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A multidisciplinary team from the National University of Singapore (NUS) has made significant strides in precision farming with the creation of an innovative plant e-skin sensor system paired with a digital-twin monitoring platform. This cutting-edge technology provides farmers with real-time, non-invasive monitoring of plant health, optimising crop yields and enabling swift responses to environmental changes.
By seamlessly integrating data collection and visualisation, the system represents a breakthrough in crop management, offering new possibilities for decision-making in both crop breeding and precision farming.
Precision farming, which relies on sensors to monitor factors like temperature, humidity, moisture, and nutrient levels, is becoming essential for maximising agricultural productivity. However, traditional plant sensors are often bulky, rigid, and prone to damaging the plants they are designed to monitor.
To address these challenges, the NUS team, led by Associate Professor Chengkuo Lee and Assistant Professor Eunyoung Chae, developed the first all-organic, ultrathin plant e-skin. This sensor system collects continuous data on plant conditions while being light, flexible, and biocompatible, ensuring no harm to the plants.
The e-skin is composed of an electrically conductive layer sandwiched between two transparent substrates, allowing more than 85% of light to pass through—crucial for photosynthesis. Measuring just 4.5 micrometres thick (about 10 times thinner than a human hair), the e-skin adheres seamlessly to plant leaves without impeding their natural processes.
Its design allows it to monitor key factors such as temperature and strain, making it highly adaptable to various plant species and environmental conditions, including high heat and rainfall. This innovation was published in Science Advances in February 2024, showcasing the successful development and testing of the e-skin under stress conditions.
Unlike rigid, opaque commercial sensors, the NUS plant e-skin is transparent and stretchable, allowing for precise, continuous data collection without harming plant growth. Its versatility makes it suitable for various plant types and agricultural environments.
The e-skin integrates two types of sensors: a strain sensor for monitoring growth patterns and a temperature sensor for assessing the surface temperature of plant leaves. In testing, the strain sensor successfully monitored the growth of Field Mustard leaves, conforming to the delicate leaf surface without causing any observable damage.
The temperature sensor, a key feature of the e-skin, allows for the non-invasive measurement of leaf surface temperatures. This capability is not commonly found in conventional sensors and provides valuable insights into managing heat stress, a growing concern for crops exposed to long-term heat.
The data collected by the plant e-skin feeds into the accompanying digital twin platform, which visualises the plant’s physical state in real-time. Using the collected sensor data, the digital twin creates a virtual representation of the plant, enabling farmers to monitor and adjust conditions such as temperature fluctuations.
For example, in tests, temperature changes on the plant’s surface were instantly reflected by colour changes on the digital twin, allowing for rapid interpretation and intervention. This system has the potential to optimise controlled environments, such as indoor farms, where temperature and humidity levels need constant regulation.
The NUS team sees great potential in expanding the digital-twin platform for broader applications. While the current system monitors temperature, the team is working on integrating additional sensors for humidity and chemical analysis. By coupling these sensors with the digital twin, the platform will enable even more comprehensive monitoring, further enhancing decision-making in precision farming.
Looking ahead, this combined plant e-skin and digital-twin technology could revolutionise agriculture by providing farmers with the tools to make timely, data-driven decisions. With the ability to continuously and non-invasively monitor plant health under various environmental conditions, the system offers the potential to accelerate crop breeding processes and improve yields, contributing to more sustainable farming practices.
