Diagnosis and detection of phosphorus nutrition level for Solanum lycopersicum based on electrical impedance spectroscopy. (March 2016)

• Record Type: Journal Article
• Authors: Meiqing, Li; Jinyang, Li; Hanping, Mao; Yanyou, Wu
• Is Part Of: Biosystems engineering. Volume 143(2016:Mar.)
• Page Start: 108
• Page End: 118
• Publication Date: 2016-03
• Subjects: Solanum lycopersicum -- Phosphorus nutrition level -- Diagnosis and detection -- Electrical impedance spectroscopy; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2016.01.005
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Phosphorus (P) performs a key function in crop yield and quality. P deficiency frequently occurs in crop production and degrades crop yield and quality. Excessive P fertilisers cause environmental pollution and increase production cost. Therefore, diagnosis and detection of P content in plants are impending. Crop P monitoring methods have been developed to improve P fertiliser management, and most of these methods are based on leaf or canopy optical property measurements. However, sensitivity to environmental interference remains an important drawback. Electrical impedance has been applied to determine the physiological and nutritional status of plant tissue, but no studies related to plant P content have been reported. The objective of this article is to analyse how electrical impedance response of tomatoes is influenced by P nutrition status and explore the feasibility of P-deficiency detection by electrical impedance measurement. Five sets of tomato with different P source concentrations are used. Total P and electrical impedance spectra within the frequency range of 1 Hz–1 MHz are measured. The measured impedance data are analysed by using the modified model. The changes in equivalent parameters are analysed, the influence of moisture content on impedance measurement is discussed, and the characteristic frequency band is obtained. Then, we established the regression prediction model between total P and electrical impedance. High and positive correlation is observed between plant P content and impedance values at the obtained characteristic frequencies. Results suggest that electrical impedance can be applied to the detection and diagnosis of plant P nutrition status. Highlights: Online and rapid diagnosis and detection of P nutrition level in plant are important. Present a novel diagnosis and detection method of P nutrition level based on EIS. Equivalent circuit model is built and characteristic frequency band is selected. Relation between P-content and impedance are analysed by PCA and stepwise regression. The efficiency and potential are validated by experiments.