Determination of Bioactive Compounds in Buriti Oil by Prediction Models Through Mid-infrared Spectroscopy

被引:1
作者
da Silva, Braian Saimon Frota [1 ]
Ferreira, Nelson Rosa [2 ]
Chiste, Renan Campos [3 ]
Alves, Claudio Nahum [1 ]
机构
[1] Fed Univ Para PPGQ, Inst Exact & Nat Sci, Grad Program Chem, Lab Catalysis & Oleochem, BR-66075110 Belem, PA, Brazil
[2] Fed Univ UFPA, Inst Technol ITEC, Grad Program Food Sci & Technol PPGCTA, BR-66075110 Belem, PA, Brazil
[3] Fed Univ Minas Gerais UFMG, Fac Pharm, BR-31270901 Belo Horizonte, MG, Brazil
关键词
FT-MIR-ATR; PLSR; Bioactive compounds; Quality control; FTIR SPECTROSCOPY;
D O I
10.1007/s12161-024-02658-x
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Buriti oil is a vegetable oil extracted from the pulp and seeds of buriti (Mauritia flexuosa L.), a palm commonly found in the Amazon region, and is used both in popular medicine and in the cosmetic and food industries. This work aimed to develop a faster and more accessible procedure to quantify the content of carotenoids, polyphenols, and total flavonoids in buriti oils, where predictive models emphasize figures of merit. The study was carried out with 50 buriti oil samples from the state of Par & aacute;, Brazil, which were sampled by combining attenuated total reflection (ATR) spectroscopy with mid-infrared Fourier transform (FT-MIR) together with partial least squares regression (PLSR). The confidence and validation matrix were obtained from ultraviolet-visible spectroscopy. The PLSR model regarding the total carotenoid content presented values between 335.33 and 1557.05 mu g/g was validated by the concentration demonstration coefficient (R2cal) equal to 0.9556, prediction demonstration coefficient (R2pred) equal to 0.85642, bias = 5.68.10-13, performance deviation ratio value (RDP) of 2.0135, and range error rate (RER) equal to 4.3747. Concentrations of phenolic compounds were predicted between 96.2964 and 121.857 GAE/100 g, where the model presented R2cal = 0.9762, R2pred = 0.8198, bias = 3.38.10-10, RDP = 5.9028, and RER = 5.7578. The flavonoid prediction model contains concentrations between 86.844 and 133.852 mg EC/100 g that circulate R2cal = 0.9445, R2pred = 0.8536, bias = 6.98.10-8, RDP = 6.7085, and RER = 6.7085. Buriti oil showed high levels of b-carotene. Prediction models are overwhelming and can be used for screening and quality control of natural products.
引用
收藏
页码:1359 / 1372
页数:14
相关论文
共 80 条
  • [71] Camellia oil authentication: A comparative analysis and recent analytical techniques developed for its assessment. A review
    Shi, Ting
    Wu, Gangcheng
    Jin, Qingzhe
    Wang, Xingguo
    [J]. TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2020, 97 : 88 - 99
  • [72] Exploring two food composition databases to estimate nutritional components of whole meals
    Silva, Marta
    Ribeiro, Mafalda
    Viegas, Olga
    Martins, Zita E.
    Faria, Miguel
    Casal, Susana
    Pinto, Edgar
    Almeida, Agostinho
    Pinho, Olivia
    Ferreira, Isabel M. P. L. V. O.
    [J]. JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2021, 102
  • [73] Raman Spectroscopy Characterization of Mineral Oil and Palm Oil with Added Multi-Walled Carbon Nanotube for Application in Oil-Filled Transformers
    Suhaimi, Nur Sabrina
    Ishak, Mohd Taufiq
    Din, Muhamad Faiz Md
    Hashim, Fakhroul Ridzuan
    Rahman, Abdul Rashid Abdul
    [J]. ENERGIES, 2022, 15 (04)
  • [74] Torres LDFB, 2023, DRUG DISCOVERY DESIG, P525, DOI [10.1007/978-3-031-35205-819, DOI 10.1007/978-3-031-35205-819]
  • [75] Innovative Vibrational Spectroscopy Research for Forensic Application
    Weber, Alexis
    Hoplight, Bailey
    Ogilvie, Rhilynn
    Muro, Claire
    Khandasammy, Shelby R.
    Perez-Almodovar, Luis
    Sears, Samuel
    Lednev, Igor K.
    [J]. ANALYTICAL CHEMISTRY, 2023, 95 (01) : 167 - 205
  • [76] Comparison of Metabolites and Species Classification of Thirteen Zingiberaceae Spices Based on GC-MS and Multi-Spectral Fusion Technology
    Wen, Hui
    Yang, Tianmei
    Yang, Weize
    Yang, Meiquan
    Wang, Yuanzhong
    Zhang, Jinyu
    [J]. FOODS, 2023, 12 (20)
  • [77] Development and inter-laboratory validation of analytical methods for glufosinate and its two metabolites in foods of plant origin
    Wu, Yangliu
    Zhou, Yilu
    Jiao, Xun
    She, Yongxin
    Zeng, Wenbo
    Cui, Hailan
    Pan, Canping
    [J]. ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2024, 416 (03) : 663 - 674
  • [78] Rapid determination of capsaicin concentration in soybean oil by terahertz spectroscopy
    Xia, Yiming
    Liu, Wei
    Shi, Yule
    Younas, Shoaib
    Liu, Changhong
    Zheng, Lei
    [J]. JOURNAL OF FOOD SCIENCE, 2022, 87 (02) : 567 - 575
  • [79] A comparative study on classification of edible vegetable oils by infrared, near infrared and fluorescence spectroscopy combined with chemometrics
    Yuan, Libo
    Meng, Xiangru
    Xin, Kehui
    Ju, Ying
    Zhang, Yan
    Yin, Chunling
    Hu, Leqian
    [J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2023, 288
  • [80] Analytical methods for determining the peroxide value of edible oils: A mini-review
    Zhang, Na
    Li, Yonglin
    Wen, Shasha
    Sun, Yiwen
    Chen, Jia
    Gao, Yuan
    Sagymbek, Altayuly
    Yu, Xiuzhu
    [J]. FOOD CHEMISTRY, 2021, 358