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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
04/01/2024 |
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Data da última atualização: |
04/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SCHOLZ, M. B. S.; PAGIATTO, N. F.; KITZBERGER, C. S. G.; PEREIRA, L. F. P.; DAVRIEUX, F.; CHARMETANTE, P.; LEROYE, T. |
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Afiliação: |
M. B. S. SCHOLZ, INSTITUTOAGRONÔMICODOPARANÁ; N. F. PAGIATTO, UNIVERSIDADE ESTADUAL DE LONDRINA; C. S. G. KITZBERGER, INSTITUTO AGRONÔMICO DO PARANÁ; LUIZ FILIPE PROTASIO PEREIRA, CNPCa; F. DAVRIEUX, LA RECHERCHE AGRONOMIQUE POUR LE DEVELOPEMENT; P. CHARMETANTE, LA RECHERCHE AGRONOMIQUE POUR LE DEVELOPEMENT; T. LEROYE, LA RECHERCHE AGRONOMIQUE POUR LE DEVELOPEMENT. |
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Título: |
Validation of near-infrared spectroscopy for the quantification of cafestol and kahweol in green coffee. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Food Research International, v. 61, p. 176-182, 2014. |
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DOI: |
http://dx.doi.org/10.1016/j.foodres.2013.12.008 |
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Idioma: |
Inglês |
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Conteúdo: |
Near-infrared spectroscopy (NIRS) is among the many tools available to study the biochemical diversity of coffee species. This technique is inexpensive, fast and accurate, and it requires only small amounts of samples. The aim of this study was to use NIRS to estimate the amount of diterpenes (cafestol and kahweol) in green coffee. To construct the prediction model, 126 Ethiopian accessions coffee collection and 44 modern cultivars were analyzed. The total sample set was split into two groups as follows: a group of 130 samples for calibration and a group of 40 samples for the validation step. Reference values of cafestol and kahweol were determined by high performance liquid chromatography (HPLC). Cafestol values ranged from 182.62 g to 1308.62 mg 100 g(-1), and kahweol values ranged from 182.69 to 1265.41 mg 100 g(-1). To improve the quality of the calibration step, a pretreatment with the second derivative was applied to smooth the raw spectra. The prediction models of cafestol and kahweol were developed using the modified partial least squares regression (mPLS). The performance of these models was evaluated by the ratio of performance deviation (RPD) and R-2 parameters, obtained by the ratio of the NIR prediction data and the corresponding reference data. The prediction models of cafestol (RPD = 2.74; R-2 = 0.89) and kahweol (RPD = 2.2; R-2 = 0.88) confirm the validity of NIRS analysis to determine diterpenes contents in green coffee. (C) 2014 Elsevier Ltd. All rights reserved. MenosNear-infrared spectroscopy (NIRS) is among the many tools available to study the biochemical diversity of coffee species. This technique is inexpensive, fast and accurate, and it requires only small amounts of samples. The aim of this study was to use NIRS to estimate the amount of diterpenes (cafestol and kahweol) in green coffee. To construct the prediction model, 126 Ethiopian accessions coffee collection and 44 modern cultivars were analyzed. The total sample set was split into two groups as follows: a group of 130 samples for calibration and a group of 40 samples for the validation step. Reference values of cafestol and kahweol were determined by high performance liquid chromatography (HPLC). Cafestol values ranged from 182.62 g to 1308.62 mg 100 g(-1), and kahweol values ranged from 182.69 to 1265.41 mg 100 g(-1). To improve the quality of the calibration step, a pretreatment with the second derivative was applied to smooth the raw spectra. The prediction models of cafestol and kahweol were developed using the modified partial least squares regression (mPLS). The performance of these models was evaluated by the ratio of performance deviation (RPD) and R-2 parameters, obtained by the ratio of the NIR prediction data and the corresponding reference data. The prediction models of cafestol (RPD = 2.74; R-2 = 0.89) and kahweol (RPD = 2.2; R-2 = 0.88) confirm the validity of NIRS analysis to determine diterpenes contents in green coffee. (C) 2014 Elsevier Ltd. All rights res... Mostrar Tudo |
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Thesaurus Nal: |
Biochemistry; Coffea arabica var. arabica; Cultivars. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02271naa a2200241 a 4500
001 2160455
005 2024-01-04
008 2014 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1016/j.foodres.2013.12.008$2DOI
100 1 $aSCHOLZ, M. B. S.
245 $aValidation of near-infrared spectroscopy for the quantification of cafestol and kahweol in green coffee.$h[electronic resource]
260 $c2014
520 $aNear-infrared spectroscopy (NIRS) is among the many tools available to study the biochemical diversity of coffee species. This technique is inexpensive, fast and accurate, and it requires only small amounts of samples. The aim of this study was to use NIRS to estimate the amount of diterpenes (cafestol and kahweol) in green coffee. To construct the prediction model, 126 Ethiopian accessions coffee collection and 44 modern cultivars were analyzed. The total sample set was split into two groups as follows: a group of 130 samples for calibration and a group of 40 samples for the validation step. Reference values of cafestol and kahweol were determined by high performance liquid chromatography (HPLC). Cafestol values ranged from 182.62 g to 1308.62 mg 100 g(-1), and kahweol values ranged from 182.69 to 1265.41 mg 100 g(-1). To improve the quality of the calibration step, a pretreatment with the second derivative was applied to smooth the raw spectra. The prediction models of cafestol and kahweol were developed using the modified partial least squares regression (mPLS). The performance of these models was evaluated by the ratio of performance deviation (RPD) and R-2 parameters, obtained by the ratio of the NIR prediction data and the corresponding reference data. The prediction models of cafestol (RPD = 2.74; R-2 = 0.89) and kahweol (RPD = 2.2; R-2 = 0.88) confirm the validity of NIRS analysis to determine diterpenes contents in green coffee. (C) 2014 Elsevier Ltd. All rights reserved.
650 $aBiochemistry
650 $aCoffea arabica var. arabica
650 $aCultivars
700 1 $aPAGIATTO, N. F.
700 1 $aKITZBERGER, C. S. G.
700 1 $aPEREIRA, L. F. P.
700 1 $aDAVRIEUX, F.
700 1 $aCHARMETANTE, P.
700 1 $aLEROYE, T.
773 $tFood Research International$gv. 61, p. 176-182, 2014.
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