A computational approach was used to analyze the FTIR spectra of a wide range of treated and untreated lignocellulosic biomass (coconut husk, banana trunk, sago hampas, rice husk, and empty fruit bunch). The biomass was treated with strong sulphuric acid and NaOH, respectively. A total of 87 spectra were obtained in which the absorption bands were de-convoluted automatically, generating a peak table of 87 rows and 60 columns. Square roots were taken of the peak values, with further standardization prior to Principal Component Analysis (PCA) for data exploration. In a scores plot, the treated and untreated biomass were distinguishable along the two main axes, PC1 and PC2. Examining the absorption bands corresponding to lignocellulosic components indicated that the acid pretreatment had resulted in dissolution and degradation of hemicelluloses and lignin, confirmed typically by disappearance of bands. The alkali treatment however was not as rigorous as the acid treatment, as some characteristic bands of hemicelluloses and lignin were enhanced, suggesting condensation of the degraded polysaccharides. The computer-assisted analysis of the FTIR spectra allowed efficient and simultaneous comparisons of lignocellulosic compositions present in various treated and untreated biomass. This represents an improvement relative to the conventional methods, since a large dataset can be handled efficiently and individual peaks can be examined.

Fourier Transform Infrared (FTIR) and Gas Chromatography Mass Spectrometry (GCMS) are two common instruments used for analysis of edible oils. The output signal is often analysed on the software attached to the workstations. The processing software is usually individualised for a specific source. The output of GCMS cannot be analysed on the FTIR hence analysts often need to juggle between instruments when multiple techniques are employed. This could become exhaustive when a large dataset is involved. This paper reports a synchronised approach for analysis of signal from FTIR and GCMS. The algorithm is demonstrated on a dataset of edible oils to investigate the thermal degradation of seven types of edible oils treated at 100°C and 150°C. The synchronised routines identify peaks present in FTIR and GCMS spectra/chromatograms where the information is subsequently extracted onto peak tables for further analysis. In this study, it is found that palm based products and corn oils were relatively more stable with higher content of antioxidants tocopherols and squalene. As a conclusion, this approach allows simultaneous analysis of signal from multiple sources and samples enhancing the efficiency of the signal processing process.

This paper reports the metals content in water, sediment, macroalgae, aquatic plant, and fish of Batang Ai Hydroelectric Reservoir in Sarawak, Malaysia. The samples were acid digested and subjected to atomic absorption spectrometry analysis for Na, K, Mn, Cr, Ni, Zn, Mg, Fe, Sn, Al, Ca, As, Se, and Hg. The total Hg content was analysed on the mercury analyser. Results showed that metals in water, sediment, macroalgae, aquatic plant, and fish are distinguishable, with sediment and biota samples more susceptible to metal accumulation. The distributions of heavy metals in water specifically Se, Sn, and As could have associated with the input of fish feed, boating, and construction activities. The accumulation of heavy metals in sediment, macroalgae, and aquatic plant on the other hand might be largely influenced by the redox conditions in the aquatic environment. According to the contamination factor and the geoaccumulation index, sediment in Batang Ai Reservoir possesses low risk of contamination. The average metal contents in sediment and river water are consistently lower than the literature values reported and well below the limit of various guidelines. For fishes, trace element Hg was detected; however, the concentration was below the permissible level suggested by the Food and Agriculture Organization.

The presence of dissolved organic matter, scientifically known as humic substances, gives an undesirable color and taste to water. In addition, they are the precursors of carcinogenic disinfection by-products upon disinfection treatment. Adsorption provides a potential means of removal of humic substances, and lignocellulosic biomass serves as a promising candidate. In this paper, we report the application of modified coconut copra residues for adsorption of humic substances from peat swamp runoff. The FTIR spectra suggest that coconut copra residues are genuinely rich with carboxyl groups with long alkyl chains; this renders the material a natural biosorbent, attaining an average of 50% removal under the conditions of testing. Upon treatment, dissolution of lignin and hemicellulose with the enhancement of effective carboxyl groups occurs, improving the adsorption efficiency to 96%; the treated water is visibly clear. The relative band abundance and band shifts further confirm the involvement of the surface functional groups in the adsorption process. The modified coconut copra residue is an attractive biosorbent option for removal of humic substances. The operating conditions are mild, involving non-toxic chemicals, and no pH adjustment is necessary to allow adsorption.