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Mendes JF, Norcino LB, Corrêa TQ, Barbosa TV, Paschoalin RT, Mattoso LHC. Obtaining poly (lactic acid) nanofibers encapsulated with peppermint essential oil as potential packaging via solution-blow-spinning. Int J Biol Macromol 2023; 230:123424. [PMID: 36708906 DOI: 10.1016/j.ijbiomac.2023.123424] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 01/18/2023] [Accepted: 01/21/2023] [Indexed: 01/27/2023]
Abstract
The development of active packaging based on biodegradable material and incorporating active compounds, such as essential oil, is a new technique to ensure food safety without harming the environment. In this study, nanofiber mats of poly (lactic acid)/ polyethylene glycol (PLA/PEG) blend incorporated with peppermint essential oil (PO) at different ratios (5-20 % v/w) were produced by solution-blow-spinning (SBS) for potential packaging application. Electron microscopy showed a cylindrical and interlaced morphology for PLA/PEG/PO and a significant increase in the diameter (139-192 nm) of the nanofibers by increasing PO content. All nanofibers showed high thermal stability (278-345 °C) suitable for use in the food industry. Nuclear magnetic resonance (13C NMR) spectrum confirmed PO in the nanofibers after SBS. ATR-FTIR spectral analysis supported the chemical composition of the nanofiber mats. PO addition led to obtaining hydrophobic nanofibers, enhancing the contact angle to 122° and decreasing water vapor permeability (60 % reduction compared to the PLA/PEG (3.0 g.mm.kPa-1.h-1.m-2). Although the PLA/PEG/20%PO nanofibers did not show halo formation in 24 h, they effectively extended the strawberries' shelf-life at 25 °C, evidencing PO release over time. It also reduced weight loss (2.5 % and 0.3 % weight loss after 5 days for PLA/PEG and PLA/PEG/20%PO, respectively) and increased firmness (8-12 N) for strawberries packed with the nanofiber mats. It is suggested that PLA/PEG films incorporating PO may be used as an active, environmentally friendly packaging material.
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Affiliation(s)
- Juliana Farinassi Mendes
- National Laboratory of Nanotechnology for Agriculture (LNNA), Embrapa Instrumentation, São Carlos 13560-970, São Paulo, Brazil.
| | - Laís Bruno Norcino
- Graduate Program in Biomaterials Engineering, Federal University of Lavras, Lavras 37200-000, Minas Gerais, Brazil
| | - Thaila Quatrini Corrêa
- São Carlos Institute of Physics, University of São Paulo, PO Box 369, 13560-970 São Carlos, São Paulo, Brazil
| | - Talita Villa Barbosa
- São Carlos School of Engineering, University of São Paulo, 13560-970 São Carlos, São Paulo, Brazil
| | - Rafaella T Paschoalin
- National Laboratory of Nanotechnology for Agriculture (LNNA), Embrapa Instrumentation, São Carlos 13560-970, São Paulo, Brazil
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Liu Z, Zhang M, Chen P, Harnly JM, Sun J. Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:11138-11153. [PMID: 35998657 DOI: 10.1021/acs.jafc.2c01878] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.
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Affiliation(s)
- Zhihao Liu
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
- Department of Nutrition and Food Science, University of Maryland, College Park, Maryland 20742, United States
| | - Mengliang Zhang
- Department of Chemistry, Middle Tennessee State University, Murfreesboro, Tennessee 37132, United States
| | - Pei Chen
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
| | - James M Harnly
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
| | - Jianghao Sun
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
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3
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Mahendran G, Rahman L. Ethnomedicinal, phytochemical and pharmacological updates on Peppermint (
Mentha × piperita
L.)—A review. Phytother Res 2020; 34:2088-2139. [DOI: 10.1002/ptr.6664] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/06/2020] [Accepted: 02/18/2020] [Indexed: 12/14/2022]
Affiliation(s)
- Ganesan Mahendran
- Plant Biotechnology Division, Central Institute of Medicinal and Aromatic Plants (CSIR‐CIMAP) Lucknow India
| | - Laiq‐Ur Rahman
- Plant Biotechnology Division, Central Institute of Medicinal and Aromatic Plants (CSIR‐CIMAP) Lucknow India
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4
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Patra JK, Das G, Lee S, Kang SS, Shin HS. Selected commercial plants: A review of extraction and isolation of bioactive compounds and their pharmacological market value. Trends Food Sci Technol 2018. [DOI: 10.1016/j.tifs.2018.10.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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5
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Kaiser S, Dias JC, Ardila JA, Soares FLF, Marcelo MCA, Porte LMF, Gonçalves C, Canova LDS, Pontes OFS, Sabin GP. High-throughput simultaneous quantitation of multi-analytes in tobacco by flow injection coupled to high-resolution mass spectrometry. Talanta 2018; 190:363-374. [PMID: 30172520 DOI: 10.1016/j.talanta.2018.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 07/31/2018] [Accepted: 08/01/2018] [Indexed: 12/19/2022]
Abstract
The high-throughput screening by flow injection coupled to high-resolution mass spectrometry (HTS-FIA-HRMS) is a powerful technique that enables the identification of several types of samples in a short period of time, either with qualitative or quantitative purposes. Sensory attributes of tobacco are affected by its chemical composition, and it is very important to quantify multi-analytes in a high-throughput methodology. HTS-FIA-HRMS coupled to multivariate analysis was used to create calibration models for 27 analytes, or group of compounds, of tobacco sensory interest. The models were validated by different approaches, including permutation test to avoid overfitting, evaluation of the equipment repeatability by control samples, reproducibility comparison of results from two different equipment and analysts, and with a blind test analysis. All tests demonstrated a good response to the proposed method. No statistical difference between the errors of both equipment was observed, with less than 7% error from the control samples, and a blind test error between 5.96% and 20.10%. The partial least squares (O-PLS) regression models were applied to 815 samples, and a principal component analysis (PCA) was performed from the predicted concentration values, aiming at the non-supervised classification based on tobacco type. We expect that this proposed methodology shows not only the applicability in tobacco samples, but also demonstrates a guideline to an efficient performance of multi-analytes target analysis using the flow injection mass spectrometry with reliable and robust validation steps.
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Affiliation(s)
- Samuel Kaiser
- British American Tobacco (BAT), Cachoeirinha, RS, Brazil
| | - Jailson C Dias
- British American Tobacco (BAT), Cachoeirinha, RS, Brazil
| | - Jorge A Ardila
- British American Tobacco (BAT), Cachoeirinha, RS, Brazil
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6
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Wang Y, Chen P. Comparison of Ion Mobility Fuzzy Chromatography Mass Spectrometric (imFCMS) Fingerprinting and FCMS Fingerprinting for Differentiation of American Cranberry Cultivars. JOURNAL OF ANALYSIS AND TESTING 2018. [DOI: 10.1007/s41664-018-0059-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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7
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Du L, Lu W, Cai Z(J, Bao L, Hartmann C, Gao B, Yu L(L. Rapid detection of milk adulteration using intact protein flow injection mass spectrometric fingerprints combined with chemometrics. Food Chem 2018; 240:573-578. [DOI: 10.1016/j.foodchem.2017.07.107] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 07/19/2017] [Accepted: 07/24/2017] [Indexed: 01/06/2023]
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8
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Lu W, Liu J, Gao B, Lv X, Yu L(L. Technical note: Nontargeted detection of adulterated plant proteins in raw milk by UPLC-quadrupole time-of-flight mass spectrometric proteomics combined with chemometrics. J Dairy Sci 2017; 100:6980-6986. [DOI: 10.3168/jds.2017-12574] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 05/15/2017] [Indexed: 11/19/2022]
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10
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Gao P, Li J, Li Z, Hao J, Zan L. Establishment and application of milk fingerprint by gel filtration chromatography. J Dairy Sci 2016; 99:9493-9501. [DOI: 10.3168/jds.2015-10655] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 08/21/2016] [Indexed: 11/19/2022]
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11
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Exploratory Chemometric Analysis on Source of Origin and Cultivar of Chinese Wolfberries Using Liquid Chromatograph−Mass Spectrometric and Flow Injection Mass Spectrometric (FIMS) Fingerprints. ACTA ACUST UNITED AC 2015. [DOI: 10.1021/bk-2015-1191.ch020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
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12
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Peppermint antioxidants revisited. Food Chem 2015; 176:72-81. [DOI: 10.1016/j.foodchem.2014.12.028] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Revised: 11/10/2014] [Accepted: 12/09/2014] [Indexed: 01/06/2023]
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13
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Lu W, Jiang Q, Shi H, Niu Y, Gao B, Yu LL. Partial least-squares-discriminant analysis differentiating Chinese wolfberries by UPLC-MS and flow injection mass spectrometric (FIMS) fingerprints. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2014; 62:9073-9080. [PMID: 25152955 DOI: 10.1021/jf502156n] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Lycium barbarum L. fruits (Chinese wolfberries) were differentiated for their cultivation locations and the cultivars by ultraperformance liquid chromatography coupled with mass spectrometry (UPLC-MS) and flow injection mass spectrometric (FIMS) fingerprinting techniques combined with chemometrics analyses. The partial least-squares-discriminant analysis (PLS-DA) was applied to the data projection and supervised learning with validation. The samples formed clusters in the projected data. The prediction accuracies by PLS-DA with bootstrapped Latin partition validation were greater than 90% for all models. The chemical profiles of Chinese wolfberries were also obtained. The differentiation techniques might be utilized for Chinese wolfberry authentication.
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Affiliation(s)
- Weiying Lu
- Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University , Shanghai 200240, China
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14
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Gao B, Qin F, Ding T, Chen Y, Lu W, Yu LL. Differentiating organically and conventionally grown oregano using ultraperformance liquid chromatography mass spectrometry (UPLC-MS), headspace gas chromatography with flame ionization detection (headspace-GC-FID), and flow injection mass spectrum (FIMS) fingerprints combined with multivariate data analysis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2014; 62:8075-8084. [PMID: 25050447 DOI: 10.1021/jf502419y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Ultraperformance liquid chromatography mass spectrometry (UPLC-MS), flow injection mass spectrometry (FIMS), and headspace gas chromatography (headspace-GC) combined with multivariate data analysis techniques were examined and compared in differentiating organically grown oregano from that grown conventionally. It is the first time that headspace-GC fingerprinting technology is reported in differentiating organically and conventionally grown spice samples. The results also indicated that UPLC-MS, FIMS, and headspace-GC-FID fingerprints with OPLS-DA were able to effectively distinguish oreganos under different growing conditions, whereas with PCA, only FIMS fingerprint could differentiate the organically and conventionally grown oregano samples. UPLC fingerprinting provided detailed information about the chemical composition of oregano with a longer analysis time, whereas FIMS finished a sample analysis within 1 min. On the other hand, headspace GC-FID fingerprinting required no sample pretreatment, suggesting its potential as a high-throughput method in distinguishing organically and conventionally grown oregano samples. In addition, chemical components in oregano were identified by their molecular weight using QTOF-MS and headspace-GC-MS.
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Affiliation(s)
- Boyan Gao
- Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University , Shanghai, China
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15
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Lu Y, Gao B, Chen P, Charles D, Yu LL. Characterisation of organic and conventional sweet basil leaves using chromatographic and flow-injection mass spectrometric (FIMS) fingerprints combined with principal component analysis. Food Chem 2014; 154:262-8. [PMID: 24518341 DOI: 10.1016/j.foodchem.2014.01.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2013] [Revised: 11/26/2013] [Accepted: 01/03/2014] [Indexed: 10/25/2022]
Abstract
Sweet basil, Ocimum basilicum, is one of the most important and wildly used spices and has been shown to have antioxidant, antibacterial, and anti-diarrheal activities. In this study, high performance liquid chromatographic (HPLC) and flow-injection mass spectrometric (FIMS) fingerprinting techniques were used to differentiate organic and conventional sweet basil leaf samples. Principal component analysis (PCA) of the fingerprints indicated that both HPLC and FIMS fingerprints could effectively detect the chemical differences in the organic and conventional sweet basil leaf samples. This study suggested that the organic basil sample contained greater concentrations of almost all the major compounds than its conventional counterpart on a per same botanical weight basis. The FIMS method was able to rapidly differentiate the organic and conventional sweet basil leaf samples (1min analysis time), whereas the HPLC fingerprints provided more information about the chemical composition of the basil samples with a longer analytical time.
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Affiliation(s)
- Yingjian Lu
- Department of Nutrition and Food Science, University of Maryland, College Park, 20742 MD, USA
| | - Boyan Gao
- Department of Nutrition and Food Science, University of Maryland, College Park, 20742 MD, USA; Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Pei Chen
- Food Composition and Methods Development Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, 20705 MD, USA.
| | - Denys Charles
- Frontier Natural Products Co-op, 3021 78th Street, Norway, IA 52318, USA
| | - Liangli Lucy Yu
- Department of Nutrition and Food Science, University of Maryland, College Park, 20742 MD, USA; Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.
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16
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Zhao J, Deng J, Chen Y, Li S. Advanced phytochemical analysis of herbal tea in China. J Chromatogr A 2013; 1313:2-23. [DOI: 10.1016/j.chroma.2013.07.039] [Citation(s) in RCA: 83] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2013] [Revised: 06/19/2013] [Accepted: 07/08/2013] [Indexed: 11/25/2022]
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17
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Zhao Y, Niu Y, Xie Z, Shi H, Chen P, Yu L(L. Differentiating leaf and whole-plant samples of di- and tetraploid Gynostemma pentaphyllum (Thunb.) Makino using flow-injection mass spectrometric fingerprinting method. J Funct Foods 2013. [DOI: 10.1016/j.jff.2013.04.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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18
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Gao B, Lu Y, Sheng Y, Chen P, Yu L(L. Differentiating organic and conventional sage by chromatographic and mass spectrometry flow injection fingerprints combined with principal component analysis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2013; 61:2957-63. [PMID: 23464755 PMCID: PMC3636576 DOI: 10.1021/jf304994z] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
High-performance liquid chromatography (HPLC) and flow injection electrospray ionization with ion trap mass spectrometry (FIMS) fingerprints combined with principal component analysis (PCA) were examined for their potential in differentiating commercial organic and conventional sage samples. The individual components in the sage samples were also characterized with an ultraperformance liquid chromatograph with a quadrupole-time-of-flight mass spectrometer (UPLC Q-TOF MS). The results suggested that both HPLC and FIMS fingerprints combined with PCA could differentiate organic and conventional sage samples effectively. FIMS may serve as a quick test capable of distinguishing organic and conventional sages in 1 min and could potentially be developed for high-throughput applications, whereas HPLC fingerprints could provide more chemical composition information with a longer analytical time.
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Affiliation(s)
- Boyan Gao
- Institute of Food and Nutraceutical Science, Bor S. Luh Food Safety Research Center, School of Agriculture and Biology, Shanghai Jiao Tong University
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742
| | - Yingjian Lu
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742
| | - Yi Sheng
- Institute of Food and Nutraceutical Science, Bor S. Luh Food Safety Research Center, School of Agriculture and Biology, Shanghai Jiao Tong University
| | - Pei Chen
- Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland 20705
| | - Liangli (Lucy) Yu
- Institute of Food and Nutraceutical Science, Bor S. Luh Food Safety Research Center, School of Agriculture and Biology, Shanghai Jiao Tong University
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742
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