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Identification of provenance of Basmati rice grown in different regions of Punjab through multivariate analysis.
Saifullah, Muhammad; Nisar, Awais; Akhtar, Ramzan; M Husnain, Syed; Imtiaz, Shamila; Ahmad, Bashir; Ahmed Shafique, Munib; Butt, Saira; Arif, Muhammad; Majeed Satti, Abid; Shahzad Ahmed, Muhammad; Kelly, Simon D; Siddique, Naila.
Afiliación
  • Saifullah M; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan. Electronic address: saifi.551@gmail.com.
  • Nisar A; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • Akhtar R; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • M Husnain S; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan. Electronic address: hussnainchem@gmail.com.
  • Imtiaz S; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • Ahmad B; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • Ahmed Shafique M; Central Analytical Facility Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • Butt S; Isotope Application Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
  • Arif M; National Institute of Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan.
  • Majeed Satti A; Crop Sciences Institute (Rice Program), PARC-National Agriculture Research Center, 44000, Park Road, Islamabad, Pakistan.
  • Shahzad Ahmed M; Crop Sciences Institute (Rice Program), PARC-National Agriculture Research Center, 44000, Park Road, Islamabad, Pakistan.
  • Kelly SD; International Atomic Energy Agency, Vienna International Center, PO Box 100, Wagramer Strasse 5, 1400, Vienna, Austria.
  • Siddique N; Chemistry Division, Pakistan Institute of Nuclear Science and Technology (PINSTECH), Islamabad 45650, Pakistan.
Food Chem ; 444: 138549, 2024 Jun 30.
Article en En | MEDLINE | ID: mdl-38335678
ABSTRACT
High-priced Basmati rice is vulnerable to deliberate mislabeling to increase profits. This type of fraud may lower consumers' confidence as inferior products can affect brand reputation. To address this problem, there is a need to devise a method that can efficiently distinguish Basmati rice grown in regions that are famous versus the regions that are not suitable for their production. Therefore, in this investigation, thirty-six samples of Basmati rice were collected from two zones of Punjab province (one known for Basmati rice) of Pakistan which is the major producer of Basmati rice. The elemental composition of rice samples was assessed using inductively coupled plasma-optical emission spectrometry and an organic elemental analyzer, whereas data on δ13C was acquired using isotopic ratio-mass spectrometry. Regional clustering of samples based on their respective cultivation zones was observed using multivariate data analysis techniques. Partial least squares-discriminant analysis was found to be effective in grouping rice samples from the different locations and identifying unknown samples belonging to these two regions. Further recommendations are presented to develop a better model for tracing the origin of unidentified rice samples.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza Tipo de estudio: Diagnostic_studies Idioma: En Revista: Food Chem Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza Tipo de estudio: Diagnostic_studies Idioma: En Revista: Food Chem Año: 2024 Tipo del documento: Article