Quality assessment of coconut oil and detection of adulteration

Abstract

The research programme entitled “Quality assessment of coconut oil and detection of adulteration” was undertaken at the Department of Plantation Crops and Spices, College of Agriculture Vellayani during the period 2018-2020. The study was conducted in order to assess the quality parameters of coconut oil and to detect adulteration by different techniques and to validate an easy and efficient method for the detection. Coconut oil was adulterated with 1, 5, 10, 15, 20 and 30 per cent of palm kernel oil and mineral oil. Apart from this pure coconut oil, pure palm kernel oil, pure mineral oil and five branded coconut oils were also collected altogether contributing twenty samples. These samples were analysed for physical and chemical characteristics, microbial contamination, thin layer chromatography, fatty acid composition by GCMS and FTIR spectroscopy to detect adulteration and to find an easy and efficient method for detection of adulteration. Physical and chemical characteristics analysed revealed refractive index and relative density of pure coconut oil, branded coconut oil and coconut oil mixed up to 30 per cent palm kernel oil were within the codex standard range. The apparent density of pure coconut oil differed significantly from adulterated samples. Insoluble impurities of all the samples were in the range 0.024-0.047 per cent which was within the standard prescribed by Codex (< 0.05 per cent). Saponification value of pure sample and all the branded coconut oil samples showed a value above 250 mg KOH g of oil-1 which was in tune with standard specified by FSSAI. Palm kernel oil and mineral oil as adulterant in different percentage showed less than 250 mg KOH g of oil-1. FSSAI standard for iodine value of coconut oil is in the range 7.5-10g and the iodine value of pure sample and all the branded coconut oil samples tested were within the range 7.5-10g. Iodine value of coconut oil adulterated with 5 per cent palm kernel oil and above exceeded the standard value (10) while adulteration with mineral oil above 1 per cent showed less than 7.5g. Standard Polenske value as prescribed by FSSAI and Codex (not less than13) was noticed in all samples except coconut oil with palm kernel oil 5 per cent and above and all mineral oil combinations. Pure sample, branded coconut oil and coconut oil mixed with varying percentage of palm kernel oil had unsaponifiable value within the limit of standards (not more than 1 per cent) while that of coconut oil mixed with even 1 per cent mineral oil and above exceeded the limit (1.18 per cent). Acid value of not more than 6 was the standard put forward by FSSAI and Codex and all oil samples except palm kernel oil and coconut oil mixed with 15 per cent palm kernel oil and above recorded values above 6. FSSAI standard for peroxide content in fresh coconut oil is below 10 meq/Kg and higher peroxide value were obtained from coconut samples mixed with palm kernel oil at 5 per cent and above and mineral oil at 15 per cent and above. Codex standard for matter volatile at 105°C is < 0.2% and all samples were within the limit. Principal component analysis (PCA) performed on physical and chemical characteristics of oil revealed high coefficient in PC1 for unsaponifiable matter and it contributed to maximum variation followed by relative density, apparent density, Polenske value, refractive index, saponification value and iodine value. In PC2, high coefficient was noticed for acid value followed by peroxide value and iodine value . Microbial contamination assessed by total plate count was within the APCC standard of less than 10 (< 10) colony forming units/ml. Fungal and actinomycete population was however not detected in the oil samples. Thin layer chromatography revealed yellow streaks in the profile of pure coconut oil sample, branded coconut oil samples and coconut oil mixed with different concentrations of palm kernel oil while yellow streaks were absent in coconut oil samples mixed with mineral oil. Gas chromatography coupled with mass spectrometry revealed the fatty acid composition in the oil samples. Principal component analysis carried out to analyze the variation contributed by the fatty acids revealed C16:0, C 12:0 and C 14:0 contributed the maximum variation in PC1. In PC2 high coefficient was noticed for C8:0 and C10:0. Percentage of oleic (C18:1) and linoleic (C18:2) acids were found to increase with increase in concentration of palm kernel oil and fatty acids were not detected in mineral oil. FTIR spectra formed peaks at regions of 2800-2900 cm-1, 1743 cm-1, 1465 cm- 1, 1417 cm-1, 1377 cm-1, 1229 cm-1, 1155 cm-1, 1111 cm-1, 962 cm-1, 722 cm-1 in pure coconut oil sample. Branded coconut oil samples and palm kernel oil adulterated samples obtained peaks at similar regions. Intensity of the peak at 3006 cm-1 increased with increasing concentration of palm kernel oil. The peaks for mineral oil were obtained at 2954 cm-1, 2923 cm-1, 2854cm1, 1466 cm-1, 1378 cm-1 and 721 cm-1. Intensity of the peaks at 1743 cm-1, 1229 cm-1, 1155 cm-1 and 1111 cm-1 were found to decrease with increase in percentage of mineral oil which indicated the absence of carbonyl group in mineral oil. Economics of adulteration of coconut oil by palm kernel oil and mineral oil revealed that maximum of Rs 4800/- per quintal was obtained by adulteration when 30 per cent of coconut oil was substituted by mineral oil followed by 20 per cent mineral oil ( Rs 3200/- per quintal) and 30 per cent palm kernel oil ( Rs 3150/- per quintal). The present study implies that among the physical and chemical parameters, unsaponifiable matter, relative density, apparent density, Polenske value and refractive index could be used to identify the adulteration in coconut oil by mineral oil. Similarly thin layer chromatography could also detect the presence of mineral oil. Saponification value, iodine value and Polenske value could detect the adulteration due to palm kernel oil. The use of FTIR spectroscopic technique is an easy method to identify adulteration in coconut oil through identification of specific peaks. GCMS analysis could provide information about the fatty acid composition.