Rapid detection of Ganoderma-infected oil palms by microwave ergosterol extraction with HPLC and TLC.

Abstract

Detection of basal stem rot (BSR) by Ganoderma of oil palms was based on foliar symptoms and production of basidiomata. Enzyme-Linked Immunosorbent Assays-Polyclonal Antibody (ELISA-PAB) and PCR have been proposed as early detection methods for the disease. These techniques are complex, time consuming and have accuracy limitations. An ergosterol method was developed which correlated well with the degree of infection in oil palms, including samples growing in plantations. However, the method was capable of being optimised. This current study was designed to develop a simpler, more rapid and efficient ergosterol method with utility in the field that involved the use of microwave extraction. The optimised procedure involved extracting a small amount of Ganoderma, or Ganoderma-infected oil palm suspended in low volumes of solvent followed by irradiation in a conventional microwave oven at 70°C and medium high power for 30s, resulting in simultaneous extraction and saponification. Ergosterol was detected by thin layer chromatography (TLC) and quantified using high performance liquid chromatography with diode array detection. The TLC method was novel and provided a simple, inexpensive method with utility in the field. The new method was particularly effective at extracting high yields of ergosterol from infected oil palm and enables rapid analysis of field samples on site, allowing infected oil palms to be treated or culled very rapidly. Some limitations of the method are discussed herein. The procedures lend themselves to controlling the disease more effectively and allowing more effective use of land currently employed to grow oil palms, thereby reducing pressure to develop new plantations.

DOI: 10.1016/j.mimet.2014.03.005

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Cite this paper

@article{Muniroh2014RapidDO, title={Rapid detection of Ganoderma-infected oil palms by microwave ergosterol extraction with HPLC and TLC.}, author={M S Muniroh and Meon Sariah and Muchlisin Zainal Abidin and Nelson Lima and Robert Paterson}, journal={Journal of microbiological methods}, year={2014}, volume={100}, pages={143-7} }