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    The role of sensors and data collection in a successful vertical farm

     

    It’s widely recognized that vertical farming has many advantages over traditional crop-growing methods. Simply put, despite relatively high setup and operational costs, the production per unit of growth area in vertical farms easily exceeds that in the most advanced greenhouses. But to consistently hit this level of production, you need to ensure growth conditions are continuously at their best. This is where sensors and data play a pivotal role, and why they’re ready to transform the future of vertical farming.

    What data do you need to capture?

     

    To use sensors and data effectively, you first need to know what kind of data is valuable and why. The most important values to measure are the following conditions for growth:
     

    • Climate (characterized by a combination of air temperature, humidity levels, CO2 levels and air speed)
    • Plant temperature
    • The nutrient composition of the irrigation water
    • The light level and spectrum (as perceived by the plants)
    • Plant morphology, deficiencies and growth (phenotyping)

     

    These conditions are significant for different reasons. The difference between plant temperature and air temperature, for example, can tell us whether the leaves’ stomata are open. If they aren’t, the plant cannot absorb CO2 and convert it into biomass. Likewise, we can continually measure the pH (acidity) and EC (electrical conductivity) of the irrigation water to ensure optimal plant growth. We are also cooperating with several companies that are developing sensors to measure other parameters of the irrigation water (such as f.e. iron or magnesium).
    You might be surprised to see that we measure the light level and spectrum as perceived by the plants, presuming that we can deduce this already from the type and number of LED lighting modules installed. However, our research has found that the plants’ perceived light level can deviate up to as high as a factor of two from the light level installed depending on the optical properties of the materials used between and above the plants. This value largely depends on the degree to which the plants cover the growth area, and with such a high potential deviation rate, is one we need to measure and track to ensure optimal growth conditions.

     

    The value of monitoring every stage of the growth process

     

    Sensors enable us to monitor these growth conditions, recognize anomalies and identify problems as early as possible. By detecting problems at an early stage, we can respond pro-actively instead of reactively. This holds especially true for system-related problems – such as the temperature deviating from an intended setpoint – which can be rectified almost immediately.

    In addition to measuring growth conditions, measuring growth results also provides valuable data – using parameters such as plant size, height, weight and color. We can use cameras to capture images of the plants in the growth layer, for example, following growth development over time and gauging whether growth meets expectations or not by comparing it to data captured in previous growth cycles under similar conditions. Like sensors, cameras can also help to prevent problems early by enabling the detection of early-stage growth deficiencies (such as tip-burn) and diseases.

     

    How our sensor and data platform can help

     

    Our sensor platform allows us to measure the conditions most important for plant growth. These conditions include climate parameters and irrigation parameters (including water supplied/drained in addition to pH and EC). At the GrowWise Center in Eindhoven’s High Tech Campus (HTC), we collect about 1,600 unique setpoint and sensor readings every ten minutes from our eight climate cells – valuable ongoing research that helps us to continuously build on our knowledge base and improve the solutions we can offer.

    The sensors can be placed anywhere within a growth layer and wirelessly communicate the data they gather to the system backend. Cloud applications then retrieve this data and visualize the information that is most relevant and useful to plant specialists and growers. The development of the sensor platform is part of Horizon 2020 Internet of Food (H2020 IoF), a European Commission (EC) innovation project, in which we are closely collaborating with Staay Food Group.

    Succesful vertical farm

     

    The future of vertical farming

     

    The benefits of modern sensor technology and data science are already manifold, but technological advancements in areas such as AI promise to be truly revolutionary. Signify is currently researching AI-based algorithms that can train models to couple realized growth conditions with realized growth results, for example, in a process known as ‘supervised learning’. This will ultimately enable us to predict the precise growth conditions to achieve optimal growth – and meet the most specific grower needs. AI techniques like machine learning can also be used to analyze images of plants’ growth to immediately detect any unexpected deviations or growth deficiencies.

     

    Right now, our sensor and data platform combined with cloud applications adds considerable value for our plant specialists and customers – from monitoring the growth process and detecting problems as early as possible to accelerating the development of new optimized growth recipes. It’s clear that sensors and the data they capture play a pivotal role in the continuing evolution of vertical farms. Signify and our customers will not just be a part of this revolution – we will drive it.

    Marcel Krijn hi res FvBeek
    Dr. Marcel Krijn is a principal research scientist at Signify and has over ten years of experience in horticulture. His primary interest is the advancement of vertical farming as a mainstream method of food production that is both energy-efficient and commercially beneficial for Signify’s customers. His research efforts also focus on the development of new options for data-driven growth management. 

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