Nigella sativa oil (NSO) is one of the high value oils in fats and oils industry due to its nutritional applications and its beneficial effects on human health. Several biological activities have been reported, especially antioxidant activities due to its active components, especially phenolics compounds. Some methods have been used for extraction of NSO from seeds to obtain high yield with excellent quality which includes solvent extraction, cold press, Soxhlet, and microwave assisted extraction. NSO commands a high price in the market, as a consequence, NSO is a target to be adulterated with cheaper oils such as corn and soybean oils. Indeed, the authentication analysis of NSO by determining several physico-chemical properties to determine the characteristics of NSO must be performed. This review highlighted some physico-chemical properties of NSO along with authentication of NSO from adulterants. The antioxidant activities of NSO were also highlighted in this review. Based on its activity as antioxidant, NSO is a good source to be used in nutraceutical and pharmaceutical products.
Honey is a natural food derived from flowers nectar that has many health benefits. This
reason made honey become one of category food product that has a risk to be adulterated
because of economically motivation. This study was conducted for characterization and
authentication of Indonesia wild honey (IWH) collected from seven geographical regions
(Sumatra, Bangka Belitung, Java, Kalimantan, Sulawesi, West Nusa Tenggara, and East
Nusa Tenggara) and harvested during 2016–2018 based on physicochemical parameters,
sugar content, minerals, and antioxidant components. The study showed that the result
differs widely among the type of honey. IWH has a moisture content between 16.52-
33.41%, a pH value between 3.00 to 4.65 and color characteristic ranged from pale yellow
to dark brown. All samples contain the highest amount in potassium, but several minerals
found in the specific region. Evaluation of authenticity from sugar content data set by
principal component analysis (PCA) and Linear Discriminant Analysis (LDA) revealed
that the authentic and adulterated honey samples could be differentiated with a 95.5%
accuracy. The honey samples were classified on their botanical and geographical origin
using the antioxidant properties, and results of PCA and LDA demonstrated that the
antioxidant parameters can provide adequate information to allow classification of the
various types of IWH samples collected from different geographical regions with accuracy
80-100% for Bangka Belitung, Sulawesi, Kalimantan, West Nusa Tenggara, East Nusa
Tenggara and Java island
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