Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Plant Sciences, TOMATO LYCOPERSICON-ESCULENTUM, LIGHT INTERCEPTION, ARABIDOPSIS-THALIANA, WATER RELATIONS, 1-AMINOCYCLOPROPANE-1-CARBOXYLIC ACID, ETHYLENE SENSITIVITY, PHENOTYPING SYSTEM, HYPONASTIC GROWTH, CIRCADIAN CLOCK, SHADE-AVOIDANCE, Circadian Clocks, Crops, Agricultural, Digital Technology, Lactuca, Solanum lycopersicum, Movement, Musa, Plant Leaves, Stress, Physiological, Zea mays, C14/18/056#54689091, 11C4319N|11C4321N#54318221, G092419N#54969809, 06 Biological Sciences, 07 Agricultural and Veterinary Sciences, Plant Biology & Botany, 3108 Plant biology

Abstract:

Plant and plant organ movements are the result of a complex integration of endogenous growth and developmental responses, partially controlled by the circadian clock, and external environmental cues. Monitoring of plant motion is typically done by image-based phenotyping techniques with the aid of computer vision algorithms. Here we present a method to measure leaf movements using a digital inertial measurement unit (IMU) sensor. The lightweight sensor is easily attachable to a leaf or plant organ and records angular traits in real-time for two dimensions (pitch and roll) with high resolution (measured sensor oscillations of 0.36 ± 0.53° for pitch and 0.50 ± 0.65° for roll). We were able to record simple movements such as petiole bending, as well as complex lamina motions, in several crops, ranging from tomato to banana. We also assessed growth responses in terms of lettuce rosette expansion and maize seedling stem movements. The IMU sensors are capable of detecting small changes of nutations (i.e. bending movements) in leaves of different ages and in different plant species. In addition, the sensor system can also monitor stress-induced leaf movements. We observed that unfavorable environmental conditions evoke certain leaf movements, such as drastic epinastic responses, as well as subtle fading of the amplitude of nutations. In summary, the presented digital sensor system enables continuous detection of a variety of leaf motions with high precision, and is a low-cost tool in the field of plant phenotyping, with potential applications in early stress detection.