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Thantar S, Mihailova A, Islam MD, Maxwell F, Hamed I, Vlachou C, Kelly SD. Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics. Talanta 2024; 273:125910. [PMID: 38492284 DOI: 10.1016/j.talanta.2024.125910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/06/2024] [Accepted: 03/09/2024] [Indexed: 03/18/2024]
Abstract
Paw San rice, also known as "Myanmar pearl rice", is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice. In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice. The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.
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Affiliation(s)
- Saw Thantar
- Department of Nuclear Technology, Kyaukse Technological University, Kyaukse, Myanmar
| | - Alina Mihailova
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria.
| | - Marivil D Islam
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria
| | - Florence Maxwell
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria
| | - Islam Hamed
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria
| | - Christina Vlachou
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria
| | - Simon D Kelly
- Food Safety and Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400, Vienna, Austria
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Qiu Z, Wu F, Hu H, Guo J, Wu C, Wang P, Ling J, Cui Y, Ye J, Fang G, Liu X. Deciphering the Microbiological Mechanisms Underlying the Impact of Different Storage Conditions on Rice Grain Quality. Foods 2024; 13:266. [PMID: 38254567 PMCID: PMC10814994 DOI: 10.3390/foods13020266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 12/28/2023] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Different storage conditions can influence microbial community structure and metabolic functions, affecting rice grains' quality. However, the microbiological mechanisms by which different storage conditions affect the quality of rice grains are not yet well understood. This study monitored the quality (the content of starch, protein, etc.) and microbial community structure of rice grains stored under different storage conditions with nitrogen gas atmosphere (RA: normal temperature, horizontal ventilation, RB: normal temperature, vertical ventilation, RC: quasi-low temperature, horizontal ventilation). The results revealed that the rice grains stored under condition RB exhibited significantly lower quality compared to condition RA and RC. In addition, under this condition, the highest relative abundance of Aspergillus (16.0%) and Penicillium (0.4%) and the highest levels of aflatoxin A (3.77 ± 0.07 μg/kg) and ochratoxin B1 (3.19 ± 0.05 μg/kg) were detected, which suggested a higher risk of fungal toxin contamination. Finally, co-occurrence network analysis was performed, and the results revealed that butyl 1,2-benzenedicarboxylate was negatively correlated (p < 0.05) with Moesziomyces and Alternaria. These findings will contribute to the knowledge base of rice storage management and guide the development of effective control measures against undesirable microbial activities.
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Affiliation(s)
- Zhuzhu Qiu
- College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China;
| | - Fenghua Wu
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
| | - Hao Hu
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
| | - Jian Guo
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
| | - Changling Wu
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
| | - Peng Wang
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
| | - Jiangang Ling
- Ningbo Academy of Agricultural Sciences, Ningbo 315000, China; (J.L.); (Y.C.)
| | - Yan Cui
- Ningbo Academy of Agricultural Sciences, Ningbo 315000, China; (J.L.); (Y.C.)
| | - Jing Ye
- Zhejiang Tongqu Grain Storage Co., Ltd., Quzhou 324000, China;
| | - Guanyu Fang
- College of Food & Health, Zhejiang A&F University, Hangzhou 311300, China; (F.W.); (H.H.); (J.G.); (C.W.); (P.W.)
| | - Xingquan Liu
- National Grain Industry (High-Quality Rice Storage in Temperate and Humid Region) Technology Innovation Center, Zhejiang A&F University, Hangzhou 311300, China
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3
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Dehelean A, Cristea G, Feher I, Hategan AR, Magdas DA. Differentiation of Transylvanian fruit distillates using supervised statistical tools based on isotopic and elemental fingerprint. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:1454-1463. [PMID: 36168887 DOI: 10.1002/jsfa.12241] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 09/06/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND The spirit drinks industry is one of the largest in the world. Fruit distillates require adequate analysis methods combined with statistical tools to build differentiation models, according to distinct criteria (geographical and botanical origin, producer's fingerprint, respectively). Over time a database of alcoholic beverage fingerprints can be generated, being very important for product safety and authenticity control. RESULTS To control the distillates' geographical origin, linear discriminant analysis (LDA) revealed that the cross-validation classification was correct for 88.2% of samples, but partial least squares discriminant analysis (PLS-DA) was slightly better suited for this purpose, with a correct classification rate of 91.2%. LDA effectiveness was proven for the trademark fingerprint differentiation, which was achieved at 93.5%, compared to 89.1% for PLS-DA. The principal predictors obtained by LDA were the same both for geographical origin and producer differentiation: B, δ13 C, Na, Cu, Ca and Be; highlighting the fact that in the production process of distillates each producer used fruits coming from the respective specific region. Through PLS-DA, some of the discrimination markers were the same for geographical origin and producer's identification, but others were completely specific: the rare earth elements Eu and Er only for geographical origin differentiation, and Cu solely as predictor for producer's identification. Regarding distillates' fruit variety, the correct discrimination rates of plum spirits from the rest were 84.2% for PLS-DA and 63% for LDA. CONCLUSION LDA and PLS-DA were suitable for differentiation models development of fruits spirits according to geographical region, producer and fruit variety based on isotopic and elemental fingerprint. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Adriana Dehelean
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Gabriela Cristea
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Ioana Feher
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Ariana Raluca Hategan
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Dana Alina Magdas
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
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Li Z, Song J, Ma Y, Yu Y, He X, Guo Y, Dou J, Dong H. Identification of aged-rice adulteration based on near-infrared spectroscopy combined with partial least squares regression and characteristic wavelength variables. Food Chem X 2022; 17:100539. [PMID: 36845513 PMCID: PMC9943763 DOI: 10.1016/j.fochx.2022.100539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/10/2022] [Accepted: 12/03/2022] [Indexed: 12/13/2022] Open
Abstract
The long-term storage of rice will inevitably be involved in the deterioration of edible quality, and aged rice poses a great threat to food safety and human health. The acid value can be employed as a sensitive index for the determination of rice quality and freshness. In this study, near-infrared spectra of three kinds of rice (Chinese Daohuaxiang, southern japonica rice, and late japonica rice) mixed with different proportions of aged rice were collected. The partial least squares regression (PLSR) model with different preprocessing was constructed to identify the aged rice adulteration. Meanwhile, a competitive adaptive reweighted sampling (CARS) algorithm was used to extract the optimization model of characteristic variables. The constructed CARS-PLSR model method could not only reduce greatly the number of characteristic variables required by the spectrum but also improve the identification accuracy of three kinds of aged-rice adulteration. As above, this study proposed a rapid, simple, and accurate detection method for aged-rice adulteration, providing new clues and alternatives for the quality control of commercial rice.
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Affiliation(s)
- Zhanming Li
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - Jiahui Song
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - Yinxing Ma
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - Yue Yu
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China,Corresponding authors.
| | - Xueming He
- College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China
| | - Yuanxin Guo
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - Jinxin Dou
- Academy of National Food and Strategic Reserves Administration, Beijing 100037, China
| | - Hao Dong
- College of Light Industry and Food Sciences, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China,Corresponding authors.
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5
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Feasibility study on prediction of the grain mixtures for black sesame paste recipe with different chemometric methods. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.114078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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6
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Geographical Origin Differentiation of Rice by LC–MS-Based Non-Targeted Metabolomics. Foods 2022; 11:foods11213318. [DOI: 10.3390/foods11213318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 10/09/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022] Open
Abstract
Many factors, such as soil, climate, and water source in the planting area, can affect rice taste and quality. Adulterated rice is common in the market, which seriously damages the production and sales of high-quality rice. Traceability analysis of rice has become one of the important research fields of food safety management. In this study, LC–MS-based non-targeted metabolomics technology was used to trace four rice samples from Heilongjiang and Jiangsu Provinces, namely, Daohuaxiang (DH), Huaidao No. 5 (HD), Songjing (SJ), and Changlixiang (CL). Results showed that the discrimination accuracy of the partial least squares discriminant analysis (PLS-DA) model was as high as 100% with satisfactory prediction ability. A total of 328 differential metabolites were screened, indicating significant differences in rice metabolites from different origins. Pathway enrichment analysis was carried out on the four rice samples based on the KEGG database to determine the three metabolic pathways with the highest enrichment degree. The main biochemical metabolic pathways and signal transduction pathways involved in differential metabolites in rice were obtained. This study provides theoretical support for the geographical origins of rice and elucidates the change mechanism of rice metabolic pathways, which can shed light on improving rice quality control.
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Liyanaarachchi G, Mahanama K, Somasiri H, Punyasiri P, Ranatunga M, Wijesena K, Weerasinghe W. Impact of seasonal, geographical and varietal variations on amino acid profile of Sri Lankan rice varieties (Oryza sativa L.). J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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8
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Rapid detection of adulteration of glutinous rice as raw material of Shaoxing Huangjiu (Chinese Rice Wine) by near infrared spectroscopy combined with chemometrics. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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9
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DNA-Based Tools to Certify Authenticity of Rice Varieties—An Overview. Foods 2022; 11:foods11030258. [PMID: 35159410 PMCID: PMC8834242 DOI: 10.3390/foods11030258] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/04/2022] [Accepted: 01/12/2022] [Indexed: 02/07/2023] Open
Abstract
Rice (Oryza sativa L.) is one of the most cultivated and consumed crops worldwide. It is mainly produced in Asia but, due to its large genetic pool, it has expanded to several ecosystems, latitudes and climatic conditions. Europe is a rice producing region, especially in the Mediterranean countries, that grow mostly typical japonica varieties. The European consumer interest in rice has increased over the last decades towards more exotic types, often more expensive (e.g., aromatic rice) and Europe is a net importer of this commodity. This has increased food fraud opportunities in the rice supply chain, which may deliver mixtures with lower quality rice, a problem that is now global. The development of tools to clearly identify undesirable mixtures thus became urgent. Among the various tools available, DNA-based markers are considered particularly reliable and stable for discrimination of rice varieties. This review covers aspects ranging from rice diversity and fraud issues to the DNA-based methods used to distinguish varieties and detect unwanted mixtures. Although not exhaustive, the review covers the diversity of strategies and ongoing improvements already tested, highlighting important advantages and disadvantages in terms of costs, reliability, labor-effort and potential scalability for routine fraud detection.
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10
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Rapid identification of the variety and geographical origin of Wuyou No.4 rice by fourier transform near-infrared spectroscopy coupled with chemometrics. J Cereal Sci 2021. [DOI: 10.1016/j.jcs.2021.103322] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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Kovacs Z, Muncan J, Ohmido N, Bazar G, Tsenkova R. Water Spectral Patterns Reveals Similarities and Differences in Rice Germination and Induced Degenerated Callus Development. PLANTS (BASEL, SWITZERLAND) 2021; 10:1832. [PMID: 34579366 PMCID: PMC8471901 DOI: 10.3390/plants10091832] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/29/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022]
Abstract
In vivo monitoring of rice (Oryza sativa L.) seed germination and seedling growth under general conditions in closed Petri dishes containing agar base medium at room temperature (temperature = 24.5 ± 1 °C, relative humidity = 76 ± 7% (average ± standard deviation)), and induced degenerated callus formation with plant growth regulator, were performed using short-wavelength near-infrared spectroscopy and aquaphotomics over A period of 26 days. The results of spectral analysis suggest changes in water absorbances due to the production of common metabolites, as well as increases in biomass and the sizes of the samples. Quantitative models built to predict the day of the development provided better accuracy for rice seedlings growth compared to callus formation. Eight common water bands were identified as presenting prominent changes in the absorbance pattern. The water matrix of only rice seedlings showed three developmental stages: firstly expressing a predominantly weakly hydrogen-bonded state, then a more strongly hydrogen-bonded state, and then, again, a weakly hydrogen-bonded state at the end. In rice callus induction and proliferation, no similar change in water absorbance pattern was observed. The presented findings indicate the potential of aquaphotomics for the in vivo detection of degeneration in cell development.
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Affiliation(s)
- Zoltan Kovacs
- Department of Measurements and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, Somlói út 14-16, 1118 Budapest, Hungary
| | - Jelena Muncan
- Biomeasurement Technology Laboratory, Graduate School of Agricultural Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Hyogo, Japan;
| | - Nobuko Ohmido
- Department of Human Environmental Science, Graduate School of Human Development and Environment, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Hyogo, Japan;
| | - George Bazar
- ADEXGO Ltd., Lapostelki u. 13, 8230 Balatonfüred, Hungary;
| | - Roumiana Tsenkova
- Biomeasurement Technology Laboratory, Graduate School of Agricultural Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Hyogo, Japan;
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Srinuttrakul W, Mihailova A, Islam MD, Liebisch B, Maxwell F, Kelly SD, Cannavan A. Geographical Differentiation of Hom Mali Rice Cultivated in Different Regions of Thailand Using FTIR-ATR and NIR Spectroscopy. Foods 2021; 10:foods10081951. [PMID: 34441727 PMCID: PMC8392001 DOI: 10.3390/foods10081951] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/16/2021] [Accepted: 08/18/2021] [Indexed: 11/20/2022] Open
Abstract
Although Hom Mali rice is considered the highest quality rice in Thailand, it is susceptible to adulteration and substitution. There is a need for rapid, low-cost and efficient analytical techniques for monitoring the authenticity and geographical origin of Thai Hom Mali rice. In this study, two infrared spectroscopy techniques, Fourier-transform infrared spectroscopy with attenuated total reflection (FTIR-ATR) and near-infrared (NIR) spectroscopy, were applied and compared for the differentiation of Thai Hom Mali rice from two geographical regions over two production years. The Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model, built using spectral data from the benchtop FTIR-ATR, achieved 96.97% and 100% correct classification of the test dataset for each of the production years, respectively. The OPLS-DA model, built using spectral data from the portable handheld NIR, achieved 84.85% and 86.96% correct classification of the test dataset for each of the production years, respectively. Direct NIR analysis of the polished rice grains (i.e., no sample preparation) was determined as reliable for analysis of ground rice samples. FTIR-ATR and NIR spectroscopic analysis both have significant potential as screening tools for the rapid detection of fraud issues related to the geographical origin of Thai Hom Mali rice.
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Affiliation(s)
- Wannee Srinuttrakul
- Research and Development Division, Thailand Institute of Nuclear Technology, Sai Mun, Ongkharak, Nakhon Nayok 26120, Thailand;
| | - Alina Mihailova
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
- Correspondence:
| | - Marivil D. Islam
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
| | - Beatrix Liebisch
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
| | - Florence Maxwell
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
| | - Simon D. Kelly
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
| | - Andrew Cannavan
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria; (M.D.I.); (B.L.); (F.M.); (S.D.K.); (A.C.)
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