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  • Ký hiệu PL/XG: 664
    Nhan đề: Multivariate statistical approach in food and pharmaceutical quality control /
DDC 664
Nhan đề Multivariate statistical approach in food and pharmaceutical quality control / Nguyen Thu Hoai, Nguyen Phuc Thinh, Ly Du Thu, Nguyen Huu Quang, Nguyen Thi My Chi, Ta Thi Le Huyen, Vo Hien, Nguyen Anh Mai
Thông tin xuất bản Ho Chi Minh city : Nguyen Tat Thanh University, 2019
Mô tả vật lý 8 p.
Tóm tắt IR spectra contain chemical information of matter and can be acquired from raw/untreated samples. The spectra are, however, complicated to interpret and could not be used directly for both qualitative and quantitative purposes. In this research a statistical approach namely, multivariate data analysis (MVDA) or chemometrics was employed for mining information related to chemical compositions from spectroscopic data. Two examples are used to illustrate the potential of this approach, one is edible oil (using benchtop FT-IR), and pharmaceuticals (using handheld NIR). Olive oil was differentiated from adulterants (sesame, sunflower, palm oil) in PCA, and the content of olive oil was successfully determined by the PLS model the error of olive oil content < 5%. Norfloxacin content in lab-scale powder formulation yield the auspicious results with the error < 6%. The results proved the developed techniques are promising for rapid analysis at significantly lower costs.
Từ khóa tự do Chất lượng thực phẩm và dược phẩm
Từ khóa tự do Chemometrics
Từ khóa tự do Food and pharmaceutical quality
Từ khóa tự do Handheld NIR
Từ khóa tự do Multivariate data analysis
Từ khóa tự do Phân tích dữ liệu đa biến
Tác giả(bs) CN Ly, Du Thu
Tác giả(bs) CN Nguyen, Phuc Thinh
Tác giả(bs) CN Nguyen, Thu Hoai
Nguồn trích Journal of Science and Technology - NTTU2019p. 59-66 Số: 06
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082 |a664
245 |aMultivariate statistical approach in food and pharmaceutical quality control / |cNguyen Thu Hoai, Nguyen Phuc Thinh, Ly Du Thu, Nguyen Huu Quang, Nguyen Thi My Chi, Ta Thi Le Huyen, Vo Hien, Nguyen Anh Mai
260 |aHo Chi Minh city : |bNguyen Tat Thanh University, |c2019
300 |a8 p.
520 |aIR spectra contain chemical information of matter and can be acquired from raw/untreated samples. The spectra are, however, complicated to interpret and could not be used directly for both qualitative and quantitative purposes. In this research a statistical approach namely, multivariate data analysis (MVDA) or chemometrics was employed for mining information related to chemical compositions from spectroscopic data. Two examples are used to illustrate the potential of this approach, one is edible oil (using benchtop FT-IR), and pharmaceuticals (using handheld NIR). Olive oil was differentiated from adulterants (sesame, sunflower, palm oil) in PCA, and the content of olive oil was successfully determined by the PLS model the error of olive oil content < 5%. Norfloxacin content in lab-scale powder formulation yield the auspicious results with the error < 6%. The results proved the developed techniques are promising for rapid analysis at significantly lower costs.
653 |aChất lượng thực phẩm và dược phẩm
653 |aChemometrics
653 |aFood and pharmaceutical quality
653 |aHandheld NIR
653 |aMultivariate data analysis
653 |aPhân tích dữ liệu đa biến
690 |aKhoa Công nghệ Hoá học & Thực phẩm
690|aKhoa Dược
700 |aLy, Du Thu
700 |aNguyen, Phuc Thinh
700 |aNguyen, Thu Hoai
773 |tJournal of Science and Technology - NTTU|d2019|gp. 59-66|x2615-9015|i06
890|c1|a0|b0|d6
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