Icelandic
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Food Chemistry 2017-Mar

Qualitative and quantitative detection of honey adulterated with high-fructose corn syrup and maltose syrup by using near-infrared spectroscopy.

Aðeins skráðir notendur geta þýtt greinar
Skráðu þig / skráðu þig
Krækjan er vistuð á klemmuspjaldið
Shuifang Li
Xin Zhang
Yang Shan
Donglin Su
Qiang Ma
Ruizhi Wen
Jiaojuan Li

Lykilorð

Útdráttur

Near-infrared spectroscopy (NIR) was used for qualitative and quantitative detection of honey adulterated with high-fructose corn syrup (HFCS) or maltose syrup (MS). Competitive adaptive reweighted sampling (CARS) was employed to select key variables. Partial least squares linear discriminant analysis (PLS-LDA) was adopted to classify the adulterated honey samples. The CARS-PLS-LDA models showed an accuracy of 86.3% (honey vs. adulterated honey with HFCS) and 96.1% (honey vs. adulterated honey with MS), respectively. PLS regression (PLSR) was used to predict the extent of adulteration in the honeys. The results showed that NIR combined with PLSR could not be used to quantify adulteration with HFCS, but could be used to quantify adulteration with MS: coefficient (Rp2) and root mean square of prediction (RMSEP) were 0.901 and 4.041 for MS-adulterated samples from different floral origins, and 0.981 and 1.786 for MS-adulterated samples from the same floral origin (Brassica spp.), respectively.

Skráðu þig á
facebook síðu okkar

Heillasta gagnagrunnur lækningajurtanna sem studdur er af vísindum

  • Virkar á 55 tungumálum
  • Jurtalækningar studdir af vísindum
  • Jurtaviðurkenning eftir ímynd
  • Gagnvirkt GPS kort - merktu jurtir á staðsetningu (kemur fljótlega)
  • Lestu vísindarit sem tengjast leit þinni
  • Leitaðu að lækningajurtum eftir áhrifum þeirra
  • Skipuleggðu áhugamál þitt og vertu vakandi með fréttarannsóknum, klínískum rannsóknum og einkaleyfum

Sláðu inn einkenni eða sjúkdóm og lestu um jurtir sem gætu hjálpað, sláðu jurt og sjáðu sjúkdóma og einkenni sem hún er notuð við.
* Allar upplýsingar eru byggðar á birtum vísindarannsóknum

Google Play badgeApp Store badge