{"title":"傅里叶变换近红外光谱(FT-NIR)测定姜黄中姜黄素、淀粉和水分含量","authors":"K. Thangavel , K. Dhivya","doi":"10.1016/j.eaef.2019.02.003","DOIUrl":null,"url":null,"abstract":"<div><p><span><span><span>Fourier transform near infrared spectroscopy (FT-NIR) in diffuse reflectance mode was used for the rapid estimation of </span>curcumin<span>, starch<span> and moisture contents in </span></span></span>turmeric samples. Thirty samples each of fingers and bulbs from varieties ‘Erode local’ and ‘Salem local’ (n = 120) were used for the study. Calibration models were developed and evaluated to describe the relationship between the three quality attributes with the NIR spectra of the turmeric powder. NIR reflectance spectra were acquired for each turmeric sample at a resolution of 8 cm</span><sup>−1</sup> over a wave number range of 12,500 to 3600 cm<sup>−1</sup>. Vector normalization, first derivative and first derivative plus vector normalization were used as spectral pre-processing options. The relationship between the acquired spectra of turmeric samples and the quality attributes was examined through partial least square (PLS) regression algorithm. First derivative plus vector normalization technique predicted curcumin content with best accuracy with lowest root mean square error of cross validation (RMSECV) of 0.178% and maximum correlation coefficient for validation plots (R<sup>2</sup> = 91.9). Vector normalization technique predicted the starch and moisture content with RMSECV and R<sup>2</sup><span> value of 0.076%, 96.8 and 0.032%, 81.1 respectively. The results demonstrated that FT-NIR could be used as a rapid technique for quantification of curcumin, starch and moisture content in turmeric rhizomes for online grading in spice processing.</span></p></div>","PeriodicalId":38965,"journal":{"name":"Engineering in Agriculture, Environment and Food","volume":"12 2","pages":"Pages 264-269"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.eaef.2019.02.003","citationCount":"24","resultStr":"{\"title\":\"Determination of curcumin, starch and moisture content in turmeric by Fourier transform near infrared spectroscopy (FT-NIR)\",\"authors\":\"K. Thangavel , K. Dhivya\",\"doi\":\"10.1016/j.eaef.2019.02.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span><span>Fourier transform near infrared spectroscopy (FT-NIR) in diffuse reflectance mode was used for the rapid estimation of </span>curcumin<span>, starch<span> and moisture contents in </span></span></span>turmeric samples. Thirty samples each of fingers and bulbs from varieties ‘Erode local’ and ‘Salem local’ (n = 120) were used for the study. Calibration models were developed and evaluated to describe the relationship between the three quality attributes with the NIR spectra of the turmeric powder. NIR reflectance spectra were acquired for each turmeric sample at a resolution of 8 cm</span><sup>−1</sup> over a wave number range of 12,500 to 3600 cm<sup>−1</sup>. Vector normalization, first derivative and first derivative plus vector normalization were used as spectral pre-processing options. The relationship between the acquired spectra of turmeric samples and the quality attributes was examined through partial least square (PLS) regression algorithm. First derivative plus vector normalization technique predicted curcumin content with best accuracy with lowest root mean square error of cross validation (RMSECV) of 0.178% and maximum correlation coefficient for validation plots (R<sup>2</sup> = 91.9). Vector normalization technique predicted the starch and moisture content with RMSECV and R<sup>2</sup><span> value of 0.076%, 96.8 and 0.032%, 81.1 respectively. The results demonstrated that FT-NIR could be used as a rapid technique for quantification of curcumin, starch and moisture content in turmeric rhizomes for online grading in spice processing.</span></p></div>\",\"PeriodicalId\":38965,\"journal\":{\"name\":\"Engineering in Agriculture, Environment and Food\",\"volume\":\"12 2\",\"pages\":\"Pages 264-269\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.eaef.2019.02.003\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering in Agriculture, Environment and Food\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1881836618302271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering in Agriculture, Environment and Food","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1881836618302271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
Determination of curcumin, starch and moisture content in turmeric by Fourier transform near infrared spectroscopy (FT-NIR)
Fourier transform near infrared spectroscopy (FT-NIR) in diffuse reflectance mode was used for the rapid estimation of curcumin, starch and moisture contents in turmeric samples. Thirty samples each of fingers and bulbs from varieties ‘Erode local’ and ‘Salem local’ (n = 120) were used for the study. Calibration models were developed and evaluated to describe the relationship between the three quality attributes with the NIR spectra of the turmeric powder. NIR reflectance spectra were acquired for each turmeric sample at a resolution of 8 cm−1 over a wave number range of 12,500 to 3600 cm−1. Vector normalization, first derivative and first derivative plus vector normalization were used as spectral pre-processing options. The relationship between the acquired spectra of turmeric samples and the quality attributes was examined through partial least square (PLS) regression algorithm. First derivative plus vector normalization technique predicted curcumin content with best accuracy with lowest root mean square error of cross validation (RMSECV) of 0.178% and maximum correlation coefficient for validation plots (R2 = 91.9). Vector normalization technique predicted the starch and moisture content with RMSECV and R2 value of 0.076%, 96.8 and 0.032%, 81.1 respectively. The results demonstrated that FT-NIR could be used as a rapid technique for quantification of curcumin, starch and moisture content in turmeric rhizomes for online grading in spice processing.
期刊介绍:
Engineering in Agriculture, Environment and Food (EAEF) is devoted to the advancement and dissemination of scientific and technical knowledge concerning agricultural machinery, tillage, terramechanics, precision farming, agricultural instrumentation, sensors, bio-robotics, systems automation, processing of agricultural products and foods, quality evaluation and food safety, waste treatment and management, environmental control, energy utilization agricultural systems engineering, bio-informatics, computer simulation, computational mechanics, farm work systems and mechanized cropping. It is an international English E-journal published and distributed by the Asian Agricultural and Biological Engineering Association (AABEA). Authors should submit the manuscript file written by MS Word through a web site. The manuscript must be approved by the author''s organization prior to submission if required. Contact the societies which you belong to, if you have any question on manuscript submission or on the Journal EAEF.