Characterization of rice cultivars using Raman spectroscopy and multivariate analysis

被引:2
|
作者
Kadam, Saurabh [1 ]
Jadhav, Priyanka A. [4 ,5 ]
Singh, Rajshri [1 ]
Hole, Arti [4 ]
Sawardekar, Santosh [3 ]
Krishna, C. Murali [4 ,5 ]
Barage, Sagar [1 ,2 ]
机构
[1] Amity Univ, Amity Inst Biotechnol, Panvel 410206, Maharashtra, India
[2] Amity Univ, Amity Inst Biotechnol, Ctr Computat Biol & Translat Res, Panvel 410206, Maharashtra, India
[3] Dr Balasaheb Sawant Konkan Krishi Vidyapeeth, Plant Biotechnol Ctr, Dapoli 415712, India
[4] Tata Mem Hosp, Adv Ctr Treatment Res & Educ Canc, Navi Mumbai 410210, India
[5] Homi Bhabha Natl Inst, Training Sch Complex, Mumbai 400094, India
来源
BIOCATALYSIS AND AGRICULTURAL BIOTECHNOLOGY | 2024年 / 60卷
关键词
Rice cultivars; Nutritional content; Raman spectroscopy; Multivariate analysis; AMYLOSE CONTENT; ORAL CANCERS; ANTIOXIDANT; PHYTOCHEMICALS; IDENTIFICATION; QUALITY;
D O I
10.1016/j.bcab.2024.103280
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Rice is a widely consumed cereal known for its high carbohydrate content and the presence of essential nutritional elements such as proteins and lipids. The previous Raman spectroscopy (RS) studies on whole brown rice kernel have only been able to partially reveal nutritional content. This study employs RS to accurately assess the nutritional profiles of forty rice cultivars in powdered form, facilitating their characterization. The combination of RS and advanced chemometric techniques enables the discrimination of rice cultivars based on key biochemical attributes, including amylose and starch content, aromatic properties, protein content, and total antioxidant capacity, resulting in an impressive accuracy rate of 73%. Significant observations in the fingerprint region included specific Raman spectral features associated with glucose ring stretching at similar to 478 cm-1 and indicative stretching vibrations for glycosidic bonds and amylose structures at similar to 409 cm-1, similar to 439 cm-1, similar to 521 cm-1, and similar to 868 cm-1. Furthermore, prominent spectral bands associated with amino acids such as phenylalanine (similar to 1004 cm-1, similar to 1580 cm-1, similar to 1606 cm-1), tryptophan (similar to 872 cm-1, similar to 1360 cm-1, similar to 1543 cm-1, similar to 1620 cm-1), and tyrosine (similar to 853 cm-1, similar to 1176 cm-1, similar to 1556 cm-1) were observed. Additionally, characteristic peaks related to protein content, carotenoids, and amino acids were identified at similar to 1084 cm-1, similar to 1111 cm-1, similar to 1162 cm-1, similar to 1263 cm-1, similar to 1310 cm-1, and similar to 1404 cm-1. These findings underscore the potential of RS as a fully automated, rapid, and accurate tool for evaluating the nutritional content of rice cultivars.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Evaluation of antibiotic effects on Pseudomonas aeruginosa biofilm using Raman spectroscopy and multivariate analysis
    Jung, Gyeong Bok
    Nam, Seong Won
    Choi, Samjin
    Lee, Gi-Ja
    Park, Hun-Kuk
    BIOMEDICAL OPTICS EXPRESS, 2014, 5 (09): : 3238 - 3251
  • [32] Classification of Greek extra virgin olive oils by Raman spectroscopy in conjunction with sensory and cultivation characteristics, and multivariate analysis
    Philippidis, Aggelos
    Kontzedaki, Renate
    Orfanakis, Emmanouil
    Fragkoulis, Nikolaos
    Zoumi, Aikaterini
    Germanaki, Eleftheria
    Samartzis, Peter C.
    Velegrakis, Michalis
    JSFA REPORTS, 2023, 3 (10): : 486 - 493
  • [33] Study of moisture content and water activity of rice using fluorescence spectroscopy and multivariate analysis
    Ozbekova, Zhyldyzai
    Kulmyrzaev, Asylbek
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2019, 223
  • [34] Cross-Scale Predictive Modeling of CHO Cell Culture Growth and Metabolites Using Raman Spectroscopy and Multivariate Analysis
    Berry, Brandon
    Moretto, Justin
    Matthews, Thomas
    Smelko, John
    Wiltberger, Kelly
    BIOTECHNOLOGY PROGRESS, 2015, 31 (02) : 566 - 577
  • [35] Determination of milk fat authenticity in ultra-filtered white cheese by using Raman spectroscopy with multivariate data analysis
    Genis, Duygu Ozer
    Sezer, Banu
    Durna, Sahin
    Boyaci, Ismail Hakki
    FOOD CHEMISTRY, 2021, 336
  • [36] Identification of rice varieties and determination of their geographical origin in China using Raman spectroscopy
    Zhu, Ling
    Sun, Juan
    Wu, Gangcheng
    Wang, Yanan
    Zhang, Hui
    Wang, Li
    Qian, Haifeng
    Qi, XiGuang
    JOURNAL OF CEREAL SCIENCE, 2018, 82 : 175 - 182
  • [37] Evaluation of sample pretreatment method for geographic authentication of rice using Raman spectroscopy
    Sha, Min
    Gui, Dongdong
    Zhang, Zhengyong
    Ji, Xinyan
    Shi, Xiaojing
    Liu, Jun
    Zhang, Ding
    JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION, 2019, 13 (03) : 1705 - 1712
  • [38] Raman spectroscopy and multivariate analysis as potential tool to follow Alzheimer's disease progression
    Carota, Angela Gilda
    Campanella, Beatrice
    Del Carratore, Renata
    Bongioanni, Paolo
    Giannelli, Roberta
    Legnaioli, Stefano
    ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2022, 414 (16) : 4667 - 4675
  • [39] Raman spectroscopy and multivariate analysis as potential tool to follow Alzheimer’s disease progression
    Angela Gilda Carota
    Beatrice Campanella
    Renata Del Carratore
    Paolo Bongioanni
    Roberta Giannelli
    Stefano Legnaioli
    Analytical and Bioanalytical Chemistry, 2022, 414 : 4667 - 4675
  • [40] Rapid Detection of Adulterants in Whey Protein Supplement by Raman Spectroscopy Combined with Multivariate Analysis
    Jiao, Xianzhi
    Meng, Yaoyong
    Wang, Kangkang
    Huang, Wei
    Li, Nan
    Liu, Timon Cheng-Yi
    MOLECULES, 2019, 24 (10)