Researchers have developed a way to study and track the internal communication of living plants using carbon nanotube sensors that can be embedded in plant leaves. The sensors can report on plants’ signaling waves to reveal how they respond to stresses such as injury, infection, heat, and light damage, providing valuable real-time insights for engineering plants to maximize crop yield.

The nanobionic approach uses sensors to intercept the hydrogen peroxide signals that plants use to communicate internally and displays the data on remote electronic devices such as cellphones, allowing agricultural scientists to remotely keep track of plant health in real time. The technology can provide much-needed data to inform a range of agricultural applications such as screening different species of plants for their ability to resist mechanical damage, light, heat, and other forms of stress, or study how different species respond to pathogens. It can also be used to study how plants respond to different growing conditions in urban farms.

Plants that grow at high density are prone to shade avoidance, where they divert resources into growing taller instead of putting energy into producing crops, lowering overall crop yield. The sensors intercept that stress signal to understand the conditions and the mechanism happening upstream and downstream in the plant that give rise to the shade avoidance, thus leading to fuller crops.

Traditionally, molecular biology research has been limited to only specific plants that are amenable to genetic manipulation but the new technology can potentially be applied to any plant. The team used a method called lipid exchange envelope penetration (LEEP) to incorporate the sensors into plant leaves.

The release of hydrogen peroxide triggers calcium release among adjacent plant cells, stimulating them to release more hydrogen peroxide and creating a wave of distress signals along the leaf. The wave of hydrogen peroxide stimulates plants to produce secondary metabolites that can help repair damage.

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