and distribution components to food retail and recycling, Gen AI is expected to bring major productivity enhancements. Across the industry, Gen AI is anticipated to optimize processes, cut costs, and importantly, fuel innovations through creating new simulations and efficient code.
In agriculture, Gen AI can enhance crop management by optimizing production practices through the analysis of big agronomic data. With AI-supported insights, companies and agronomists can support farmers in adopting precise management techniques and understanding patterns that could influence the performance of crop varieties and production practices on their specific farms. Gen AI can be used to track climate trends and even help farmers become more resilient to the changing climate.
Agmatix is already developing new agronomic products that use Gen AI and will be at the forefront of Agtech trends in 2024. The Agmatix team leads the industry in using artificial intelligence to harness the potential of big data, develop insights and models to fuel decision-making and produce agronomist and industry-friendly tools to enable sustainable agriculture.
With this track record of innovation, Agmatix is confidently leading the way towards increasing the use of GenAI in agriculture. The Digital Crop Advisor tool is one example of how Gen AI is already helping agronomists distill agronomic data into effective management recommendations for farmers. Backed by big data, Gen AI, and a desire to support farmers in producing more sustainable crops, Digital Crop Advisor is a key tool for enhancing sustainable crop productivity.
2: Utilizing Digital Twins to Optimize Field Trials
A digital twin is a digital model or a virtual representation of an actual physical product (or a system or process). A perfectly accurate digital twin allows researchers and designers to experiment with the model as though they were handling its physical counterpart. Users can leverage real-time or historical data inputs – or a combination of the two (e.g. the Internet of Things and sensor data).
A significant advantage of digital twins is that they can often be created before the physical product. This transforms the possibilities of typically expensive and time consuming field trials. One AgTech application for digital twins is the development of (virtual) complex systems, utilizing a mass of data. This type of modeling would simply have been impractical even a few years ago. The further integration of digital twins into field tests and field test planning is likely to be one most interesting 2024 trends in digital agriculture.
Agmatix CEO Ron Baruchi explains the role of synthetic data field trials and how it can be leveraged to enhance the performance of digital twins.
“Generating real-world data is an expensive, time-consuming process. It typically takes more than 150 studies to register a new active ingredient.
From 2010-14, it cost around $286 million to discover and develop a new crop protection product.
$47 million (approximately 16%) was budgeted for field trials.
It takes just over 11 years from the first synthesis to the first sale of a crop protection product.
Synthetic data is based on real-world data that has been generated by a model that keeps the same statistical properties and connections between the different parameters of real-world data sets. Datasets can be fully synthetic, or partially synthetic, where synthetic data helps fill in any gaps in real-world data.
Synthetic data is not a replacement for original data, but a secondary source—one that can significantly reduce the time, cost, and effort in obtaining original data. Which offers great potential in reducing the time and investment of bringing new agricultural products to market.
Synthetic data can also be used for R&D purposes. Scientists can create a “digital twin,” in which a computer takes real-world data to maintain its statistical correlations, and generates synthetic data to create a system that emulates real life.
In agriculture, you could create a digital twin of a field trial to test which variables, such as soil types and weather conditions, are necessary for a successful real-world field trial. This has huge implications for agricultural input suppliers like crop protection companies, who are required to manage large field trials to receive regulatory approval, or seed companies that rely heavily on experimentation to improve their seed genetics.
Digital twins can also be used to fill in data gaps from real-world sets. If an equipment error or a remote sensor fails and data is missing, you can generate synthetic data based on statistical models to fill in those holes and provide a complete picture of the study. Or if data is missing in certain geographic locations due to a lack of research facilities, synthetic data can help fill in those absent areas.”
In agriculture, Digital Twins have the power to increase efficiencies in the development and validation processes for new innovations. With increased efficiency, efficacy, and safety, using Digital Twins for field trials can be a competitive advantage in the race to market.
Agmatix software is designed to help companies overcome challenges related to using traditional field trials alone through advanced technologies like Digital Twins. With the end-to-end Agronomic Trial Management solution supporting organizations to plan, execute, and govern their agronomic field trials, companies can easily adopt advanced technology into their processes and reap the benefits of faster, more effective field trials.
3 Technical Innovation in Regenerative Agriculture
Trends in agriculture in 2024 will include greater technical innovation and research into regenerative agriculture. The essence of regenerative agriculture is mimicking natural processes and biodiversity (within a managed plan) on agricultural land. It encompasses a holistic approach to preventing and reversing soil erosion and improving soil health.
Regenerative agriculture uses tailored hybrid solutions that can include adaptive grazing, the incorporation of cover crops, forage crops, and perennial grasses to vulnerable areas, along with a no-till planting plan, data-based fertilizer strategies, and an ecologically friendly approach to pesticide use. As we face the challenges of climate change, and the requirement to feed a world population of over 8 billion people, regenerative agriculture has never been more vital.
The availability of accurate and up-to-date data enables the development of localized regenerative agriculture solutions that are tailored to soil conditions, weather conditions, and microclimates, current crop growth or land use, as well as individual budgets and local regulations.
Agmatix is dedicated to fostering the widespread adoption of regenerative agriculture practices through rapid and effective means. Utilizing site-specific data, the Agmatix platform offers a holistic view of sustainability that extends well beyond simple carbon metrics and one-size-fits-all solutions. This approach encompasses a range of elements, including soil health, crop protection, and the efficiency of nutrients and irrigation, among others. By setting site-specific benchmarks, the platform enables the establishment of realistic, actionable objectives for growers, promoting scalable sustainability and formulating strategies tailored to local environments.
Furthermore, Agmatix’s commitment to regenerative agriculture shines through its platform. It offers accurate, user-friendly tools for creating crop nutrition plans centered on sustainability. This empowers agronomists with resources to guide growers in adopting regenerative practices, which not only benefit the environment but also enhance productivity.
4 Managing Data with Advanced Cloud Solutions
Innovation in agriculture is often data-dependent and the cloud gives researchers the ability to collate, manage, and extrapolate information from data in a way that was simply unimaginable for previous generations of agronomists. According to IDC, agriculture is growing exponentially year over year, and it is estimated that by 2036 the amount of data collected on the farm will increase by more than 800%. An agriculture field trial data tool that utilizes secure cloud systems can give a range of stakeholders real-time access to relevant information that is harvested from a mass of data. Trial durations are reduced, costs are cut, and the volume and scope of trials can be increased.
Cloud technology can be applied to every aspect of agriculture and food production, including crop management, crucial soil information, monitoring and analyzing crop growth over multiple seasons, planning new agricultural ventures, and leveraging local knowledge for decision-making. Cloud-based solutions enhance researchers’, agronomists’, and farmers’ abilities to collaborate and make real-time data-based decisions.
Agmatix software is cloud-based to enable maximum efficiency, security, and collaboration. This game-changing technology has been key to Agmatix developing solutions for trial management and crop nutrition management that can be used in-season for time-sensitive decisions.
For research and development companies, cloud-based technologies enable a complete overhaul of legacy processes to unlock new, efficient ways of conducting business. Cloud-based technology is cost-effective; reduces overhead, doesn’t require massive IT teams or hardware storage space, and it’s scalable to meet business needs. It also provides new ways of doing business, through easy collaboration with external stakeholders and automatic access to data that’s needed to make important decisions in the research and development process.
5 Innovation Across the Agricultural Spectrum
Agriculture has roots in innovation. In fact, shifting away from a hunter-gatherer lifestyle to an agrarian one was an innovation in and of itself! The earliest farmers were instinctive researchers and scientists who, through trial and error and observation, succeeded in producing a surplus of crops and ensuring the survival of each succeeding generation.
Past innovations in agriculture were essentially practical and began with selective breeding, the use of fertilizers, the development of water collection and irrigation systems, primitive pest control methods, pollination techniques, and various food preservation and production techniques. As agriculture progressed, farmers adopted crop rotation, and the Industrial Revolution led to innovations like seed drills and steam-powered farm vehicles.
The new technological revolution, combined with the shift towards sustainability and environmental protection has brought us to the threshold of what will likely be the fastest, most intense, and most transformative period of agricultural innovation in human history. Innovative trends in agriculture in 2024 will include progress in the development of hardy crop strains that can thrive as the climate changes, the identification and adoption of nutrient-dense ‘superfoods’, and a shift towards specialized agriculture in non-rural settings.
Innovation at the farm level is poised for impact, too. Armed with digital technologies, farmers can improve the processing and use of the data they collect on the farm. Agtech solutions can help farmers and agronomists measure and demonstrate the real-life return on investment and value of agriculture technologies.
As we face the pressures of climate change, challenging geopolitical events, and sustained population growth, the most important Agtech trends in 2024 will be those that increase innovation and shorten the time to market for game-changing new products. Companies that can plan flawless field trials with shorter durations, and deal proactively with regulatory and compliance requirements, will have a definite competitive advantage. McKinsey notes that technology can increase productivity which directly impacts the bottom line, saving 10 to 15% percent of overall research and development costs through tools like generative AI.
