ARS | Publication request: Detection and Quantification of Silicon in Floricultural Crops Utilizing Three Distinct Analytical Methods

Submitted to: Communications in Soil Science and Plant Analysis
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 1, 2007
Publication Date: October 10, 2008
Repository URL: http://hdl.handle.net/10113/21441
Citation: Frantz, J., Locke, J.C., Datnoff, L., Omer, M.A., Widrig, A.K., Sturtz, D.S., Horst, L., Krause, C.R. 2008. Detection and Quantification of Silicon in Floricultural Crops Utilizing Three Distinct Analytical Methods. Communications in Soil Science and Plant Analysis. 39:2734-2751.

Interpretive Summary: Silicon (Si) is increasingly used in agriculture because it helps crops resist some types of stress. Several methods for detecting and quantifying silicon in plants have been reported, but it is not known how well the different methods correlate to one another. Furthermore, the use of some methods requires expensive or not-readily available equipment or highly corrosive chemicals. We compared silicon detection and quantification using three different methods in 14 economically important floriculture species. Generally, there was agreement between the plasma spectroscopic and colorimetric methods with only a few species deviating substantially between them including snapdragon (.05% vs. 0.025% silicon dry weight), impatiens (0.2% vs. 0.09%) and poinsettia (0.046% vs. 0.094%). The results of these studies test suggest there is agreement between quantification methods and a lower detection limit of about 300 mg kg-1 dry weight of Si using an electron microscope. Changing tissue preparation methods from NaOH to KOH resulted in safer procedures for analysis. Several new floriculture species were also identified that take up and accumulate silicon in significant concentrations.

Technical Abstract: Silicon (Si) is increasingly used in agriculture due to its apparent beneficial effects in stimulating stress resistance in some crops. Several methods for detecting and quantifying silicon in plants have been reported including electron beam analysis (EBA), which is the use of scanning electron microscopy with energy dispersive X-ray analysis, colorimetric determination of silicon after autoclave-induced digestion, and inductively coupled plasma optical emission spectroscopy (ICP-OES), which relies on similar digestion approaches as the colorimetric method. Typically, only one method for quantification is used in a study, so it is not known how well the different methods correlate to one another. Furthermore, the use of some methods requires expensive or not-readily available equipment or highly corrosive reagents. We compared silicon detection and quantification using EBA, colorimetric analysis, and ICP-OES in 14 economically important floriculture species. We also sought to reduce the reliance on highly corrosive materials in order to produce a safer, more cost effective approach to the analysis of silicon in plant tissues. Using EBA, silicon was identified most commonly around the base of trichomes and along the leaf margins. Processing and analyzing for silicon using NaOH resulted in damaged torches and microwavable, Teflon vessels that required expensive replacement at the end of each run. Conversely, analyzing samples with the KOH-based matrix in the ICP resulted in minimal visible damage and was able to make multiple runs without replacement. Generally, there was agreement between the ICP-OES and colorimetric methods with only a few species deviating substantially between ICP and colorimetric methods including snapdragon (.05% vs. 0.025% silicon dry weight), impatiens (0.2% vs. 0.09%) and poinsettia (0.046% vs. 0.094%). The results of this test suggest there is agreement between quantification methods and a lower detection limit of about 300 mg kg-1 dry weight of Si using EBA. Changing tissue preparation methods from NaOH to KOH resulted in safer procedures for analysis. Several new floriculture species were also identified that take up and accumulate silicon in significant concentrations.