[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"_public_publisher_byId_833c02c9-7751-4eb0-89ce-6d9b89b96f20":3,"_public_publication_all{\"sortAscending\":false,\"sortField\":\"updateTime\",\"page\":0,\"size\":10,\"facet\":true,\"searchKey\":\"publisherId:833c02c9-7751-4eb0-89ce-6d9b89b96f20,\"}":55},{"code":4,"data":5,"meta":22},"SUCCESS",{"id":6,"createTime":7,"updateTime":8,"relativeEntities":9,"slug":10,"properties":11,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":24,"manageAffiliations":25,"indexDatabases":26,"url":22,"thumbnailPath":22,"statistic":42,"gsStatistic":22,"type":54,"analyzePriority":22},"833c02c9-7751-4eb0-89ce-6d9b89b96f20","2024-04-07T12:22:41.150+00:00","2025-11-21T10:07:41.271+00:00",[],"Sensing-and-Instrumentation-for-Food-Quality-and-Safety",{"eissn":12,"issn":14,"title":16,"url":18},{"VOID":13},"19327587",{"VOID":15},"19329954",{"EN":17},"Sensing and Instrumentation for Food Quality and Safety",{"VOID":19},"https:\u002F\u002Flink.springer.com\u002Fjournal\u002F11694","PUBLISHER","PENDING",null,0,[],[],[27],{"id":28,"indexDatabase":29,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},"fd3c04b7-08ea-4f6e-8156-34474b54df1e",{"id":30,"createTime":22,"updateTime":22,"relativeEntities":31,"label":32,"description":34,"key":36,"publicationTags":37,"standard":22},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9",[],{"EN":33,"VI":33},"Scopus - Elsevier",{"EN":33,"VI":35},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[38],"SCOPUS","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F12100155511","2008-2013","NONE",{"impactFactor":23,"impactFactorByYear":43,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":45,"totalCitation":23,"totalCitationByYear":52,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":53,"hindexLast5Year":23,"hindex":23},{},79,{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},19,28,11,9,10,2,{},{},"JOURNAL",{"meta":56,"data":58},{"total":57},"90",[59,199,327,423,514,607,724,845,907,994],{"id":60,"createTime":61,"updateTime":62,"relativeEntities":63,"slug":64,"properties":65,"entityType":74,"verifyStatus":75,"verifyTime":62,"verifyNote":76,"languages":22,"translateLanguages":22,"viewCount":77,"primaryUrl":78,"fullTextUrl":22,"authors":79,"publicationType":168,"publisherRelationship":169,"citationCount":22,"citationInfo":22,"publishDate":195,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":197,"openAccess":22,"references":22,"isForceReanalyzing":198},"be703d8d-f78b-45f2-b539-edcd0e30c827","2023-12-27T00:48:57.625+00:00","2025-02-26T22:28:57.881+00:00",[],"Time-resolved-reflectance-spectroscopy-for-non-destructive-assessment-of-food-quality",{"abstract":66,"title":68,"references":70,"doi":72},{"EN":67},"In the majority of most food and feed, visible, and near infrared light undergoes multiple scattering events and the overall light distribution is determined more by scattering rather than absorption due to the microscopic spatial changes in the refractive index. Conventional steady state reflectance spectroscopy can provide information on light attenuation, which depends both on light absorption and light scattering, but cannot separate these two effects. In contrast, time-resolved reflectance spectroscopy (TRS) allows more detailed optical characterization of diffusive media in terms of their absorption coefficient and reduced scattering coefficient. From the assessment of the absorption and reduced scattering coefficients, information can then be derived on the composition and internal structure of the medium. The main advantages of the technique are the absolute non-invasiveness, the potentiality for non-contact measurements and the capacity to probe internal properties with no influence from the skin. In this work we review the physical and technical issues related to the use of TRS for non-destructive quality assessment of fruit and vegetable. A laboratory system for broadband TRS, based on tunable mode-locked lasers and fast micro-channel plate photomultiplier and a portable set-up for TRS measurements, based on pulsed diode lasers and compact metal-channel photomultiplier, are described. Results on broadband optical characterization of fruits and applications of TRS to the detection of internal defects in pears and to maturity assessment in nectarines are presented.",{"EN":69},"Time-resolved reflectance spectroscopy for non-destructive assessment of food quality",{"VOID":71},"V.A. McGlone, C.J. Clark, R.B. Jordan, Postharvest Biol. Technol. 46, 1–9 (2007)\nY. Liu, Y. Ying, X. Fu, H. Lu, J. Food Eng. 80, 986–989 (2007)\nG. Ma, X. Fu, Y. Zhou, Y. Ying, H. Xu, L. Xie, T. Lin, Spectrosc. Spectral Anal. 27, 907–910 (2007)\nM. Zude, B. Herold, J. Roger, V. Bellon-Maurel, S. Landahl, J. Food Eng. 77, 254–260 (2006)\nB.M. Nicolaï, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K.I. Theron, J. Lammertyn, Postharvest Biol. Technol. 46, 99–118 (2007)\nX. Fu, Y. Ying, H. Lu, H. Xu, J. Food Eng. 83, 317–323 (2007)\nS. Teerachaichayut, K.Y. Kil, A. Terdwongworakul, W. Thanapase, Y. Nakanishi, Postharvest Biol. Technol. 43, 202–206 (2007)\nD. Han, R. Tu, C. Lu, X. Liu, Z. Wen, Food Control 17, 604–608 (2006)\nB.M. NicolaI, E. LoÌtze, A. Peirs, N. Scheerlinck, K. Theron, Postharvest Biol. Technol. 40, 1–6 (2006)\nX. Fu, Y. Ying, H. Lu, H. Yu, H. Xu, Spectrosc. Spectral Anal. 27, 911–915 (2007)\nR. Lu, Y. Peng, J. Near Infrared Spectrosc. 13, 27–35 (2005)\nV.A. McGlone, H. Abe, S. Kawano, J. Near Infrared Spectrosc. 5, 83–89 (1997)\nA. Yodh, B. Chance, Phys. Today, 48, 34–40 (1995)\nR. Cubeddu, C. D’Andrea, A. Pifferi et al., Appl. Opt. 40, 538–543 (2001)\nR. Cubeddu, C. D’Andrea, A. Pifferi et al., Appl. Spectrosc. 55, 1368–1374 (2001)\nS. Feng, F.A. Zeng, B. Chance, Appl. Opt. 34, 3826–3837 (1995)\nW. Becker, Advanced Time-Correlated Single Photon Counting. (Springer, Berlin, 2005)\nA. Pifferi, A. Torricelli, P. Taroni, D. Comelli, A. Bassi, R. Cubeddu, Rev. Sci. Instrum. 78, 53–103 (2007)\nM.S. Patterson, B. Chance, B.C. Wilson, Appl. Opt. 28, 2331–2336 (1989)\nR.C. Haskell, L.O. Svaasand, T.T. Tsay, T.C. Feng, M.S. McAdams, B.J. Tromberg, J. Opt. Soc. Am. A 11, 2727–2741 (1994)\nD. Contini, F. Martelli, G. Zaccanti, Appl. Opt. 36, 4587–4599 (1997)\nR. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, in Fruit and Vegetable Processing, ed. by W. Jongen (CRC-Woodhead Publishing, Cambridge, 2002), pp. 150–169\nJ.R. Mourant, T. Fuselier, J. Boyer, T.M. Johnson, I.J. Bigio, Appl. Opt. 36, 949–957 (1997)\nM. Vanoli, P. Eccher Zerbini, M. Grassi et al., J. Fruit Orn. Plant Res. 14, 273–282 (2006)\nP. Eccher Zerbini, M. Grassi, R. Cubeddu, A. Pifferi, A. Torricelli, Postharvest Biol. Technol. 25, 87–99 (2002)\nM. Vanoli, P. Eccher Zerbini, M. Grassi et al., Acta Hortic. 682, 1481–1488 (2005)\nP. Eccher Zerbini, P. Cambiaghi, M. Grassi et al., Acta Hortic. 682, 965–972 (2005)\nP. Eccher Zerbini, M. Grassi, M. Fibiani et al., Acta Hortic. 604, 171–177 (2003)\nS. Jacob, M. Vanoli, M. Grassi et al., J. Fruit Orn Plant Res 14, 183–194 (2005)\nM. Vanoli, P. Eccher Zerbini, M. Grassi et al., in Advances in Plant Ethylene Research, ed. by A. Ramina, C. Chang, J. Giovannoni, H. Klee, P. Perata, E. Woltering. Proceedings of the 7th International Symposium on the Plant Hormone Ethylene. (Springer, Dorrdrecht, 2007), p. 219–221\nL.M.M. Tijskens, P. Eccher Zerbini, M. Vanoli et al., Int. J. Postharvest Technol. Innov. 1, 178–188 (2006)\nP. Eccher Zerbini, M. Vanoli, M. Grassi et al., Acta Hortic. 682, 1459–1464 (2005)\nP. Eccher Zerbini, M. Vanoli, M. Grassi et al., Postharvest Biol. Technol. 39, 223–232 (2006)\nL.M.M. Tijskens, P. Eccher Zerbini, R.B. Schouten et al., Postharvest Biol. Technol. 45, 204–213 (2007)\nA. Pifferi, P. Taroni, A. Torricelli, F. Messina, R. Cubeddu, G.M. Danesini, Opt. Lett. 28, 1138–1140 (2003)\nBecker & Hickl GmbH website: http:\u002F\u002Fwww.becker-hickl.de\nPicoQuant GmbH website: http:\u002F\u002Fwww.picoquant.com\nHamamatsu Photonics K.K. website: http:\u002F\u002Fwww.hamamatsu.com\nA. Bassi, J. Swartling, C. D’Andrea, A. Pifferi, A. Torricelli, R. Cubeddu, Opt. Lett. 29, 2405–2407 (2004)\nA. Bassi, A. Farina, C. D’Andrea, A. Pifferi, G. Valentini, R. Cubeddu, Opt. Exp. 15, 14482–14487 (2007)\nS.G. Leon-Saval, T.A. Birks, J. Bland-Hawthorn, M. Englund, Opt. Lett. 30, 2545–2527 (2005)\nF. Zappa, S. Tisa, A. Gulinatti, A. Gallivanoni, S. Cova, Opt. Lett. 30, 1327–1329 (2005)",{"VOID":73},"10.1007\u002Fs11694-008-9036-2","PUBLICATION","VERIFIED","Auto Verify",1,"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9036-2",[80,96,111,124,140,154],{"id":81,"sortIndex":23,"researcher":22,"roles":82,"affiliations":84,"properties":93,"displayName":95,"givenName":22,"familyName":22},"337d3827-ab4a-477c-9811-13d6ed997f29",[83],"AUTHOR",[85],{"id":86,"sortIndex":23,"affiliation":87,"properties":22},"7e2b1d68-ddef-4d7c-8255-5567450dbc07",{"id":86,"createTime":22,"updateTime":22,"relativeEntities":88,"slug":22,"properties":89,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":92,"statistic":22},[],{"title":90},{"VI":91},"Politecnico di Milano Dipartimento di Fisica, ULTRAS-INFM-CNR, Milan, Italy",[],{"title":94},{"VI":95},"Alessandro Torricelli",{"id":97,"sortIndex":77,"researcher":22,"roles":98,"affiliations":99,"properties":108,"displayName":110,"givenName":22,"familyName":22},"a5a2fad9-fbdc-474e-818a-abe15588545a",[83],[100],{"id":101,"sortIndex":23,"affiliation":102,"properties":22},"68a22bb6-03f8-4062-9c6a-20d873888435",{"id":101,"createTime":22,"updateTime":22,"relativeEntities":103,"slug":22,"properties":104,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":107,"statistic":22},[],{"title":105},{"VI":106},"Politecnico di Milano Dipartimento di Fisica, IFN-CNR, Milan, Italy",[],{"title":109},{"VI":110},"Lorenzo Spinelli",{"id":112,"sortIndex":51,"researcher":22,"roles":113,"affiliations":114,"properties":121,"displayName":123,"givenName":22,"familyName":22},"a0c9bb4a-e98e-48fe-8334-7cbd7a2cddda",[83],[115],{"id":86,"sortIndex":23,"affiliation":116,"properties":22},{"id":86,"createTime":22,"updateTime":22,"relativeEntities":117,"slug":22,"properties":118,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":120,"statistic":22},[],{"title":119},{"VI":91},[],{"title":122},{"VI":123},"Davide Contini",{"id":125,"sortIndex":126,"researcher":22,"roles":127,"affiliations":128,"properties":137,"displayName":139,"givenName":22,"familyName":22},"658d27ee-7c8f-48d2-9508-0222cbb57f4e",3,[83],[129],{"id":130,"sortIndex":23,"affiliation":131,"properties":22},"eecb4c5e-f8fd-49eb-8253-5e052b818409",{"id":130,"createTime":22,"updateTime":22,"relativeEntities":132,"slug":22,"properties":133,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":136,"statistic":22},[],{"title":134},{"VI":135},"CRA-IAA (Agricultural Research Council – Research Unit for Agro Food Industry), Milan, Italy",[],{"title":138},{"VI":139},"Maristella Vanoli",{"id":141,"sortIndex":142,"researcher":22,"roles":143,"affiliations":144,"properties":151,"displayName":153,"givenName":22,"familyName":22},"dd62cb9f-b596-4ee9-8df9-7bc2276ad7d0",4,[83],[145],{"id":130,"sortIndex":23,"affiliation":146,"properties":22},{"id":130,"createTime":22,"updateTime":22,"relativeEntities":147,"slug":22,"properties":148,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":150,"statistic":22},[],{"title":149},{"VI":135},[],{"title":152},{"VI":153},"Anna Rizzolo",{"id":155,"sortIndex":156,"researcher":22,"roles":157,"affiliations":158,"properties":165,"displayName":167,"givenName":22,"familyName":22},"133676e8-db8f-4673-8d55-3b84a3acf92c",5,[83],[159],{"id":130,"sortIndex":23,"affiliation":160,"properties":22},{"id":130,"createTime":22,"updateTime":22,"relativeEntities":161,"slug":22,"properties":162,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":164,"statistic":22},[],{"title":163},{"VI":135},[],{"title":166},{"VI":167},"Paola Eccher Zerbini","ARTICLE",{"url":78,"publisher":170,"properties":190},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":171,"slug":10,"properties":172,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":176,"manageAffiliations":177,"indexDatabases":178,"url":22,"thumbnailPath":22,"statistic":185,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":173,"title":174,"eissn":175},{"VOID":15},{"EN":17},{"VOID":13},[],[],[179],{"id":28,"indexDatabase":180,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":181,"label":182,"description":183,"key":36,"publicationTags":184,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":186,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":187,"totalCitation":23,"totalCitationByYear":188,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":189,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":191,"volume":193},{"VOID":192},"82-89",{"VOID":194},"2","2008-03-13",2008,[38],false,{"id":200,"createTime":201,"updateTime":202,"relativeEntities":203,"slug":204,"properties":205,"entityType":74,"verifyStatus":75,"verifyTime":202,"verifyNote":76,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":214,"fullTextUrl":22,"authors":215,"publicationType":168,"publisherRelationship":300,"citationCount":22,"citationInfo":22,"publishDate":325,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":326,"openAccess":22,"references":22,"isForceReanalyzing":198},"0383dfe0-8d52-4fb4-b509-b32f84522df2","2024-02-20T23:16:23.312+00:00","2025-02-26T16:02:26.459+00:00",[],"Partial-least-squares-analysis-of-near-infrared-hyperspectral-images-for-beef-tenderness-prediction",{"abstract":206,"title":208,"references":210,"doi":212},{"EN":207},"Tenderness is a primary determinant of consumer satisfaction of beef steaks. The objective of this study was to implement and test near-infrared (NIR) hyperspectral imaging to forecast 14-day aged, cooked beef tenderness from the hyperspectral images of fresh ribeye steaks (n = 319) acquired at 3–5 day post-mortem. A pushbroom hyperspectral imaging system (wavelength range: 900–1700 nm) with a diffuse-flood lighting system was developed. After imaging, steaks were vacuum-packaged and aged until 14 days postmortem. After aging, the samples were cooked and slice shear force (SSF) values were collected as a tenderness reference. After reflectance calibration, a Region-of-Interest (ROI) of 150 × 300 pixels at the center of longissimus muscle was selected. Partial least squares regression (PLSR) was carried out on each ROI image to reduce the dimension along the spectral axis. Gray-level textural co-occurrence matrix analysis with two quantization levels (64 and 256) was conducted on the PLSR bands to extract second-order statistical textural features. These features were then used in a canonical discriminant model to predict three beef tenderness categories, namely tender (SSF ≤ 205.80 N), intermediate (205.80 N \u003C SSF \u003C 254.80 N), and tough (SSF ≥ 254.80 N). The model with a quantization level of 256 performed better than the one with a quantization level of 64. This model correctly classified 242 out of 314 samples with an overall accuracy of 77.0%. Fat, protein, and water absorption bands were identified between 900 and 1700 nm. Our results show that NIR hyperspectral imaging holds promise as an instrument for forecasting beef tenderness.",{"EN":209},"Partial least squares analysis of near-infrared hyperspectral images for beef tenderness prediction",{"VOID":211},"USDA (1997) Available at: http:\u002F\u002Fwww.ams.usda.gov\u002Flsg\u002Fstand\u002Fstandards\u002Fbeef-car.pdf, Accessed on 9 Feb 2004\nR.C. Winger, C.J. Hagyard, in Quality Attributes and Their Measurement in Meat, Poultry and Fish Products. Advances in meat research series, eds. by A.M. Pearson, T.R. Dutson (Blackie Academic & Professional, London, UK, 1994) 9, 94\nS.J. Boleman, S.L. Boleman, R.K. Miller, et al., J. Anim. Sci. 75, 1521 (1997)\nJ.L. Lusk, J.A. Fox, T.C. Schroeder, J. Mintert, M. Koohmaraie, Am. J. Agric. Econ. 83, 539 (2001)\nS.D. Shackelford, T.L. Wheeler, M.K. Meade, J.O. Reagan, B.L. Byrnes, M. Koohmaraie, J. Anim. Sci. 79, 2605 (2001)\nD.M. Feuz, W.J. Umberger, C.R. Calkins, B. Sitz, J. Agric. Res. Econ. 29, 501 (2004)\nD.R. McKenna, D.L. Roebert, P.K. Bates, et al., J. Anim. Sci. 80, 1212 (2002)\nNAMP (John Wiley & Sons, New Jersey, NJ, 2007)\nL.E. Jeremiah, Food Res. Int. 29, 513 (1996)\nT.L. Wheeler, L.V. Cundiff, R.M. Koch, J. Anim. Sci. 72, 3145 (1994)\nC.L. Lorenzen, D.S. Hale, D.B. Griffin, et al., J. Anim. Sci. 71, 1495 (1993)\nS.L. Boleman, S.J. Boleman, W.W. Morgan, et al., J. Anim. Sci. 76, 96 (1998)\nJ.B. Morgan, J.W. Savell, D.S. Hale, R.K. Miller, D.B. Griffin, H.R. Cross, S.D. Shackelford, J. Anim. Sci. 69, 3274 (1991)\nJ.C. Brooks, J.B. Belew, D.B. Griffin, et al., J. Anim. Sci. 78, 1852 (2000)\nS.D. Shackelford, T.L. Wheeler, M. Koohmaraie, J. Anim. Sci. 77, 1474 (1999)\nD.J. Vote, K.E. Belk, J.D. Tatum, J.A. Scanga, G.C. Smith, J. Anim. Sci. 81, 457 (2003)\nD.M. Wulf, S.F. O’connor, J.D. Tatum, G.C. Smith, J. Anim. Sci. 75, 684 (1997)\nD.M. WulfJ, K. Page, J. Anim. Sci. 78, 2595 (2000)\nA.M. Wyle, R.C. Cannell, K.E. Belk, M. Goldberg, R. Rifle, G.C. Smith, Research Report (Department of Animal Science, Colorado State University, Fort Collins, CO, 1999)\nA.M. Wyle, D.J. Vote, D.L. Roeber, et al., J. Anim. Sci. 81, 441 (2003)\nJ. Li, J. Tan, P. Shatadal, ASAE Annual International Meeting, ASAE Paper #99–3158 (1999)\nJ. Li, J. Tan, P. Shatadal, Meat Sci. 57, 341 (2001)\nJ. Li, J. Tan, F.A. Martz, H. Heymann, Meat Sci. 53, 17 (1999)\nC. Zheng, D.W. Sun, L. Zheng, Trans. ASAE 49, 1447 (2006)\nM. Mitsumoto, S. Maeda, T. Mitsuhashi, S. Ozawa, J. Food Sci. 59, 1493 (1991)\nK.I. Hildrum, B.N. Nilsen, M. Mielnik, T. Naes, Meat Sci. 38, 67 (1994)\nK.I. Hildrum, T. Isaksson, T. Næs, B.N. Nilsen, M. Rødbotten, P. Lea, J. Near Infrared Spectrosc. 3, 81 (1995)\nR. Rødbotten, B.-H. Mevik, K.I. Hildrum, J. Near Infrared Spectrosc. 9, 199 (2001)\nB. Park, Y.R. Chen, W.R. Hruschka, S.D. Shackelford, M. Koohmaraie, J. Anim. Sci. 76, 2115 (1998)\nJ. Subbiah, G.A. Kranzler, SPIE International Symposium (2003)\nY. Liu, B.G. Lyon, W.R. Windham, C.E. Realini, Pringle, T.D.D.S. Duckett, Meat Sci. 65, 1107 (2003)\nB. Leroy, S. Lambotte, O. Dotreppe, H. Lecocq, L. Istasse, A. Clinquart, Meat Sci. 66, 45 (2003)\nJ.J. Xia, E.P. Berg, J.W. Lee, G. Yao, Meat Sci. 75, 78 (2006)\nR. Lu, Trans. ASAE 46, 523 (2003)\nX. Cheng, Y.R. Chen, Y. Tao, C.Y. Wang, M.S. Kim, A.M. Lefcourt, Trans. ASAE 47, 1313 (2004)\nM.S. Kim, A.M. Lefcourt, K. Chao, Y.R. Chen, I. Kim, D.E. Chan, Trans. ASAE 45, 2027 (2002)\nM.S. Kim, A.M. Lefcourt, Y.R. Chen, I. Kim, D.E. Chan, K. Chao, Trans. ASAE 45, 2039 (2002)\nB. Park, K.C. Lawrence, W.R. Windham, R.J. Buhr, Trans. ASAE 45, 2017 (2002)\nB. Park, S.C. Yoon, K.C. Lawrence, W.R. Windham, ASAE Annual International Meeting, ASAE Paper #04-3032 (2004)\nB. Park, S.C. Yoon, K.C. Lawrence, W.R. Windham, ASAE Annual International Meeting, ASAE Paper #05-3071 (2005)\nR.P. Cogdill, C.R. Hurdburgh, G.R. Rippke, Trans. ASAE 47, 311 (2004)\nM. Koohmaraie, Meat Sci. 36, 93 (1994)\nC.-J. Du, D.-W. Sun, Trans. ASAE 49, 441 (2006)\nB. Park, Y.R. Chen, W.R. Hruschka, S.D. Shackelford, M. Koohmaraie, Trans. ASAE 44, 609 (2001)\nK.C. Lawrence, B. Park, W.R. Windham, C. Mao, Trans. ASAE 46, 513 (2003)\nJ.S. Shenk, M.O. Westerhaus, Crop Sci. 31, 469 (1991)\nR.M. Haralick, K. Shanmugan, I. Dinstein, IEEE Trans. Syst. Man Cybern. SMC-3, 610 (1973)\nG. Konda Naganathan, L.M. Grimes, J. Subbiah, C.R. Calkins, ASAE Annual International Meeting, ASAE Paper #063036 (2006)\nS.D. Shackelford, T.L. Wheeler, M. Koohmaraie, Meat Sci. 69, 409 (2005)\nD.A. Burns, E.W. Ciurczak (2001) Handbook of near-infrared analysis\nJ.C. Paul, Sensing Instrum Food Qual Saf 30, 271 (1989)\nM.S. Kim, Y.R. Chen, B.K. Cho, K. Chao, C.C. Yang, A.M. Lefcourt, D. Chan, Sens. Instrum. Food Qual. 1, 151 (2007)",{"VOID":213},"10.1007\u002Fs11694-008-9051-3","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9051-3",[216,231,246,259,272,287],{"id":217,"sortIndex":23,"researcher":22,"roles":218,"affiliations":219,"properties":228,"displayName":230,"givenName":22,"familyName":22},"7202c889-3250-48d6-ad8d-3666d2f7f5b8",[83],[220],{"id":221,"sortIndex":23,"affiliation":222,"properties":22},"e5afb621-c5e5-424b-b2c2-714bffe94f08",{"id":221,"createTime":22,"updateTime":22,"relativeEntities":223,"slug":22,"properties":224,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":227,"statistic":22},[],{"title":225},{"VI":226},"Biological Systems Engineering, University of Nebraska, Lincoln, USA",[],{"title":229},{"VI":230},"Govindarajan Konda Naganathan",{"id":232,"sortIndex":77,"researcher":22,"roles":233,"affiliations":234,"properties":243,"displayName":245,"givenName":22,"familyName":22},"cf33f3e1-de8d-4bcf-af04-dd1d4b9c2808",[83],[235],{"id":236,"sortIndex":23,"affiliation":237,"properties":22},"3b27cb52-59b0-4b33-8453-31ca02193b06",{"id":236,"createTime":22,"updateTime":22,"relativeEntities":238,"slug":22,"properties":239,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":242,"statistic":22},[],{"title":240},{"VI":241},"Animal Science, University of Nebraska, Lincoln, USA",[],{"title":244},{"VI":245},"Lauren M. Grimes",{"id":247,"sortIndex":51,"researcher":22,"roles":248,"affiliations":249,"properties":256,"displayName":258,"givenName":22,"familyName":22},"74bbd387-c934-44c2-9c25-eb4b27b30cc4",[83],[250],{"id":221,"sortIndex":23,"affiliation":251,"properties":22},{"id":221,"createTime":22,"updateTime":22,"relativeEntities":252,"slug":22,"properties":253,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":255,"statistic":22},[],{"title":254},{"VI":226},[],{"title":257},{"VI":258},"Jeyamkondan Subbiah",{"id":260,"sortIndex":126,"researcher":22,"roles":261,"affiliations":262,"properties":269,"displayName":271,"givenName":22,"familyName":22},"2ea9742c-ff72-4892-95c4-d442c338d432",[83],[263],{"id":236,"sortIndex":23,"affiliation":264,"properties":22},{"id":236,"createTime":22,"updateTime":22,"relativeEntities":265,"slug":22,"properties":266,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":268,"statistic":22},[],{"title":267},{"VI":241},[],{"title":270},{"VI":271},"Chris R. Calkins",{"id":273,"sortIndex":142,"researcher":22,"roles":274,"affiliations":275,"properties":284,"displayName":286,"givenName":22,"familyName":22},"f5fd39d3-f538-4318-90da-494b9c4bc085",[83],[276],{"id":277,"sortIndex":23,"affiliation":278,"properties":22},"378be913-2e3a-4370-ac0e-0b8b15123910",{"id":277,"createTime":22,"updateTime":22,"relativeEntities":279,"slug":22,"properties":280,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":283,"statistic":22},[],{"title":281},{"VI":282},"Computer Science and Engineering, University of Nebraska, Lincoln, USA",[],{"title":285},{"VI":286},"Ashok Samal",{"id":288,"sortIndex":156,"researcher":22,"roles":289,"affiliations":290,"properties":297,"displayName":299,"givenName":22,"familyName":22},"32916e89-85a4-4270-936f-3f905e3fff36",[83],[291],{"id":221,"sortIndex":23,"affiliation":292,"properties":22},{"id":221,"createTime":22,"updateTime":22,"relativeEntities":293,"slug":22,"properties":294,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":296,"statistic":22},[],{"title":295},{"VI":226},[],{"title":298},{"VI":299},"George E. Meyer",{"url":214,"publisher":301,"properties":321},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":302,"slug":10,"properties":303,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":307,"manageAffiliations":308,"indexDatabases":309,"url":22,"thumbnailPath":22,"statistic":316,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":304,"title":305,"eissn":306},{"VOID":15},{"EN":17},{"VOID":13},[],[],[310],{"id":28,"indexDatabase":311,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":312,"label":313,"description":314,"key":36,"publicationTags":315,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":317,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":318,"totalCitation":23,"totalCitationByYear":319,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":320,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":322,"volume":324},{"VOID":323},"178-188",{"VOID":194},"2008-06-12",[38],{"id":328,"createTime":329,"updateTime":330,"relativeEntities":331,"slug":332,"properties":333,"entityType":74,"verifyStatus":75,"verifyTime":346,"verifyNote":76,"languages":22,"translateLanguages":347,"viewCount":23,"primaryUrl":349,"fullTextUrl":22,"authors":350,"publicationType":168,"publisherRelationship":394,"citationCount":22,"citationInfo":22,"publishDate":420,"publishYear":421,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":422,"openAccess":22,"references":22,"isForceReanalyzing":198},"607841c4-4979-4451-a47b-5492a77e58a8","2023-12-25T04:58:34.537+00:00","2025-02-25T12:48:45.699+00:00",[],"Effect-of-microwave-heating-on-the-near-infrared-spectra-and-on-the-prediction-accuracy-of-chemical-parameters-in-red-grape-homogenates",{"abstract":334,"title":337,"keywords":340,"references":342,"doi":344},{"EN":335,"VI":336},"This study reports the effect of microwaving on the chemical composition [pH, total soluble solids (TSS), dry matter (DM) and total anthocyanins extraction], and the visible (VIS) and (NIR) spectra of red grape homogenates. It was observed that microwaving red grape homogenates prior to analysis improved the NIR calibrations for total anthocyanins (SECV: 0.21–0.13 mg g−1) and TSS (SECV: 0.89–0.54 °Brix), however no improvements in the NIR calibrations for DM were observed. Microwaving red grape samples prior to NIR scanning also caused an increased in absorbance for samples heated for up to 3 min, particularly in those wavelengths associated with water (1400 nm and 1930 nm). The practical implication of this study is that microwaving of red grape samples prior to scanning did not improve the NIR calibration statistics for the most common chemical parameters measured in red grapes.","Nghiên cứu này báo cáo về ảnh hưởng của việc gia nhiệt bằng vi sóng lên thành phần hóa học [pH, tổng chất hòa tan (TSS), chất khô (DM) và tổng lượng anthocyanins chiết xuất], cũng như quang phổ khả kiến (VIS) và hồng ngoại gần (NIR) của các mẫu nho đỏ đồng nhất. Đã quan sát thấy rằng việc gia nhiệt bằng vi sóng các mẫu nho đỏ đồng nhất trước khi phân tích đã cải thiện các hiệu chuẩn NIR cho tổng lượng anthocyanins (SECV: 0,21–0,13 mg g−1) và TSS (SECV: 0,89–0,54 °Brix), tuy nhiên không có sự cải thiện nào trong các hiệu chuẩn NIR cho DM. Gia nhiệt bằng vi sóng các mẫu nho đỏ trước khi quét NIR cũng dẫn đến sự gia tăng độ hấp thụ cho các mẫu được đun nóng trong 3 phút, đặc biệt là ở các bước sóng liên quan đến nước (1400 nm và 1930 nm). Ý nghĩa thực tiễn của nghiên cứu này là việc gia nhiệt bằng vi sóng các mẫu nho đỏ trước khi quét không cải thiện các thông số thống kê hiệu chuẩn NIR cho các tham số hóa học phổ biến nhất được đo trong nho đỏ.",{"EN":338,"VI":339},"Effect of microwave heating on the near infrared spectra and on the prediction accuracy of chemical parameters in red grape homogenates","Ảnh hưởng của việc gia nhiệt bằng vi sóng lên phổ hồng ngoại gần và độ chính xác dự đoán của các tham số hóa học trong mẫu nho đỏ đồng nhất",{"VI":341},"nho đỏ, vi sóng, phổ hồng ngoại gần, anthocyanins, chất hòa tan",{"VOID":343},"E.R. Deaville, P.C. Flinn, Near infrared (NIR) spectroscopy: an alternative approach for the estimation of forage quality and voluntary intake, in Forage Evaluation in Ruminant Nutrition, ed. by D.I. Givens, E. Owen, R.F.E. Axford, H.M. Omedi (CABI Publishing, Wallingford, 2000), pp. 301–320\nI. Murray, I. Cowe, Sample preparation, in Near Infrared Spectroscopy in Agriculture, ed. by C.A. Roberts, J. Workman, J.B. Reeves (American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, Madison, 2004), pp. 75–115\nW. Cynkar, D. Cozzolino, R.G. Dambergs, L. Janik, M. Gishen, The effects of homogenisation method and freezing on the determination of quality parameters in red grape berries of Vitis vinifera. Aust. J. Grape Wine Res. 10, 236–242 (2004)\nM. Gishen, D. Cozzolino, R.G. Dambergs, Grape and wine analysis in the Australian wine industry—enhancing the power of spectroscopy with chemometrics. Aust. J. Grape Wine Res. 11, 296–305 (2005)\nI.L. Francis, P.B. Høj, R.G. Dambergs, M. Gishen, M. de Barros Lopes, I.S. Pretorius, P.W. Godden, P.A. Henschke, M. Herderich, E.J. Waters, Objective measures of grape quality—are they achievable? in Proceedings of Twelfth Australian Wine Industry Technical Conference, ed. by I.S. Pretorius, P. Williams, R. Blair (Melbourne, Victoria), pp. 85–90\nJ.A. Kennedy, C. Saucier, Y. Glories, Grape and wine phenolics: history and perspective. Am. J. Enol. Viticult. 57, 239–248 (2006)\nM. Krstic, G. Moulds, B. Panagiatopoulos, S. West, Growing Quality Grapes to Winery Specification, in Quality Measurement and Management Options for Grapegrowers, ed. by S. Collins (Winetitles, Adelaide, 2003), pp. 17–19\nR.G. Dambergs, D. Cozzolino, W.U. Cynkar, A. Kambouris, I.L. Francis, P.B. Høj, M. Gishen, The use of near infrared reflectance for grape quality measurement. Aust. Grapegrow. Winemak. J. 476, 69–76 (2003)\nD. Cozzolino, R.G. Dambergs, W. Cynkar, L. Janik, M. Gishen, Analysis of grape and wine by near infrared spectroscopy—a review. J. Near Infrared Spectrosc. 14, 279–289 (2006)\nC. Somers, The Wine Spectrum (Winetitles, Adelaide, 1998)\nC. Somers, M.E. Evans, Wine quality: correlations with colour density and anthocyanin equilibria in a group of young red wines. J. Sci. Food Agric. 25, 1369–1379 (1974)\nC. Arana, C. Jaren, J. Arazuri, Maturity, variety and origin determination in white grapes (Vitis Vinifera L.) using near infrared reflectance technology. J. Near Infrared Spectrosc. 13, 349–357 (2005)\nD. Cozzolino, R.G. Dambergs, W. Cynkar, L. Janik, M. Gishen, Effect of both homogenization and storage on the spectra of red grapes, and on the measurement of total anthocyanins, total soluble solids and pH by Vis-NIR spectroscopy. J. Near Infrared Spectrosc. 13, 213–223 (2005)\nD. Cozzolino, M.B. Esler, R.G. Dambergs, W.U. Cynkar, D. Boehm, I.L. Francis, M. Gishen, Prediction of colour and pH using a diode array spectrophotometer (400–1100 nm). J. Near Infrared Spectrosc. 12, 105–111 (2004)\nD. Cozzolino, M.J. Kwiatkowski, M. Parker, W.U. Cynkar, R.G. Dambergs, M. Gishen, M. Herderich, Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy. Anal. Chim. Acta 513, 73–78 (2004)\nR.G. Dambergs, D. Cozzolino, W. Cynkar, M. Gishen, The determination of red grape quality parameters using the LOCAL algorithm. J. Near Infrared Spectrosc. 14, 71–80 (2006)\nP. Iland, A. Ewart, J. Sitters, A. Markides, N. Bruer, Techniques for Chemical Analysis and Quality Monitoring During Winemaking (P. Iland Wine Promotions, Campbelltown, 2000)\nT. Naes, T. Isaksson, T. Fearn, T. Davies, A User-Friendly Guide to Multivariate Calibration and Classification (NIR Publications, Chichester, 2002)\nM. Otto, Chemometrics: statistics and Computer Application in Analytical Chemistry (Wiley-VCH, Chichester, 1999)\nH. Maeda, Y. Ozaki, M. Tanaka, N. Hayashi, T. Kojima, Discrimination of commercial natural mineral waters using near infrared spectroscopy and principal component analysis. J. Near Infrared Spectrosc. 3, 191–201 (1995)\nI. Noda, Progress in two-dimensional (2D) correlation spectroscopy. J. Mol. Struct. 799, 2–15 (2006)\nI. Noda, Advances in two-dimensional correlation spectroscopy. Vib. Spectrosc. 36, 143–165 (2004)\nV.H. Segtnan, K. Kvaalb, E.O. Rukkea, R.B. Schüllera, T. Isaksson, Rapid assessment of physico-chemical properties of gelatine using near infrared Spectroscopy. Food Hydrocoll. 17, 585–592 (2003)\nV.H. Segtnan, T. Isaksson, Temperature, sample and time dependent structural characteristics of gelatine gels studied by near infrared spectroscopy. Food Hydrocoll. 18, 1–11 (2004)\nM. Pinelo, A. Arnous, A.S. Meyer, Upgrading of grape skins: significance of plant cell-wall structural components and extraction techniques for phenol release. Trends Food Sci. Technol. 17, 579–590 (2006)\nI. Murray, Forage analysis by near infrared spectroscopy, in Sward Management Handbook, ed. by A. Davies, R.D. Baker, S.A. Grant, A.S. Laidlaw (British Grassland Society, UK, 1993), pp. 285–312\nC.G. Boeriu, T. Stolle-Smits, C. Van Dijk, Characterisation of cell wall pectins by near infrared spectroscopy. J. Near Infrared Spectrosc. 6, A299–A301 (1998)\nM.R. Sohn, R.K. Cho, J. Korean Soc. Horticult. Sci. 41, 65–70 (2000)\nP. Sirisomboon, M. Tanaka, S. Fujita, T. Kojima, Evaluation of pectin constituents of Japanese pear by near infrared spectroscopy. J. Food Eng. 78, 701–707 (2007)\nB.G. Osborne, T. Fearn, P.H. Hindle, Near Infrared Spectroscopy in Food Analysis (Longman Scientific and Technical, Essex, England, 1993)\nCh.E. Miller, in Near Infrared Technology in the Agricultural and Food Industries, ed. by P.C. Williams, K.H. Norris (American Association of Cereal Chemist, St. Paul, 2001), pp. 19–39\nH. Swierenga, F. Wülfert, O.E. de Noord, A.P. de Weijer, L.M.C. Smilde, Development of robust calibration models in near infra-red spectrometric applications. Anal. Chim. Acta 411, 121–125 (2000)",{"VOID":345},"10.1007\u002Fs11694-011-9116-6","2025-01-29T23:04:39.498+00:00",[348],"VI","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-011-9116-6",[351,366,379],{"id":352,"sortIndex":23,"researcher":22,"roles":353,"affiliations":354,"properties":363,"displayName":365,"givenName":22,"familyName":22},"a2137d4f-a912-4123-86f2-e61c8021aa87",[83],[355],{"id":356,"sortIndex":23,"affiliation":357,"properties":22},"26bb7a73-6bef-42af-b3c8-c538f01080ec",{"id":356,"createTime":22,"updateTime":22,"relativeEntities":358,"slug":22,"properties":359,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":362,"statistic":22},[],{"title":360},{"VI":361},"The Australian Wine Research Institute, Adelaide, Australia",[],{"title":364},{"VI":365},"D. Cozzolino",{"id":367,"sortIndex":77,"researcher":22,"roles":368,"affiliations":369,"properties":376,"displayName":378,"givenName":22,"familyName":22},"0a695a7d-821d-4a4d-8316-7cbd2c2221ed",[83],[370],{"id":356,"sortIndex":23,"affiliation":371,"properties":22},{"id":356,"createTime":22,"updateTime":22,"relativeEntities":372,"slug":22,"properties":373,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":375,"statistic":22},[],{"title":374},{"VI":361},[],{"title":377},{"VI":378},"W. U. Cynkar",{"id":380,"sortIndex":51,"researcher":22,"roles":381,"affiliations":382,"properties":391,"displayName":393,"givenName":22,"familyName":22},"f73ceea9-d508-464d-8849-79e6f6ac3b70",[83],[383],{"id":384,"sortIndex":23,"affiliation":385,"properties":22},"868b872f-bdfb-423b-adfd-c4fa62a266c4",{"id":384,"createTime":22,"updateTime":22,"relativeEntities":386,"slug":22,"properties":387,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":390,"statistic":22},[],{"title":388},{"VI":389},"Tasmanian Institute of Agricultural Research, University of Tasmania, Hobart, Australia",[],{"title":392},{"VI":393},"R. G. Dambergs",{"url":349,"publisher":395,"properties":415},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":396,"slug":10,"properties":397,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":401,"manageAffiliations":402,"indexDatabases":403,"url":22,"thumbnailPath":22,"statistic":410,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":398,"title":399,"eissn":400},{"VOID":15},{"EN":17},{"VOID":13},[],[],[404],{"id":28,"indexDatabase":405,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":406,"label":407,"description":408,"key":36,"publicationTags":409,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":411,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":412,"totalCitation":23,"totalCitationByYear":413,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":414,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":416,"volume":418},{"VOID":417},"97-103",{"VOID":419},"5","2011-07-30",2011,[38],{"id":424,"createTime":425,"updateTime":426,"relativeEntities":427,"slug":428,"properties":429,"entityType":74,"verifyStatus":75,"verifyTime":442,"verifyNote":76,"languages":22,"translateLanguages":443,"viewCount":23,"primaryUrl":444,"fullTextUrl":22,"authors":445,"publicationType":168,"publisherRelationship":487,"citationCount":22,"citationInfo":22,"publishDate":512,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":513,"openAccess":22,"references":22,"isForceReanalyzing":198},"49dd8cf3-2650-4a47-a471-418583d0e013","2024-01-21T10:15:27.159+00:00","2025-02-25T12:47:47.112+00:00",[],"Development-of-non-destructive-methods-to-evaluate-oyster-quality-by-electronic-nose-technology",{"abstract":430,"title":433,"keywords":436,"references":438,"doi":440},{"EN":431,"VI":432},"The effectiveness of two electronic nose (e-nose) systems to assess the quality of oysters was studied on live oysters stored at 4 and 7°C for 14 days. E-nose data were correlated with a trained sensory panel evaluation by quantitative description analysis and with aerobic plate count. Oysters stored at both temperatures exhibited varying degrees of microbial spoilage, with bacterial load reaching 107 CFU\u002Fg at day 7 for 7°C storage. Cyranose 320 e-nose system was capable of generating characterized smell prints to differentiate oyster qualities of varying age (100% separation). The validation results showed that Cyranose 320 can identify the quality of oysters in terms of storage time with 93% accuracy. Comparatively, the correct classification rate for VOCcheck e-nose was only 22%. Correlation of e-nose data with microbial counts suggested Cyranose 320 was able to predict the microbial quality of oysters. Correlation of sensory panel scores with e-nose data revealed that e-nose has demonstrated potential as a quality assessment tool by mapping varying degrees of oyster quality.","Độ hiệu quả của hai hệ thống mũi điện tử (e-nose) trong việc đánh giá chất lượng hàu đã được nghiên cứu trên hàu sống được lưu trữ ở 4 và 7°C trong 14 ngày. Dữ liệu từ e-nose được đối chiếu với đánh giá của một nhóm cảm quan được đào tạo thông qua phân tích mô tả định lượng và với số lượng vi khuẩn hiếu khí. Hàu được lưu trữ ở cả hai nhiệt độ cho thấy nhiều mức độ hư hỏng vi sinh vật khác nhau, với tải trọng vi khuẩn đạt 107 CFU\u002Fg vào ngày thứ 7 đối với việc lưu trữ ở 7°C. Hệ thống mũi điện tử Cyranose 320 có khả năng tạo ra các dấu hiệu mùi đã được phân loại để phân biệt chất lượng hàu theo độ tuổi khác nhau (phân tách 100%). Kết quả xác thực cho thấy Cyranose 320 có thể xác định chất lượng của hàu theo thời gian lưu trữ với độ chính xác 93%. So với đó, tỷ lệ phân loại đúng của e-nose VOCcheck chỉ đạt 22%. Sự tương quan giữa dữ liệu e-nose với số lượng vi sinh vật cho thấy Cyranose 320 có khả năng dự đoán chất lượng vi sinh vật của hàu. Sự tương quan giữa điểm số của nhóm cảm quan với dữ liệu e-nose tiết lộ rằng e-nose đã thể hiện tiềm năng như một công cụ đánh giá chất lượng bằng cách lập bản đồ các mức độ chất lượng hàu khác nhau.",{"EN":434,"VI":435},"Development of non-destructive methods to evaluate oyster quality by electronic nose technology","Phát triển các phương pháp không phá hủy để đánh giá chất lượng hàu bằng công nghệ mũi điện tử",{"VI":437},"hàu, mũi điện tử, chất lượng thực phẩm, lưu trữ vi sinh vật, phân tích cảm quan",{"VOID":439},"C. Gorga, L.J. Ronsivalli, Mar. Fish. Rev. 44(2), 11–16 (1982)\nC.E. Hebard, G.J. Flick, R.E. Martin, in Chemistry and Biochemistry of Marine Food Product, ed. by R.E. Martin, G.J. Flick, C.E. Hebard, D.R. Ward (AVI Pub. Co., Westport, 1982), pp. 149–304\nP.B. Johnsen, C.A. Kelly, J. Sens. Stud. 4(3), 189–199 (1990)\nP.B. Johnsen, S.W. Lloyd, Can. J. Fish. Aquat. Sci. 49(11), 2406–2411 (1992)\nW.X. Du, C.M. Lin, T.S. Huang, J. Kim, M.R. Marshall, C.I. Wei, J. Food Sci. 67(1), 307–313 (2002)\nT.C. Pearce, S.S. Schiffman, H.T. Nagle, J.W. Cardner, Handbook of Machine Olfaction. Electronic Nose Technology (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, 2003)\nÖ. Tokuşoğlu, M.Ö. Balaban, J. Shellfish. Res. 23(1), 143–148 (2004)\nF. Korel, D.A. Luzuriaga, M.Ö. Balaban, J. Aquat. Food Prod. Technol. 10(1), 3–18 (2001a)\nF. Korel, D.A. Luzuriaga, M.Ö. Balaban, J. Food Sci. 66(7), 1018–1024 (2001b)\nW.X. Du, J. Kim, J.A. Cornell, T.S. Huang, M.R. Marshall, C.I. Wei, J. Food Protect. 64(12), 2027–2036 (2001a)\nW.X. Du, J. Kim, T.S. Huang, J.A. Cornell, M.R. Marshall, C.I. Wei, J. Agric. Food Chem. 49(1), 527–534 (2001b)\nD.A. Luzuriaga, M.Ö. Balaban, in Electronic Noses and Sensor Array Based Systems, ed. by W.J. Hurst, (Technomic Publishing Co., Lancaster, 1999a), pp. 177–184\nD.A. Luzuriaga, M.Ö. Balaban, in Electronic Noses and Sensor Array Based Systems, ed. by W.J. Hurst (Technomic Publishing Co., Lancaster, 1999b), pp. 162–169\nM. Holmberg, F.S.H. Winquist, I. Lundtrom, An electronic nose used for food control. Alpha M. O. S. 1st international symposium on olfaction and electronic noses, Toulouse, 1994\nB.E. Perkins, Aqua-cultured Oysters Products: Inspection, Quality, Handling, Storage, Safety. Available at http:\u002F\u002Fgovdocs.aquake.org\u002Fcgi\u002Fcontent\u002Fabstract\u002F2003\u002F724\u002F7240130. Accessed 2 Jan 2008, (1997)\nFDA. Bacteriological Analytical Manual Online, Aerobic Plate Count. Available athttp:\u002F\u002Fvm.cfsan.fda.gov\u002F~ebam\u002Fbam-3.html. Accessed 28 June 2004, (2001)\nH. He, R.M. Adams, D.F. Farkas, M.T. Morrissey, J. Food Sci. 67(2), 640–645 (2002)\nP.N. Bartlett, J.M. Elliott, J.W. Gardner, Food Technol. 51(12), 44–48 (1997)\nICMSF, Microorganisms in Foods 2: Sampling for Microbiological Analysis: Principles and Specific Applications, 2nd edn. (University of Toronto Press, Toronto, 1986)\nCFR, Code of Federal Regulations. Title 50, Wildlife and Fisheries Part 265 (The Office of the Federal Register, National Archives and Records Administration, U.S. Government Printing Office, Washington, 1997)",{"VOID":441},"10.1007\u002Fs11694-008-9034-4","2025-01-30T00:21:38.772+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9034-4",[446,461,474],{"id":447,"sortIndex":23,"researcher":22,"roles":448,"affiliations":449,"properties":458,"displayName":460,"givenName":22,"familyName":22},"3b14f769-16de-4460-9dd8-693e68469435",[83],[450],{"id":451,"sortIndex":23,"affiliation":452,"properties":22},"7cf73e97-62c2-4b29-b204-e571108433ea",{"id":451,"createTime":22,"updateTime":22,"relativeEntities":453,"slug":22,"properties":454,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":457,"statistic":22},[],{"title":455},{"VI":456},"Biological Systems Engineering Department, Virginia Tech, Blacksburg, USA",[],{"title":459},{"VI":460},"Xiaopei Hu",{"id":462,"sortIndex":77,"researcher":22,"roles":463,"affiliations":464,"properties":471,"displayName":473,"givenName":22,"familyName":22},"c98ad6d1-7b47-47d5-92ca-898056ff25a0",[83],[465],{"id":451,"sortIndex":23,"affiliation":466,"properties":22},{"id":451,"createTime":22,"updateTime":22,"relativeEntities":467,"slug":22,"properties":468,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":470,"statistic":22},[],{"title":469},{"VI":456},[],{"title":472},{"VI":473},"ParameswaraKumar Mallikarjunan",{"id":475,"sortIndex":51,"researcher":22,"roles":476,"affiliations":477,"properties":484,"displayName":486,"givenName":22,"familyName":22},"830c8b8a-fdd7-40ca-b43d-5755ef896af0",[83],[478],{"id":451,"sortIndex":23,"affiliation":479,"properties":22},{"id":451,"createTime":22,"updateTime":22,"relativeEntities":480,"slug":22,"properties":481,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":483,"statistic":22},[],{"title":482},{"VI":456},[],{"title":485},{"VI":486},"David Vaughan",{"url":444,"publisher":488,"properties":508},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":489,"slug":10,"properties":490,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":494,"manageAffiliations":495,"indexDatabases":496,"url":22,"thumbnailPath":22,"statistic":503,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":491,"title":492,"eissn":493},{"VOID":15},{"EN":17},{"VOID":13},[],[],[497],{"id":28,"indexDatabase":498,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":499,"label":500,"description":501,"key":36,"publicationTags":502,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":504,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":505,"totalCitation":23,"totalCitationByYear":506,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":507,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":509,"volume":511},{"VOID":510},"51-57",{"VOID":194},"2008-02-20",[38],{"id":515,"createTime":516,"updateTime":517,"relativeEntities":518,"slug":519,"properties":520,"entityType":74,"verifyStatus":75,"verifyTime":534,"verifyNote":76,"languages":22,"translateLanguages":535,"viewCount":23,"primaryUrl":536,"fullTextUrl":22,"authors":537,"publicationType":168,"publisherRelationship":583,"citationCount":22,"citationInfo":22,"publishDate":604,"publishYear":605,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":606,"openAccess":22,"references":22,"isForceReanalyzing":198},"7756e746-01d3-4cd9-a56a-70a6b357de94","2024-04-08T10:41:09.327+00:00","2025-02-25T12:46:50.179+00:00",[],"Analysis-of-calcium-in-milk-using-an-embedded-system",{"abstract":521,"title":524,"keywords":527,"references":530,"doi":532},{"EN":522,"VI":523},"The objective of the present work is to design and implement a low cost PIC18F452 microcontroller based instrument for the measurement of calcium in milk samples using Light Emitting Diode (LED) as source and photodiode as detector. The developed instrument measures the absorbance, calculates the concentration and displays the results in Liquid Crystal Display (LCD). The principle of the measurement is based on the reaction between calcium and Ortho Cresolphthalein Complexone (OCPC) reagent in alkaline medium to form purple complex with maximum absorption at 570 nm. Algorithm is developed to monitor and control the process sequences and transmit data to PC via serial communication module using an RS232 protocol. Statistical analyses are carried out to evaluate the performance characteristics of the developed instrument and compared with the conventional instrument. Linear calibration curve is obtained between 0 and 5.0 mmol L−1 and lower limit of detection is 0.05 mmol L−1. The developed system shows the good performance and the results are in good agreement with the current clinical spectrophotometric method at 96% of confidence level.","Mục tiêu của nghiên cứu này là thiết kế và triển khai một thiết bị giá rẻ dựa trên vi điều khiển PIC18F452 để đo lường hàm lượng canxi trong mẫu sữa, sử dụng Diode Phát Quang (LED) làm nguồn sáng và photodiode làm cảm biến. Thiết bị được phát triển có khả năng đo độ hấp thụ, tính toán nồng độ và hiển thị kết quả trên Màn hình R рhỏlọwọ (LCD). Nguyên tắc đo lường dựa trên phản ứng giữa canxi và thuốc thử Ortho Cresolphthalein Complexone (OCPC) trong môi trường kiềm để tạo thành phức màu tím với độ hấp thụ tối đa ở 570 nm. Thuật toán được phát triển để theo dõi và điều khiển chu trình đo lường và truyền dữ liệu đến máy tính qua mô-đun giao tiếp nối tiếp sử dụng giao thức RS232. Các phân tích thống kê được thực hiện để đánh giá đặc tính hiệu suất của thiết bị đã phát triển và so sánh với thiết bị thông thường. Đường cong hiệu chuẩn tuyến tính đạt được trong khoảng từ 0 đến 5,0 mmol L−1 và giới hạn phát hiện thấp nhất là 0,05 mmol L−1. Hệ thống đã phát triển cho thấy hiệu suất tốt và các kết quả đạt được có sự tương đồng cao với phương pháp quang phổ lâm sàng hiện tại ở mức độ tin cậy 96%.",{"EN":525,"VI":526},"Analysis of calcium in milk using an embedded system","Phân tích canxi trong sữa bằng hệ thống nhúng",{"EN":528,"VI":529},"","canxi, sữa, vi điều khiển, thiết bị đo lường, phương pháp quang phổ, Ortho Cresolphthalein Complexone",{"VOID":531},"K.-L. Chen, S.-J. Jiangm, Determination of calcium, iron and zinc in milk powder by reaction cell inductively coupled plasma mass spectrometry. Anal. Chim. Acta 470, 223–228 (2002)\nA. Kamchan, P. Puwastien, P.P. Sirichakwal, R. Kongkachuichai, In vitro calcium bioavailability of vegetables, legumes and seeds. J. Food Compost. Anal. 17, 311–320 (2004)\nInstitute of Medicine, Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D and Fluoride (National Academy Press, Washington, DC, 1997)\nP. Campins-Fal, J. Verdti-Andrks, F. Bosch-Reig, Evaluation and elimination of the blank bias error using the H-point standard additions method (HPSAM) in the simultaneous spectrophotometric determination of two analytes. Anal. Chim. Acta 348, 39–49 (1997)\nPIC18F452 microcontroller data sheet. www.microchip.com\nJ.F. Van Staden, R.E. Taljaard, Determination of calcium in water, urine and pharmaceutical samples by sequential injection analysis. Anal. Chim. Acta 323, 75–85 (1996)\nC.C. Oliveira, R.P. Sartini, E.A.G. Zagatto, Microwave-assisted sample preparation in sequential injection: spectrophotometric determination of magnesium, calcium, and iron in food. Anal. Chim. Acta 413, 41–48 (2000)\nA. Afkhami, T. Madrakian, M. Abbasi-Tarighat, Simultaneous determination of calcium, magnesium, and zinc in different foodstuffs and pharmaceutical samples with continuous wavelet transforms. Food Chem. 109, 660–669 (2008)\nF.A.A. Matias, M.M.D.C. Vila, M. Tubino, A simple device for quantitative colorimetric diffuse reflectance measurement. Sens. Actuators B 88, 60–66 (2003)\nA.E. Moe, S. Marx, N. Banani, M. Liu, B. Marquardt, D.M. Wilson, Improvement in LED-based fluorescence analysis system. Sens. Actuators B 111–112, 230–241 (2005)",{"VOID":533},"10.1007\u002Fs11694-010-9102-4","2025-01-31T16:47:18.484+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-010-9102-4",[538,553,568],{"id":539,"sortIndex":23,"researcher":22,"roles":540,"affiliations":541,"properties":550,"displayName":552,"givenName":22,"familyName":22},"ee1edad0-2743-4d64-aacf-6d32046b3383",[83],[542],{"id":543,"sortIndex":23,"affiliation":544,"properties":22},"b583e184-a389-4fa7-8c15-53cb19ce3759",{"id":543,"createTime":22,"updateTime":22,"relativeEntities":545,"slug":22,"properties":546,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":549,"statistic":22},[],{"title":547},{"VI":548},"Department of Electronics & Instrumentation Engineering, SASTRA University, Thanjavur, India",[],{"title":551},{"VI":552},"P. Neelamegam",{"id":554,"sortIndex":77,"researcher":22,"roles":555,"affiliations":556,"properties":565,"displayName":567,"givenName":22,"familyName":22},"78b79047-4ff5-4bd8-a522-01102a34caf2",[83],[557],{"id":558,"sortIndex":23,"affiliation":559,"properties":22},"f741528a-755b-47b9-9292-0200403ae7db",{"id":558,"createTime":22,"updateTime":22,"relativeEntities":560,"slug":22,"properties":561,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":564,"statistic":22},[],{"title":562},{"VI":563},"PG Department of Electronics, St. Joseph’s College (Autonomous), Tiruchirappalli, India",[],{"title":566},{"VI":567},"A. Jamaludeen",{"id":569,"sortIndex":51,"researcher":22,"roles":570,"affiliations":571,"properties":580,"displayName":582,"givenName":22,"familyName":22},"1757ed6b-c22d-40b7-9728-655805abaad3",[83],[572],{"id":573,"sortIndex":23,"affiliation":574,"properties":22},"844d0b51-b5b1-4f61-8595-603c84c75cdf",{"id":573,"createTime":22,"updateTime":22,"relativeEntities":575,"slug":22,"properties":576,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":579,"statistic":22},[],{"title":577},{"VI":578},"PG and Research Department of Physics, Nehru Memorial College (Autonomous), Puthanampatti, Tiruchirappalli, India",[],{"title":581},{"VI":582},"A. Rajendran",{"url":22,"publisher":584,"properties":22},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":585,"slug":10,"properties":586,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":590,"manageAffiliations":591,"indexDatabases":592,"url":22,"thumbnailPath":22,"statistic":599,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":587,"title":588,"eissn":589},{"VOID":15},{"EN":17},{"VOID":13},[],[],[593],{"id":28,"indexDatabase":594,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":595,"label":596,"description":597,"key":36,"publicationTags":598,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":600,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":601,"totalCitation":23,"totalCitationByYear":602,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":603,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},"2010-09-11",2010,[38],{"id":608,"createTime":609,"updateTime":610,"relativeEntities":611,"slug":612,"properties":613,"entityType":74,"verifyStatus":75,"verifyTime":626,"verifyNote":76,"languages":22,"translateLanguages":627,"viewCount":23,"primaryUrl":628,"fullTextUrl":22,"authors":629,"publicationType":168,"publisherRelationship":697,"citationCount":22,"citationInfo":22,"publishDate":722,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":723,"openAccess":22,"references":22,"isForceReanalyzing":198},"b2901156-ff08-4674-a69f-e2a81a3f47fe","2024-01-15T07:48:18.832+00:00","2025-02-25T12:45:53.416+00:00",[],"Imaging-system-with-modified-pressure-chamber-for-crack-detection-in-shell-eggs",{"abstract":614,"title":617,"keywords":620,"references":622,"doi":624},{"EN":615,"VI":616},"To detect checks and\u002For cracks in shell eggs, the egg industry is using high-speed acoustic systems. Prior to shipment, human graders candle a small subset of eggs to ensure that the high-speed systems are operating within specifications for a given grade of egg (e.g., Grade A large eggs). In addition to visual inspection, graders also listen for a dull, flat sound as an indicator of a crack when tapping eggs together. However, very small cracks, or micro-cracks can go undetected by the human graders. A method to detect egg checks\u002Fcracks with an imaging camera was developed. The system consisted of an imaging camera positioned above a clear inspection chamber that housed an egg and was illuminated from underneath. The chamber was designed so that a short, quick vacuum could be pulled to enhance the crack detection. High-resolution monochromatic images were collected at atmospheric pressure and under negative pressure. The negative pressure gradient was used to briefly open any existing cracks without inducing any new cracks in an intact egg. Initially, eggs were manually rotated three times to image the whole surface of the egg. The ratio of a negative-pressure image divided by an atmospheric-pressure image was used to highlight the cracks and simple image processing was used to identify a crack. A total of 80 cracked and 80 intact eggs were imaged with the system. Only one cracked egg was not detected, and this was because the crack was located on the air-cell end of the egg and was not visible by the camera. Thus, the system was 98.75% accurate in identifying cracked eggs and 100% accurate in identifying intact eggs. This initial phase of the research was successful and the system is being scaled up to image multiple eggs at a time.","Để phát hiện các vết nứt và\u002Fhoặc các vết kiểm tra trong trứng, ngành công nghiệp trứng đang sử dụng các hệ thống âm thanh tốc độ cao. Trước khi giao hàng, nhân viên kiểm tra sẽ chiếu đèn vào một mẫu nhỏ trứng để đảm bảo rằng các hệ thống tốc độ cao hoạt động theo thông số kỹ thuật của một loại trứng nhất định (ví dụ: trứng lớn loại A). Ngoài việc kiểm tra bằng mắt, nhân viên cũng lắng nghe âm thanh trầm, phẳng như là chỉ báo cho một vết nứt khi gõ các quả trứng lại với nhau. Tuy nhiên, những vết nứt rất nhỏ hay micro-crack có thể không được phát hiện bởi nhân viên kiểm tra. Một phương pháp để phát hiện các vết nứt\u002Ftrứng bị kiểm tra bằng camera hình ảnh đã được phát triển. Hệ thống bao gồm một camera hình ảnh được đặt ở trên một buồng kiểm tra trong suốt, nơi chứa một quả trứng và được chiếu sáng từ phía dưới. Buồng được thiết kế sao cho một chân không ngắn, nhanh có thể được kéo để tăng cường việc phát hiện vết nứt. Các hình ảnh đơn sắc độ phân giải cao được thu thập ở áp suất khí quyển và dưới áp suất âm. Độ chênh lệch áp suất âm được sử dụng để mở tạm thời bất kỳ vết nứt nào hiện có mà không gây ra bất kỳ vết nứt mới nào trong một quả trứng nguyên vẹn. Ban đầu, trứng được xoay ba lần bằng tay để lấy hình ảnh toàn bộ bề mặt của quả trứng. Tỷ lệ của hình ảnh áp suất âm chia cho hình ảnh áp suất khí quyển được sử dụng để làm nổi bật các vết nứt, và quy trình xử lý hình ảnh đơn giản được sử dụng để xác định một vết nứt. Tổng cộng 80 quả trứng bị nứt và 80 quả trứng nguyên vẹn đã được hình ảnh hóa bằng hệ thống. Chỉ có một quả trứng bị nứt không được phát hiện, và điều này là do vết nứt nằm ở đầu không khí của quả trứng và không nhìn thấy được bởi camera. Do đó, hệ thống đạt độ chính xác 98,75% trong việc xác định các quả trứng bị nứt và 100% trong việc xác định các quả trứng nguyên vẹn. Giai đoạn ban đầu của nghiên cứu này đã thành công và hệ thống đang được mở rộng để lấy hình ảnh nhiều quả trứng cùng một lúc.",{"EN":618,"VI":619},"Imaging system with modified-pressure chamber for crack detection in shell eggs","Hệ thống hình ảnh với buồng áp suất điều chỉnh để phát hiện nứt trong trứng vỏ",{"VI":621},"kiểm tra trứng, phát hiện nứt, hệ thống hình ảnh, áp suất âm, trứng vỏ",{"VOID":623},"U.S. Dept. Agric., Agric. Market. Serv., AMS 56 (7-20-00)\nU.S. Dept. Agric., 7CFR part 56.4(b) (2006)\nB. DeKetelaere, F. Bamelis, B. Kemps, E. Decuypere, J. DeBaerdemaeker, World Poultry Sci. J. 60, 289 (2004)\nG.N. Bliss, U.S. Patent 3,744,299 (1973)\nP. Coucke, PhD. thesis, Katholieke Universitet, Leuven, 1998\nB. DeKetelaere, P. Coucke, J. DeBaerdemaeker, J. Agric. Eng. Res. 76, 157 (2000)\nR.T. Elster, J.W. Goodrum, Trans. ASAE 34, 307 (1991)\nJ.W. Goodrum, R.T. Elster, Trans. ASAE 35, 1323 (1992)\nJ. Lin, Y. Lin, M. Hsieh, C. Yang, Proceedings of the ASAE Annual International Meeting, Sacramento, 2001 (ASAE, St. Joseph, MI, 2001) 01-6032\nK.C. Lawrence, W.R. Windham, B. Park, R.J. Buhr, J. Near Infrared Spectrosc. 11, 269 (2003)",{"VOID":625},"10.1007\u002Fs11694-008-9039-z","2025-02-02T14:17:34.805+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9039-z",[630,645,658,671,684],{"id":631,"sortIndex":23,"researcher":22,"roles":632,"affiliations":633,"properties":642,"displayName":644,"givenName":22,"familyName":22},"e0b27517-f17d-436e-84fd-01128f966c08",[83],[634],{"id":635,"sortIndex":23,"affiliation":636,"properties":22},"a39c0d3c-e1c6-4d4c-8630-444b586a9ff6",{"id":635,"createTime":22,"updateTime":22,"relativeEntities":637,"slug":22,"properties":638,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":641,"statistic":22},[],{"title":639},{"VI":640},"USDA, ARS, Russell Research Center, Athens, USA",[],{"title":643},{"VI":644},"Kurt C. Lawrence",{"id":646,"sortIndex":77,"researcher":22,"roles":647,"affiliations":648,"properties":655,"displayName":657,"givenName":22,"familyName":22},"470ec38d-064b-4703-b672-12903e44f0cf",[83],[649],{"id":635,"sortIndex":23,"affiliation":650,"properties":22},{"id":635,"createTime":22,"updateTime":22,"relativeEntities":651,"slug":22,"properties":652,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":654,"statistic":22},[],{"title":653},{"VI":640},[],{"title":656},{"VI":657},"Seung Chul Yoon",{"id":659,"sortIndex":51,"researcher":22,"roles":660,"affiliations":661,"properties":668,"displayName":670,"givenName":22,"familyName":22},"78424bdd-dc57-4fe1-a526-ac0f3f1f1a9b",[83],[662],{"id":635,"sortIndex":23,"affiliation":663,"properties":22},{"id":635,"createTime":22,"updateTime":22,"relativeEntities":664,"slug":22,"properties":665,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":667,"statistic":22},[],{"title":666},{"VI":640},[],{"title":669},{"VI":670},"Gerald W. Heitschmidt",{"id":672,"sortIndex":126,"researcher":22,"roles":673,"affiliations":674,"properties":681,"displayName":683,"givenName":22,"familyName":22},"59313ec2-a7f7-4f05-88ba-f0f485aeb9ea",[83],[675],{"id":635,"sortIndex":23,"affiliation":676,"properties":22},{"id":635,"createTime":22,"updateTime":22,"relativeEntities":677,"slug":22,"properties":678,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":680,"statistic":22},[],{"title":679},{"VI":640},[],{"title":682},{"VI":683},"Deana R. Jones",{"id":685,"sortIndex":142,"researcher":22,"roles":686,"affiliations":687,"properties":694,"displayName":696,"givenName":22,"familyName":22},"9d3737de-21c3-41b0-ae45-b3f2f5c3170d",[83],[688],{"id":635,"sortIndex":23,"affiliation":689,"properties":22},{"id":635,"createTime":22,"updateTime":22,"relativeEntities":690,"slug":22,"properties":691,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":693,"statistic":22},[],{"title":692},{"VI":640},[],{"title":695},{"VI":696},"Bosoon Park",{"url":628,"publisher":698,"properties":718},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":699,"slug":10,"properties":700,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":704,"manageAffiliations":705,"indexDatabases":706,"url":22,"thumbnailPath":22,"statistic":713,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":701,"title":702,"eissn":703},{"VOID":15},{"EN":17},{"VOID":13},[],[],[707],{"id":28,"indexDatabase":708,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":709,"label":710,"description":711,"key":36,"publicationTags":712,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":714,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":715,"totalCitation":23,"totalCitationByYear":716,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":717,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":719,"volume":721},{"VOID":720},"116-122",{"VOID":194},"2008-03-14",[38],{"id":725,"createTime":726,"updateTime":727,"relativeEntities":728,"slug":729,"properties":730,"entityType":74,"verifyStatus":75,"verifyTime":743,"verifyNote":76,"languages":22,"translateLanguages":744,"viewCount":23,"primaryUrl":745,"fullTextUrl":22,"authors":746,"publicationType":168,"publisherRelationship":818,"citationCount":22,"citationInfo":22,"publishDate":843,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":844,"openAccess":22,"references":22,"isForceReanalyzing":198},"e4fb99df-8d67-4f04-a6d8-4d968422c18f","2024-01-09T04:07:14.506+00:00","2025-02-25T12:44:55.755+00:00",[],"Correlation-analysis-of-hyperspectral-imagery-for-multispectral-wavelength-selection-for-detection-of-defects-on-apples",{"abstract":731,"title":734,"keywords":737,"references":739,"doi":741},{"EN":732,"VI":733},"Visible\u002Fnear-infrared reflectance spectra extracted from hyperspectral images of apples were used to determine wavelength pairs that can be used to distinguish defect regions from normal regions on the apple surface. The optimal wavelengths were selected based on correlation analysis between the wavelength band ratio (λ1\u002Fλ2) or difference (λ1 − λ2) and the assigned value for the surface condition (0 = normal, 1 = defect). Spectral images of apple surfaces at the selected wavelengths were used to validate the correlation analysis. The correlation coefficients obtained using the correlation analysis for band ratio and difference were 0.91 and 0.79, respectively. When applied to the set of apple images, the band ratio model correctly identified 195 of the 211 defects on a set of 70 Fuji apples containing at least one defect region. Thus, the correlation analysis was demonstrated to be a feasible method for selecting wavelength pairs for use in distinguishing defects from areas without defects on apples.","Phổ phản xạ có thể nhìn thấy\u002Fgần hồng ngoại được trích xuất từ hình ảnh siêu phổ của táo đã được sử dụng để xác định các cặp bước sóng có thể được sử dụng để phân biệt các vùng khuyết tật và các vùng bình thường trên bề mặt táo. Các bước sóng tối ưu được chọn dựa trên phân tích tương quan giữa tỷ lệ băng sóng (λ1\u002Fλ2) hoặc hiệu số (λ1 − λ2) và giá trị được gán cho điều kiện bề mặt (0 = bình thường, 1 = khuyết tật). Các hình ảnh phổ của bề mặt táo tại các bước sóng được chọn đã được sử dụng để xác thực phân tích tương quan. Các hệ số tương quan thu được từ phân tích tương quan cho tỷ lệ băng sóng và hiệu số lần lượt là 0,91 và 0,79. Khi áp dụng vào bộ hình ảnh táo, mô hình tỷ lệ băng sóng đã xác định đúng 195 trong số 211 khuyết tật trên một bộ 70 quả táo Fuji chứa ít nhất một vùng khuyết tật. Do đó, phân tích tương quan đã được chứng minh là một phương pháp khả thi để chọn cặp bước sóng để sử dụng trong việc phân biệt các khuyết tật với các vùng không có khuyết tật trên táo.",{"EN":735,"VI":736},"Correlation analysis of hyperspectral imagery for multispectral wavelength selection for detection of defects on apples","Phân tích tương quan của hình ảnh siêu phổ để lựa chọn bước sóng đa phổ cho việc phát hiện các khuyết tật trên táo",{"VI":738},"phân tích tương quan; hình ảnh siêu phổ; táo; phát hiện khuyết tật; bước sóng đa phổ",{"VOID":740},"B. Park, K.C. Lawrence, W.R. Windham, R.J. Buhr, Trans. ASAE 45(6), 2017 (2003b)\nB. Park, W.R. Windham, K.C. Lawrence, D.P. Smith, P.W. Feldner, SPIE 4816, 308 (2002a)\nK. Chao, Y.R. Chen, H. Early, B. Park, Appl. Eng. Agric. 15(4), 363–369 (1999)\nC.R. Bostater, SPIE 3499, 277–285 (1998)\nM. Tsuta, J. Sugiyama, Y. Sagara, J. Agric. Food Chem. 50(1), 48–52 (2002)\nM.S. Kim, Y.R. Chen, P.M. Mehl, Trans. ASAE 44(3), 721–729 (2001)\nM.S. Kim, A.M. Lefcourt, Y.R. Chen, Appl. Opt. 42(19), 2934–3927 (2003)\nP.M. Mehl, K. Chao, M.S. Kim, Y.R. Chen, Appl. Eng. Agric. 18(2), 219 (2002)\nS.R. Delwiche, M.S. Kim, SPIE 4203, 13–20 (2000)\nD.B. Malkoff, W.R. Oliver, SPIE 3920, 118–128 (2000)\nE. Rodriguez-Diaz, M. Velez-Reyes, R.K. Chin, C.A. DiMarzio, SPIE 4129, 243–248 (2000)\nJ.A. Burman, SPIE 3871, 348–357 (1999)\nP.J. Dwyer, C.A. DiMarzio, SPIE 3752, 72–82 (1999)\nR.M. Levenson, E.S. Wachman, W. Niu, D.L. Farkas, SPIE 3438, 300–312 (1998)\nF. Feyaerts, P. Poller, L. van Gool, P. Wambacq, SPIE 3897, 193–203 (1999)\nK.J. Zuzak, M.D. Schaeberle, E.N. Lewis, Anal. Chem. 74(9), 2021–2028 (2002)\nM.E. Arnoldussen, D. Cohen, G.H. Bearman, W.S. Grundfest, J. Biomed. Opt. 5(3), 300–306 (2000)\nM.L. Huebschman, R.A. Schultz, H.R. Garner, IEEE Eng. Med. Bio. 21(4), 104–117 (2002)\nY. Inoue, J. Penuelus, Y. Nouevllon, M.S. Moran, SPIE 4151, 153–161 (2001)\nC.T. Willoughby, M.A. Folkman, M.A. Figueroa, SPIE 2599, 264–272 (1996)\nW.B. Spillman Jr., K.E. Meissner, S.C. Smith, S. Conner, R.O. Claus, SPIE 4259, 29–35 (2001)\nN. Otsu, Man Cybern. 9(1), 62–66 (1979)\nM.S. Kim, A.M. Lefcourt, K. Chao, Y.R. Chen, I. Kim, ASAE 45(6), 2027–2037 (2002)",{"VOID":742},"10.1007\u002Fs11694-008-9046-0","2025-02-02T23:24:28.366+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9046-0",[747,762,775,790,803],{"id":748,"sortIndex":23,"researcher":22,"roles":749,"affiliations":750,"properties":759,"displayName":761,"givenName":22,"familyName":22},"0388f084-d884-4469-a395-1dc6b5fbff6a",[83],[751],{"id":752,"sortIndex":23,"affiliation":753,"properties":22},"557de2b2-a5ed-4bb3-8847-ad14574b2460",{"id":752,"createTime":22,"updateTime":22,"relativeEntities":754,"slug":22,"properties":755,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":758,"statistic":22},[],{"title":756},{"VI":757},"National Institute of Agricultural Engineering, Rural Development Administration, Suwon, Korea",[],{"title":760},{"VI":761},"Kangjin Lee",{"id":763,"sortIndex":77,"researcher":22,"roles":764,"affiliations":765,"properties":772,"displayName":774,"givenName":22,"familyName":22},"e47b01d3-cc30-4960-aa09-2e3545082c90",[83],[766],{"id":752,"sortIndex":23,"affiliation":767,"properties":22},{"id":752,"createTime":22,"updateTime":22,"relativeEntities":768,"slug":22,"properties":769,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":771,"statistic":22},[],{"title":770},{"VI":757},[],{"title":773},{"VI":774},"Sukwon Kang",{"id":776,"sortIndex":51,"researcher":22,"roles":777,"affiliations":778,"properties":787,"displayName":789,"givenName":22,"familyName":22},"b4527ad8-d931-4af7-9cd1-c2b1e2b7473c",[83],[779],{"id":780,"sortIndex":23,"affiliation":781,"properties":22},"e8694bef-c8cf-49f9-871a-cd2a91fed06b",{"id":780,"createTime":22,"updateTime":22,"relativeEntities":782,"slug":22,"properties":783,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":786,"statistic":22},[],{"title":784},{"VI":785},"Food Safety Laboratory, USDA, Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, USA",[],{"title":788},{"VI":789},"Stephen R. Delwiche",{"id":791,"sortIndex":126,"researcher":22,"roles":792,"affiliations":793,"properties":800,"displayName":802,"givenName":22,"familyName":22},"8f56b643-0043-41be-aad1-1b773cdbe68c",[83],[794],{"id":780,"sortIndex":23,"affiliation":795,"properties":22},{"id":780,"createTime":22,"updateTime":22,"relativeEntities":796,"slug":22,"properties":797,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":799,"statistic":22},[],{"title":798},{"VI":785},[],{"title":801},{"VI":802},"Moon Sung Kim",{"id":804,"sortIndex":142,"researcher":22,"roles":805,"affiliations":806,"properties":815,"displayName":817,"givenName":22,"familyName":22},"97f59116-39aa-4a9b-b50d-6f5f9bee4b93",[83],[807],{"id":808,"sortIndex":23,"affiliation":809,"properties":22},"16fad3b8-77a2-4199-9151-cb239b6ed010",{"id":808,"createTime":22,"updateTime":22,"relativeEntities":810,"slug":22,"properties":811,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":814,"statistic":22},[],{"title":812},{"VI":813},"Department of Biosystems & Biomaterials Science and Engineering, Seoul National University, Seoul, Korea",[],{"title":816},{"VI":817},"Sangha Noh",{"url":745,"publisher":819,"properties":839},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":820,"slug":10,"properties":821,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":825,"manageAffiliations":826,"indexDatabases":827,"url":22,"thumbnailPath":22,"statistic":834,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":822,"title":823,"eissn":824},{"VOID":15},{"EN":17},{"VOID":13},[],[],[828],{"id":28,"indexDatabase":829,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":830,"label":831,"description":832,"key":36,"publicationTags":833,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":835,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":836,"totalCitation":23,"totalCitationByYear":837,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":838,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":840,"volume":842},{"VOID":841},"90-96",{"VOID":194},"2008-05-21",[38],{"id":846,"createTime":847,"updateTime":848,"relativeEntities":849,"slug":850,"properties":851,"entityType":74,"verifyStatus":75,"verifyTime":864,"verifyNote":76,"languages":22,"translateLanguages":865,"viewCount":23,"primaryUrl":866,"fullTextUrl":22,"authors":867,"publicationType":168,"publisherRelationship":880,"citationCount":22,"citationInfo":22,"publishDate":905,"publishYear":196,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":906,"openAccess":22,"references":22,"isForceReanalyzing":198},"ec8a139f-a810-49d6-a6fc-41bc4c4fa505","2023-12-31T08:48:32.674+00:00","2025-02-25T12:43:57.689+00:00",[],"High-speed-bichromatic-inspection-of-wheat-kernels-for-mold-and-color-class-using-high-power-pulsed-LEDs",{"abstract":852,"title":855,"keywords":858,"references":860,"doi":862},{"EN":853,"VI":854},"High-speed optical sorting of seeds in commercial processing is routinely practiced for removal of discolored seeds, seeds from volunteer plants, and non-seed objects. Sorters are conventionally based on monochromatic or bichromatic light from broad wavebands in the visible and near-infrared regions of energy. A particular challenge for these devices has been the recognition and removal of wheat kernels that have been damaged by the mold caused by the fungal disease Fusarium Head Blight. Previous research using an off-the-shelf bichromatic design on Fusarium-damaged wheat kernels demonstrated that approximately half of damaged kernels were positively detected. The research described herein examines an alternative design for bichromatic lighting and applies this design to two scenarios: sound vs. Fusarium-damaged wheat and red vs. white wheat. The new design utilizes two high-power (HP) LEDs and one silicon photo diode detector. The LEDs are flashed in alternating sequence at high frequency (2,000 Hz), such that during the half-cycle time period (0.25 ms) that each LED is on, reflected energy readings at a 10× sampling frequency are captured from a kernel in flight. This permits the capture of approximately 20 cycles of pulsed light during the time the free-falling kernel passes through the field of view of a fiber optic probe. A linear discriminant analysis (LDA) classification algorithm was applied that used two values derived from the reflected energy readings. Based on the new design, the accuracy of sound vs. Fusarium-damaged classification was 78% on average; for red vs. white wheat classification, the average accuracy was 76%. Although these accuracy values are not at the level as that obtained from LDA models that utilize reflected energy readings at two wavelengths from stationary kernels (95% and 92% for sound vs. Fusarium-damaged and red vs. white, respectively), the new design offers an improvement over conventional bichromatic designs.","Việc phân loại hạt giống bằng ánh sáng nhanh trong quá trình chế biến thương mại thường được thực hiện để loại bỏ các hạt bị đổi màu, hạt từ cây tự mọc và các vật thể không phải hạt. Các thiết bị phân loại thường dựa trên ánh sáng đơn sắc hoặc hai sắc từ các băng tần rộng trong vùng ánh sáng nhìn thấy và hồng ngoại gần. Một thách thức đặc biệt đối với các thiết bị này là nhận diện và loại bỏ các hạt lúa mì bị hư hỏng do nấm bệnh Fusarium Head Blight. Các nghiên cứu trước đây sử dụng thiết kế hai sắc chuẩn mực trên các hạt lúa mì bị hư hỏng do Fusarium cho thấy khoảng một nửa số hạt bị hư hỏng được phát hiện. Nghiên cứu được mô tả ở đây xem xét một thiết kế thay thế cho ánh sáng hai sắc và áp dụng thiết kế này vào hai kịch bản: lúa mì tốt so với lúa mì bị hư hỏng do Fusarium và lúa mì đỏ so với lúa mì trắng. Thiết kế mới sử dụng hai LED công suất cao và một cảm biến quang silicon. Các LED được nhấp nháy theo chu kỳ luân phiên với tần số cao (2.000 Hz), sao cho trong khoảng thời gian nửa chu kỳ (0,25 ms) mà mỗi LED sáng, các chỉ số năng lượng phản xạ ở tần số lấy mẫu 10× được ghi lại từ một hạt đang bay. Điều này cho phép ghi lại khoảng 20 chu kỳ ánh sáng xung trong thời gian hạt tự do rơi qua trường nhìn của đầu dò quang sợi. Một thuật toán phân loại phân tích phân biệt tuyến tính (LDA) đã được áp dụng, sử dụng hai giá trị lấy từ các chỉ số năng lượng phản xạ. Dựa trên thiết kế mới, độ chính xác trong việc phân loại lúa mì tốt so với lúa mì bị hư hỏng do Fusarium đã đạt 78% trung bình; đối với phân loại lúa mì đỏ so với lúa mì trắng, độ chính xác trung bình là 76%. Mặc dù các giá trị chính xác này không đạt được ở cấp độ giống như từ các mô hình LDA sử dụng năng lượng phản xạ ở hai bước sóng từ các hạt đứng yên (95% và 92% cho lúa mì tốt so với bị hư hỏng và lúa mì đỏ so với lúa mì trắng, tương ứng), thiết kế mới mang lại sự cải thiện so với các thiết kế hai sắc thông thường.",{"EN":856,"VI":857},"High-speed bichromatic inspection of wheat kernels for mold and color class using high-power pulsed LEDs","Kiểm tra nhanh bằng ánh sáng hai màu đối với hạt lúa mì bị mốc và phân loại màu sử dụng LED xung công suất cao",{"VI":859},"lúa mì, phân loại, hạt giống, năng lượng phản xạ, LED công suất cao, Fusarium, bệnh nấm",{"VOID":861},"US Food and Drug Administration, Letter from Ronald Chesemore to State Agricultural Directors, State Feed Control Officials, and Food, Feed and Grain Trade Organizations on Advisory Levels for DON (vomitoxin) in Food and Feed (US Department of Health and Human Services, Public Health Service, Rockville, MD, September 16, 1993)\nFAO, Worldwide regulations for mycotoxins in food and feed in 2003. Food and Nutrition Paper 81 (Food and Agriculture Organization of the United Nations, Rome, Italy, 2004)\nR.W. Stack, in Fusarium Head Blight of Wheat and Barley, ed. by K.J. Leonard and W.R. Bushnell (American Phytopathological Society, St. Paul, MN, 2003), pp 1–34\nL.P. Hart, Plant Dis. 82, 625 (1998)\nL.M. Seitz, W.D. Eustace, H.E. Mohr, M.D. Shogren, W.T. Yamazaki, Cereal Chem. 63, 146 (1986)\nR. Tkachuk, J.E. Dexter, K.H. Tipples, T.W. Nowicki, Cereal Chem. 68, 428 (1991)\nF.E. Dowell, M.S. Ram, L.M. Seitz, Cereal Chem. 76, 573 (1999)\nX. Luo, D.S. Jayas, S.J. Symons, J. Cereal Sci. 30, 49 (1999)\nR. Ruan, S. Ning, A. Song, A. Ning, R. Jones, P. Chen, Cereal Chem. 75, 455 (1998)\nD. Atanasoff, J. Agr. Res. 20, 1 (1920)\nS.R. Delwiche, Trans. ASAE 46, 731 (2003)\nS.R. Delwiche, G.A. Hareland, Cereal Chem. 81, 643 (2004)\nS.R. Delwiche, C.S. Gaines, Appl. Eng. Agric. 21, 681 (2005)\nS.R. Delwiche, T.C. Pearson, D.L. Brabec, Plant Dis. 89, 1214 (2005)\nSAS, Proc Discrim. in Statistics Guide (SAS Institute, Cary, NC, 1988)\nF.E. Dowell, Cereal Chem. 75, 142 (1998)",{"VOID":863},"10.1007\u002Fs11694-008-9037-1","2025-02-03T03:36:22.589+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-008-9037-1",[868],{"id":869,"sortIndex":23,"researcher":22,"roles":870,"affiliations":871,"properties":878,"displayName":789,"givenName":22,"familyName":22},"c3c4f44e-995e-4b5d-892e-78977c23bc85",[83],[872],{"id":780,"sortIndex":23,"affiliation":873,"properties":22},{"id":780,"createTime":22,"updateTime":22,"relativeEntities":874,"slug":22,"properties":875,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":877,"statistic":22},[],{"title":876},{"VI":785},[],{"title":879},{"VI":789},{"url":866,"publisher":881,"properties":901},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":882,"slug":10,"properties":883,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":887,"manageAffiliations":888,"indexDatabases":889,"url":22,"thumbnailPath":22,"statistic":896,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":884,"title":885,"eissn":886},{"VOID":15},{"EN":17},{"VOID":13},[],[],[890],{"id":28,"indexDatabase":891,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":892,"label":893,"description":894,"key":36,"publicationTags":895,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":897,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":898,"totalCitation":23,"totalCitationByYear":899,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":900,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":902,"volume":904},{"VOID":903},"103-110",{"VOID":194},"2008-03-01",[38],{"id":908,"createTime":909,"updateTime":910,"relativeEntities":911,"slug":912,"properties":913,"entityType":74,"verifyStatus":75,"verifyTime":926,"verifyNote":76,"languages":22,"translateLanguages":927,"viewCount":77,"primaryUrl":928,"fullTextUrl":22,"authors":929,"publicationType":168,"publisherRelationship":967,"citationCount":22,"citationInfo":22,"publishDate":992,"publishYear":421,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":993,"openAccess":22,"references":22,"isForceReanalyzing":198},"46169aed-c91e-47d8-a768-f578e4c977d6","2024-02-13T22:51:59.277+00:00","2025-02-25T12:43:00.533+00:00",[],"Development-of-an-experimental-procedure-for-real-time-investigation-of-diffusion-in-foods",{"abstract":914,"title":917,"keywords":920,"references":922,"doi":924},{"EN":915,"VI":916},"Diffusion and mass transfer are ubiquitous operations in food processing. The application of electric fields can influence the mass transfer properties of foods. A small scale processing unit was used in the development of a method that would allow real-time measurement of diffusion of dyes into gel samples (at a range of temperatures and electric field strengths). The depth of penetration and localisation of infused material can be visualised and measured using image analysis methods.","Sự khuếch tán và chuyển giao khối lượng là những quy trình phổ biến trong chế biến thực phẩm. Việc ứng dụng các trường điện có thể ảnh hưởng đến các thuộc tính chuyển giao khối lượng của thực phẩm. Một đơn vị chế biến quy mô nhỏ đã được sử dụng trong việc phát triển một phương pháp cho phép đo lường sự khuếch tán của thuốc nhuộm vào mẫu gel (tại một loạt các nhiệt độ và cường độ trường điện). Độ sâu thâm nhập và định vị của vật liệu đã được truyền vào có thể được hình dung và đo lường bằng cách sử dụng các phương pháp phân tích hình ảnh.",{"EN":918,"VI":919},"Development of an experimental procedure for real time investigation of diffusion in foods","Phát triển quy trình thí nghiệm để điều tra sự khuếch tán trong thực phẩm theo thời gian thực",{"VI":921},"khuếch tán, chuyển giao khối lượng, thực phẩm, trường điện, phân tích hình ảnh",{"VOID":923},"K. Halden, A.A.P. DeAlwis, P.J. Fryer, Changes in the electrical conductivity of foods during ohmic heating. Int. J. Food Sci. Technol. 25, 9–25 (1990)\nP.J.R. Schreier, D.G. Reid, P.J. Fryer, Enhanced diffusion during the electrical heating of foods. Int. J. Food Sci. Technol. 28, 249–260 (1993)\nH.R. Carlon, J. Latham, Enhanced drying rates of wetted materials in electric fields. J. Atmos. Terr. Phys. 54(2), 117–118 (1992)\nA.G.F. Stapley, J.A. Sousa Gonçalves, M.P. Hollewand, L.F. Gladden, P.J. Fryer, An NMR pulsed field gradient study of the electrical and conventional heating of carrot. Int. J. Food Sci. Technol. 30, 639–654 (1995)\nM.R. Kemp, P.J. Fryer, Enhancement of diffusion through foods using alternating electric fields. Innov. Food Sci. Emerg. Technol. 8(1), 143–153 (2007)\nM. Lima, Ascorbic acid degradation kinetics and mass transfer effects in biological tissue during ohmic heating, PhD Thesis, The Ohio State University (1996)\nM. Lima, B.F. Heskitt, S.K. Sastry, Diffusion of beet dye during electrical and conventional heating at steady-state temperature. J. Food Process Eng. 24(5), 331–340 (2001)\nS. Kulsrestha, S.K. Sastry, Electroporation of vegetable tissue in an ohmic heater. Institute of Food Technologists (online). Available at: http:\u002F\u002Fwww.confex2.com\u002Fift\u002F98annual\u002Faccepted\u002F797.htm (1998)\nC.H. Lee, S.W. Yoon, Effect of ohmic heating on the structure and permeability of the cell membrane of Saccharomyces Cerevisiae. Institute of Food Technologists (online). Available at: http:\u002F\u002Fwww.confex2.com\u002Fift\u002F99annual\u002Fabstracts\u002F4302.htm (1999)\nM. Lima, S.K. Sastry, The effects of ohmic heating frequency on hot-air drying rate and juice yield. J. Food Eng. 41(2), 115–119 (1999)\nW.C. Wang, S.K. Sastry, Effects of thermal and electrothermal pretreatments on hot air drying rate of vegetable tissue. J. Food Process Eng. 23, 299–319 (2000)\nS. Salengke, Effect of ohmic pretreatment on drying rate of grapes and adsorption isotherm of raisins. Institute of Food Technologists (online). Available at: http:\u002F\u002Fwww.confex.com\u002Fift\u002F2000\u002Ftechprogram\u002Fpaper_3573.htm (2000)\nW.C. Wang, S.K. Sastry, Effects of moderate electrothermal treatments on juice yield from cellular tissue. Innov. Food Sci. Emerg. Technol. 3, 371–377 (2002)\nN.R. Lakkakula, M. Lima, T. Walker, Rice bran stabilisation and rice bran oil extraction using ohmic heating. Bioresour. Technol. 92, 157–161 (2004)\nS. Bayarri, I. Rivas, E. Costell, L. Durán, Diffusion of sucrose and aspartame in kappa-carrageenan and gellan gum gels. Food Hydrocolloids 15, 67–73 (2001)\nP.J. Fryer, in New Methods of Food Preservation, ed. by G.W. Gould. Electrical resistance heating of foods (Blackie Academic and Professional, London, 1995)\nA.A.P. DeAlwis, K. Halden, P.J. Fryer, Shape and conductivity effects in the ohmic heating of foods. Chem. Eng. Res. Des. 67, 159–168 (1989)\nM. Lima, B.F. Heskitt, S.K. Sastry, The effect of frequency and wave form on the electrical conductivity-temperature profiles of turnip tissue. J. Food Process Eng. 22, 41–54 (1999)\nT. Tzedakis, R. Basseguy, M. Comtat, Voltammetric and coulometric techniques to estimate the electrochemical reaction rate during ohmic sterilisation. J. Appl. Electrochem. 29, 821–828 (1999)\nB. Amsden, N. Turner, Diffusion characteristics of calcium alginate gels. Biotechnol. Bioeng. 65(5), 605–610 (1999)\nS. Neiser, K.I. Draget, O. Smidsrod, Interactions in bovine serum albumin-calcium alginate gel systems. Food hydrocolloids 13, 445–458 (1999)\nS. Odake, K. Hatae, A. Shimada, S. Iibuchi, Apparent diffusion coefficient of sodium-chloride in cubical agar-gel. Agric. Biol. Chem. 54(11), 2811–2817 (1990)\nJ.P. Gong, N. Komatsu, T. Nitta, Y. Osada, Electrical conductance of polyelectrolyte gels. J. Phys. Chem. B 101, 740–745 (1997)\nK. Samprovalaki, P.T. Robbins, M. Grammatika, P.J. Fryer, A study of diffusion of dyes in model foods using a visual method. J. Food Eng. (under review)",{"VOID":925},"10.1007\u002Fs11694-011-9114-8","2025-02-03T23:24:37.880+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-011-9114-8",[930,954],{"id":931,"sortIndex":23,"researcher":22,"roles":932,"affiliations":933,"properties":951,"displayName":953,"givenName":22,"familyName":22},"abcfd4df-f4b4-4bbb-902d-fb17b326a311",[83],[934,942],{"id":935,"sortIndex":23,"affiliation":936,"properties":22},"7a0ff643-fa6d-487c-a4c6-b327e706fb9e",{"id":935,"createTime":22,"updateTime":22,"relativeEntities":937,"slug":22,"properties":938,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":941,"statistic":22},[],{"title":939},{"VI":940},"Chemical Engineering, The University of Birmingham, Birmingham, UK",[],{"id":943,"sortIndex":77,"affiliation":944,"properties":950},"176ffbc4-86b4-46b5-980d-3f52f210ebf4",{"id":943,"createTime":22,"updateTime":22,"relativeEntities":945,"slug":22,"properties":946,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":949,"statistic":22},[],{"title":947},{"VI":948},"Athens, Greece",[],{},{"title":952},{"VI":953},"Konstantina Samprovalaki",{"id":955,"sortIndex":77,"researcher":22,"roles":956,"affiliations":957,"properties":964,"displayName":966,"givenName":22,"familyName":22},"7236861f-ef73-4ac1-95e5-d2b2d46e9219",[83],[958],{"id":935,"sortIndex":23,"affiliation":959,"properties":22},{"id":935,"createTime":22,"updateTime":22,"relativeEntities":960,"slug":22,"properties":961,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":963,"statistic":22},[],{"title":962},{"VI":940},[],{"title":965},{"VI":966},"Peter J. Fryer",{"url":928,"publisher":968,"properties":988},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":969,"slug":10,"properties":970,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":974,"manageAffiliations":975,"indexDatabases":976,"url":22,"thumbnailPath":22,"statistic":983,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":971,"title":972,"eissn":973},{"VOID":15},{"EN":17},{"VOID":13},[],[],[977],{"id":28,"indexDatabase":978,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":979,"label":980,"description":981,"key":36,"publicationTags":982,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":984,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":985,"totalCitation":23,"totalCitationByYear":986,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":987,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":989,"volume":991},{"VOID":990},"78-89",{"VOID":419},"2011-06-08",[38],{"id":995,"createTime":996,"updateTime":997,"relativeEntities":998,"slug":999,"properties":1000,"entityType":74,"verifyStatus":75,"verifyTime":1013,"verifyNote":76,"languages":22,"translateLanguages":1014,"viewCount":23,"primaryUrl":1015,"fullTextUrl":22,"authors":1016,"publicationType":168,"publisherRelationship":1071,"citationCount":22,"citationInfo":22,"publishDate":1096,"publishYear":421,"citationAnalyzeStatus":21,"lastCitationAnalyze":22,"indexDatabases":1097,"openAccess":22,"references":22,"isForceReanalyzing":198},"d17ea330-728f-458d-a7f0-1b0b6937fda2","2024-01-19T16:47:11.208+00:00","2025-02-25T12:42:04.775+00:00",[],"Quality-assessment-of-corn-grain-sample-using-color-image-analysis",{"abstract":1001,"title":1004,"keywords":1007,"references":1009,"doi":1011},{"EN":1002,"VI":1003},"Grain quality is assessed based on different grain features like appearance, shape, color, smell, flavour, moisture content, infections, presence of impurities, etc. The main indexes for the quality of grain samples are related to the color characteristics and the shape of the grain sample elements. Most of these characteristics are assessed visually by an expert. In this paper, an approach for an objective estimation of some basic grain quality characteristics is presented. It is based on a complex analysis of color images of the investigated objects. Due to the conceptual difference in presenting the objects’ color and shape characteristics, their assessment was performed separately. After that the results form these two assessments were combined and the final decision about the object’s classification to one of the quality groups defined by the standard regulations was made. Methods and tools for feature extraction and for object description, as well as for classification of the objects into predetermined groups were proposed. Three classifiers, based on radial basis elements, which were used for grain color and shape class recognition, were analyzed. Two different approaches for fusing the results from object color and object shape analyses were investigated. The training and testing errors of the developed procedures were evaluated.","Chất lượng hạt được đánh giá dựa trên các đặc điểm khác nhau như ngoại hình, hình dạng, màu sắc, mùi, hương vị, hàm lượng ẩm, sự nhiễm khuẩn, sự có mặt của tạp chất, v.v. Các chỉ số chính cho chất lượng mẫu hạt liên quan đến các đặc điểm màu sắc và hình dạng của các yếu tố của mẫu hạt. Hầu hết các đặc điểm này được đánh giá bằng cách quan sát trực quan của một chuyên gia. Trong bài báo này, một phương pháp để ước lượng khách quan một số đặc điểm chất lượng hạt cơ bản được trình bày. Nó dựa trên phân tích phức tạp các hình ảnh màu của các đối tượng được khảo sát. Do sự khác biệt về khái niệm trong việc trình bày đặc điểm màu sắc và hình dạng của các đối tượng, việc đánh giá của chúng đã được thực hiện tách biệt. Sau đó, các kết quả từ hai đánh giá này được kết hợp và quyết định cuối cùng về việc phân loại đối tượng vào một trong các nhóm chất lượng theo quy định tiêu chuẩn được đưa ra. Các phương pháp và công cụ cho việc trích xuất đặc điểm và mô tả đối tượng, cũng như phân loại các đối tượng vào các nhóm đã định sẵn đã được đề xuất. Ba bộ phân loại, dựa trên các yếu tố cơ sở hình tròn, được sử dụng để nhận diện lớp màu sắc và hình dạng của hạt, đã được phân tích. Hai cách tiếp cận khác nhau để hợp nhất kết quả từ phân tích màu sắc và hình dạng của đối tượng đã được điều tra. Lỗi trong đào tạo và kiểm tra của các quy trình phát triển đã được đánh giá.",{"EN":1005,"VI":1006},"Quality assessment of corn grain sample using color image analysis","Đánh giá chất lượng mẫu ngô bằng phương pháp phân tích hình ảnh màu",{"VI":1008},"đánh giá chất lượng, hạt ngô, phân tích hình ảnh màu, nhận diện lớp, phân loại đối tượng",{"VOID":1010},"M. Mladenov, C. Damyanov, S. Atanassova, Tz. Draganova, Agric. Sci. Technol. 1(1), 8 (2009)\nBulgarian Government Standard 607:1973. Grain maize for purchase and marketing\nBulgarian Government Standard 602:1987. 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Mclachlan, Discriminant Analysis and Statistical Pattern Recognition (Wiley Series in Probability and Statistics) (Wiley-Interscience, 2004), ISBN 0471691151\nS. Kotsiantis, P. Pintelas, WSEAS Trans. Inf. Sci. Appl. 1(1), 73 (2004)\nV. Vapnik, The Nature of Statistical Learning Theory (Wiley, New York, 1995)\nH. Drucker, Chris, B.L. Kaufman, A. Smola, V. Vapnik, in Advances in Neural Information Processing Systems 9, vol. 9 (1997), pp. 155–161\nD. Bremner, E. Demaine, J. Erickson et al., Discrete Comput. Geom. 4(33), 593 (2005)\nS. Vijayakumar, A. D’Souza, S. Schaal, in Nearest-Neighbor Methods in Learning and Vision: Theory and Practice, ed. by G. Shakhnarovich, T. Darrell, P. Indyk (The MIT Press, Cambridge, 2006)\nP.A. Flach, N. Lachiche, Mach. Learn. 57(3), 233 (2004)\nS. Kotsiantis, P. Pintelas, in Artificial Intelligence: Methodology, Systems, and Applications (Lecture Notes in Computer Science), ed. by C. Bussler, D. Fensel (Springer Berlin Heidelberg 2004), pp. 198–207",{"VOID":1012},"10.1007\u002Fs11694-011-9118-4","2025-02-04T20:33:36.673+00:00",[348],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11694-011-9118-4",[1017,1032,1045,1058],{"id":1018,"sortIndex":23,"researcher":22,"roles":1019,"affiliations":1020,"properties":1029,"displayName":1031,"givenName":22,"familyName":22},"f4dbabd5-6282-41fe-8775-4dca38f22979",[83],[1021],{"id":1022,"sortIndex":23,"affiliation":1023,"properties":22},"63e635c8-7f29-4400-bbd2-d8c763543223",{"id":1022,"createTime":22,"updateTime":22,"relativeEntities":1024,"slug":22,"properties":1025,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1028,"statistic":22},[],{"title":1026},{"VI":1027},"Department of Automatics, Information and Control Engineering, University of Ruse, Ruse, Bulgaria",[],{"title":1030},{"VI":1031},"Miroljub Ivanov Mladenov",{"id":1033,"sortIndex":77,"researcher":22,"roles":1034,"affiliations":1035,"properties":1042,"displayName":1044,"givenName":22,"familyName":22},"79a5cc83-ab40-4a8a-b55f-1ba5094d4fb7",[83],[1036],{"id":1022,"sortIndex":23,"affiliation":1037,"properties":22},{"id":1022,"createTime":22,"updateTime":22,"relativeEntities":1038,"slug":22,"properties":1039,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1041,"statistic":22},[],{"title":1040},{"VI":1027},[],{"title":1043},{"VI":1044},"Stanislav Miroslavov Penchev",{"id":1046,"sortIndex":51,"researcher":22,"roles":1047,"affiliations":1048,"properties":1055,"displayName":1057,"givenName":22,"familyName":22},"58a8ba0f-e5fe-4a7d-a651-ce4760acf291",[83],[1049],{"id":1022,"sortIndex":23,"affiliation":1050,"properties":22},{"id":1022,"createTime":22,"updateTime":22,"relativeEntities":1051,"slug":22,"properties":1052,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1054,"statistic":22},[],{"title":1053},{"VI":1027},[],{"title":1056},{"VI":1057},"Martin Plamenov Dejanov",{"id":1059,"sortIndex":126,"researcher":22,"roles":1060,"affiliations":1061,"properties":1068,"displayName":1070,"givenName":22,"familyName":22},"2239b69a-c206-4700-835d-d927f671fff4",[83],[1062],{"id":1022,"sortIndex":23,"affiliation":1063,"properties":22},{"id":1022,"createTime":22,"updateTime":22,"relativeEntities":1064,"slug":22,"properties":1065,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1067,"statistic":22},[],{"title":1066},{"VI":1027},[],{"title":1069},{"VI":1070},"Metin Sebahatin Mustafa",{"url":1015,"publisher":1072,"properties":1092},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1073,"slug":10,"properties":1074,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":1078,"manageAffiliations":1079,"indexDatabases":1080,"url":22,"thumbnailPath":22,"statistic":1087,"gsStatistic":22,"type":54,"analyzePriority":22},[],{"issn":1075,"title":1076,"eissn":1077},{"VOID":15},{"EN":17},{"VOID":13},[],[],[1081],{"id":28,"indexDatabase":1082,"url":39,"indexYears":40,"academicFieldIds":22,"indexDatabaseRanking":41},{"id":30,"createTime":22,"updateTime":22,"relativeEntities":1083,"label":1084,"description":1085,"key":36,"publicationTags":1086,"standard":22},[],{"EN":33,"VI":33},{"EN":33,"VI":35},[38],{"impactFactor":23,"impactFactorByYear":1088,"i10Index":23,"i10IndexLast5Year":23,"totalPublication":44,"totalPublicationByYear":1089,"totalCitation":23,"totalCitationByYear":1090,"totalCitationPerPublication":23,"totalCitationPerPublicationByYear":1091,"hindexLast5Year":23,"hindex":23},{},{"2007":46,"2008":47,"2009":48,"2010":49,"2011":50,"2012":51},{},{},{"pages":1093,"volume":1095},{"VOID":1094},"111-127",{"VOID":419},"2011-10-30",[38]]