You can’t get something from nothing, but we can achieve more with less in AgriTech…
A growing concern
Food and Agriculture Organisation’s (FAO) Food security Report from 2020 depicts a rather bleak picture for our food systems. Roughly 690 million people (8.9% of the world’s population) are currently severely hungry - an increase of 60 million since 2015 - while in 2019 an estimated 2 billion did not have access to safe and nutritious food.
The climate crisis is one of the main culprits, with extreme conditions and the associated worsened effects of pests playing an important role in limiting yields. Population growth is also to blame, with high growth rate areas being the most affected, especially when in conjunction with poor access to healthcare and education.
Unfortunately, traditional agriculture has not been keeping up with the challenge, and current predictions suggest we will miss the 2030 Zero Hunger target agreed by the World Health Assembly.
Increased pressure to ramp up production with the same resources has led to agricultural practices that contribute considerably to greenhouse gas emissions (GHG); manufacture of fertilisers and fuel; land conversion and deforestation; and water pollution.
The light… inside the tunnel
Controlled Environment Agriculture (CEA) is an excellent solution to these challenges, mainly because it reduces reliance on environmental factors and land use. These features allow CEA to overcome seasonality issues; be resilient to catastrophic events; repurpose agricultural land; and allow local food production.
As currently implemented, CEA does however suffer from a few significant limitations, especially in Vertical Farming (VF).
Firstly, its environmental impact is still very high, due mostly to its extreme energy needs. For example, a recent estimate suggests that a conventional VF container connected to the energy grid produces 8.24 Kg of CO2 per Kg of leafy green biomass (Calculating the carbon footprint of vertical farming and traditional farming, Agritecture, 18 February 2021)
Secondly, VFs are often still reliant on manual labour to monitor crops, mostly to assess plant development and detect early signs of stress or disease. Apart from increasing costs and reducing the surface available for growing crops, human labour also acts as a vector for insects and fungal pathogens, increasing the risks associated to running a VF.
Finally, the crop range that is achievable with these systems is still limited. The vast majority of farms focus on micro-greens and herbs, which are unlikely to replace staple starchy crops. This is at least in part due to the high Capex and Opex costs currently associated with VFs, which limit the crops that allow farmers to achieve profitability.
What we stand for
At Gardin, we believe that a smarter approach is needed. We can provide the tools to empower growers globally to produce more, higher quality, nutritional food, while reducing inputs, for the benefit of all.
Agronomical practices have for too long been resistant to change. Operations such as manual measurements, visual inspection, or One Factor at a Time experimentation are still prevalent, reducing the quality of the data we obtain and limiting our understanding of an extremely complex system.
We plan to change this with a coordinated multi-level approach:
- Provide novel sensing technology at scale - Technologies such as thermal and hyperspectral imaging are powerful tools, but they struggle to penetrate the market due to their complexity and high costs. We don’t like that and plan to change it through our custom sensors.
- Generate high-quality signal - General purpose sensors often compromise on data quality. Each of our sensors is developed for a specific application so that we can get the best signal-to-noise ratios, because seeing patterns is easier that way.
- Focus on real-world, real-time data - There is no better place to learn how to tackle actual problems than from expert growers. We implement a cloud-based data strategy and strive for close collaboration with all of our partners. This way we can maximise synergy and make information ready for access, wherever people are.
- Employ Design of Experiments (DOE) - Plants are complex and plastic entities, constantly sensing and responding to their environment. We appreciate this and believe that true optimisation will come from understanding the complex interaction between the many components at play. This is why DoE is at the core of everything we do.
- Capture relevant metadata - Learning from complex data is all about context and we want to make sure we capture what is important. Recording information about plant provenance, environmental conditions and production processes, we build better models and unveil previously inaccessible causal links.
- Leverage diverse backgrounds - Our team is highly multidisciplinary, including experienced professionals in optics, embedded systems, electronics, computer vision and plant science with a wide range of expertise in analytical and visualisation techniques from our respective fields. We love looking at data, discussing best analytical approaches, and learning from each other!
- Build a single ecosystem - The multiplication of tools and fragmentation of work often brought about by digitalisation campaigns adds unnecessary complexity to everyday tasks. This ultimately acts as a barrier to the adoption of disruptive technology. We want to make sure growers have a single place to go to for insight, not confusion.
This strategy allows us and our partners to optimise resource usage and get the best performance from our crops, so that we can reduce the environmental footprint of CEA agriculture, increase profitability, and expand the range of crops we can successfully grow indoors.
Growing food from our natural resources and generating insight from data have something in common. Just as biomass is made of inputs like CO₂, water and minerals; insights and understanding are made of quality data.
At Gardin we develop disruptive technology to probe plant physiology in real-time, in remote and non-destructively. Our focus is to get more and higher quality data, so that we can model plant behaviour better and revolutionise how food is produced globally.
You can’t get something from nothing. Countless physics classes have taught us that. But we believe that current AgriTech practices offer ample space for improvement — to get more with less — by weaving clever and well communicated statistics into everyday decision making.