Nondestructive diagnostics of magnesium deficiency based on distribution features of chlorophyll concentrations map on cucumber leaf

Abstract

A new and nondestructive method for diagnosing magnesium (Mg) deficiency based on chlorophyll concentration distribution features of cucumber leaves was proposed. Mg deficient cucumber plants and Control plants were grown under non-soil conditions with special nutrient supply. Cucumber leaves were employed to collect hyperspectral images using a visible and near infrared (VIS/NIR) hyperspectral imaging system (400–900 nm) and determine reference chlorophyll concentrations using high performance liquid chromatography (HPLC). An optimal chlorophyll concentration calibration model (Rp = 0.9087) was constructed and used to detect chlorophyll distribution maps of Mg deficient leaves and Control leaves. Results shown that chlorophyll content distributed more unevenly on Mg deficient leaves than Control leaves. The Standard Deviation (SD) value of the chlorophyll content at all the pixels on a chlorophyll distribution map was calculated for Mg deficient diagnostics. An Mg deficiency diagnostics model with satisfied performance (diagnostic rate 93.33%) was obtained. The result indicated the SD value of chlorophyll concentrations on the whole cucumber leaf could be employed to diagnose Mg deficiency nondestructively.

Keywords:

• chlorophyll
• cucumber
• deficiency
• diagnostics
• distribution
• magnesium

Additional information

Funding

The authors gratefully acknowledge the financial support provided by the National Key Research and Development Program of China (2017YFC1600805), the National Natural Science Foundation of China (31772073, 60901079, 31972151), the Natural Science Foundation of Jiangsu Province (BE2016306, BK20130505), China Postdoctoral Science Foundation (2016M600379), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (16KJB550002), Jiangsu Planned Projects for Postdoctoral Research Funds (1601080B), Six Talent Peaks Project in Jiangsu Province (GDZB-016), Key R&D Project of Jiangsu Province (BE2018307), Project on the integration of Industry, Education and Research cooperation of Jiangsu Province (BY2018030) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).