Stressed plants show altered phenotypes, including changes in color, smell, and shape. Yet, airborne sounds emitted by stressed plants have not been investigated before. Here we show that stressed plants emit airborne sounds that can be recorded from a distance and classified. We recorded ultrasonic sounds emitted by tomato and tobacco plants inside an acoustic chamber, and in a greenhouse, while monitoring the plant’s physiological parameters. We developed machine learning models that succeeded in identifying the condition of the plants, including dehydration level and injury, based solely on the emitted sounds. These informative sounds may also be detectable by other organisms. This work opens avenues for understanding plants and their interactions with the environment and may have significant impact on agriculture.

受胁迫的植物表现出表型的改变，包括颜色、气味和形状的变化。然而，此前尚未对受压植物发出的空气声音进行过研究。在这里，我们展示了受到压力的植物会发出空气传播的声音，这些声音可以从远处记录并分类。我们在声学室和温室中记录了番茄和烟草植物发出的超声波，同时监测植物的生理参数。我们开发了机器学习模型，仅根据发出的声音就成功识别了植物的状况，包括脱水程度和损伤程度。这些信息丰富的声音也可能被其他生物体检测到。这项工作为了解植物及其与环境的相互作用开辟了途径，并可能对农业产生重大影响。