Abstract: The wide range of metabolite concentration levels in biological samples represents a critical challenge in NMR analysis, since the NMR signals of highly concentrated metabolites usually overwhelm the spectrum and cover weaker peaks. Here, an optimum pulse sequence of band-selective excitation is proposed to suppress unwanted signals, especially sugar moieties signals (SSMS), which occur at very high concentrations compared to other metabolite signals in some biological and plant samples. We applied SSMS as the optimum pulse sequence of band selective excitation with 1D 1H presat, 2D J-RES, 2D TOCSY, and 2D 1H-13C HSQC to suppress concentrated sugar signals and identify metabolites with weaker signals. This suppression enhanced the visibility of low-concentrated metabolite signals in complex natural samples. We applied the SSMS method for proton 1D and 2D homo- and heteronuclear NMR experiments using samples of date-palm flesh, honey, a standard mixture of glucose and nine other essential primary metabolites, and fetal bovine serum. The results show that the usually overwhelming sugar signals were suppressed when applying the optimized pulse sequence for band-selective excitation, resulting in better visibility of the signals of other metabolites. Thus, by reducing the overwhelming peak of sugar, our method could detect and increase the visibilities of weaker peaks.