Discriminate geographical origin of cabe jamu (Piper retrofractum vahl) using nir spectral fingerprints– a short review

Abstract Cabe jamu is categorized as the primary material for the jamu industry because it contains an active compound that provides a health benefit. Furthermore, some area in east java is known as the central production of cabe jamu. Almost 80% of the plant area is located at Madura Island, coveri...

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Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2023-06, Vol.1182 (1), p.12081
Main Authors: Mu’tamar, M F F, Hidayat, K, Mahardika, A P, Firmansyah, R A, Sucipto, S
Format: Article
Language:English
Subjects:
Agricultural products
Classification
Counterfeit
Data integration
Environmental conditions
Infrared spectroscopy
Soil conditions
Spectroscopy
Spectrum analysis
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Summary:Abstract Cabe jamu is categorized as the primary material for the jamu industry because it contains an active compound that provides a health benefit. Furthermore, some area in east java is known as the central production of cabe jamu. Almost 80% of the plant area is located at Madura Island, covering Bangkalan, Sampang, Pamekasan, and Sumenep. Agricultural products have different characteristics when planted at different locations because of climate, soil, and environmental condition. However, counterfeit practice deteriorates the specialty of products for economic purposes. Several techniques were developed detection system of products based on geographical origin or authenticity. This paper aims to explore potential technology that is able to evaluate the authentication of products and potentially applied to cabe jamu. Overall, several strategies were obtained from this literature study to provide the high-accuracy classification of cabe jamu related to geographical origin: Coupling NIR spectroscopy with chemometrics, utilization of multiple techniques like other vibrational spectroscopy or non-vibrational spectroscopy, and use of data fusion approach to elevate the accuracy of the classification model.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/1182/1/012081