Diagnosis of potassium nutrition level in Solanum lycopersicum based on electrical impedance

• Online and rapid diagnosis and detection of K nutrition level in plant are important.
• Present a novel diagnosis and detection method of K nutrition level based on EIS.
• Equivalent circuit model is built and two characteristic frequencies are selected.
• Relation between K-content and impedance are analysed by PCA and stepwise regression.
• Efficiency and potential are validated by experiments.

Potassium (K) is an essential element for crop growth. Tomato has a long growth cycle and large fertiliser requirement; thus, K stress often occurs and degrades crop yield and quality. It is the most suitable method to provide nutrition based on the actual requirement of crop growth. An accurate monitoring and diagnosis of nutrition during crop growth is key to realise a precise nutrient management. Crop K monitoring methods have been developed to improve K fertiliser management, and most of them are based on leaf or canopy optical property measurements. However, sensitivity to environmental interference remains an important drawback of these methods. Electrical impedance has been applied to determine the physiological and nutritional status of plant tissues, but no studies related to plant K contents have been reported. This study aims to evaluate the K nutrition level based on leaf impedance spectroscopy. Five sets of tomato samples with different K contents were grown. Total K content of leaves was determined, and electrical impedance data recorded in a frequency range of 1 Hz to 1 MHz. The measured impedance data were analysed using an equivalent circuit model for cellular tissues. The change rule of equivalent parameters was obtained, and the sensitive impedance spectroscopy characteristics of K nutrition level were extracted. Moreover, the influence of moisture content on impedance measurement is discussed and the prediction model for K content is established. Results show that electrical impedance can be applied to the detection and diagnosis of plant K nutrition status.