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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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Registro original: |
Embrapa Café (CNPCa) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
11/01/2008 |
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Data da última atualização: |
24/03/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Nacional - A |
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Autoria: |
PAULINO, S. E. P.; MOURÃO FILHO, F. de A. A.; MAIA, A. de H. N.; AVILÉS, T. E. C.; DOURADO NETO, D. |
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Afiliação: |
Silvia Elisandra Pasqua Paulino, ESALQ/USP; Francisco de Assis Alves Mourão Filho, ESALQ/USP; Aline de Holanda Nunes Maia, Embrapa Meio Ambiente; Tatiana Eugenia Cantuarias Avilé, ESALQ/USP; Durval Dourado Neto, ESALQ/USP. |
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Título: |
Agrometeorological models for 'Valencia' and 'Hamlin' sweet oranges to estimate the number of fruits per plant. |
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Ano de publicação: |
2007 |
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Fonte/Imprenta: |
Scientia Agricola, Piracicaba, v.64, n.1, p.1-11, 2007. |
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Idioma: |
Inglês |
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Conteúdo: |
The development of models that allow forecasting yield tendencies is important to all sectors of the citrus industry. This work evaluated the influence of meteorological variables in different phases of the crop cycle in order to propose empirical models to estimate the number of fruits per plant (NFP) of 'Valencia' and 'Hamlin' sweet oranges. NFP sampling data from the citrus juice industry of the State of São Paulo, on the total of 15 harvests (1990/91 to 2004/05), classified into three age classes, and meteorological data of maximum and minimum air temperature and rainfall of Limeira, SP, Brazil, were utilized. Correlation coefficients were initially computed between the number of fruits per plant and each meteorological variable used for water balance and variables related to air temperature, in different periods. Linear multiple regression models were fit to describe the empirical relationship between NFP and the subsets of agrometeorological predictors that presented higher correlations in different phases of the crop cycle. The meteorological conditions during the phases of vegetative summer flush, pre-flowering, flowering and beginning of fruit growth influenced the number of fruits per plant. The proposed models presented adequate goodness-of-fit with determination coefficients varying from 0.72 to 0.87. |
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Palavras-Chave: |
Modelo de regressão linear. |
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Thesagro: |
Laranja; Meteorologia; Modelo Matemático; Previsão de Safra; Produtividade. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/100170/1/2007AP-037.pdf
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Marc: |
LEADER 02093naa a2200241 a 4500
001 1015902
005 2023-03-24
008 2007 bl uuuu u00u1 u #d
100 1 $aPAULINO, S. E. P.
245 $aAgrometeorological models for 'Valencia' and 'Hamlin' sweet oranges to estimate the number of fruits per plant.$h[electronic resource]
260 $c2007
520 $aThe development of models that allow forecasting yield tendencies is important to all sectors of the citrus industry. This work evaluated the influence of meteorological variables in different phases of the crop cycle in order to propose empirical models to estimate the number of fruits per plant (NFP) of 'Valencia' and 'Hamlin' sweet oranges. NFP sampling data from the citrus juice industry of the State of São Paulo, on the total of 15 harvests (1990/91 to 2004/05), classified into three age classes, and meteorological data of maximum and minimum air temperature and rainfall of Limeira, SP, Brazil, were utilized. Correlation coefficients were initially computed between the number of fruits per plant and each meteorological variable used for water balance and variables related to air temperature, in different periods. Linear multiple regression models were fit to describe the empirical relationship between NFP and the subsets of agrometeorological predictors that presented higher correlations in different phases of the crop cycle. The meteorological conditions during the phases of vegetative summer flush, pre-flowering, flowering and beginning of fruit growth influenced the number of fruits per plant. The proposed models presented adequate goodness-of-fit with determination coefficients varying from 0.72 to 0.87.
650 $aLaranja
650 $aMeteorologia
650 $aModelo Matemático
650 $aPrevisão de Safra
650 $aProdutividade
653 $aModelo de regressão linear
700 1 $aMOURÃO FILHO, F. de A. A.
700 1 $aMAIA, A. de H. N.
700 1 $aAVILÉS, T. E. C.
700 1 $aDOURADO NETO, D.
773 $tScientia Agricola, Piracicaba$gv.64, n.1, p.1-11, 2007.
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Registro original: |
Embrapa Meio Ambiente (CNPMA) |
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Origem |
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