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Registro Completo |
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Biblioteca(s): |
Embrapa Agroindústria de Alimentos. |
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Data corrente: |
20/08/1998 |
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Data da última atualização: |
20/08/1998 |
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Autoria: |
MARTENS, H.; RUSSWURM JR. H. ed. |
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Título: |
Food research and data analysis. |
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Ano de publicação: |
1983 |
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Fonte/Imprenta: |
London: Applied Science Publishers, 1983. |
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Páginas: |
535p. |
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ISBN: |
0-85334-206-7 |
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Idioma: |
Inglês |
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Conteúdo: |
Introductory remarks. Uderstanding food reserach data. Data analysis: multivariate or univariate and other difficulties. Quantitative analysis of qualitative data. Extracting information from spectrophotometric curves. Predicting chemical composition from visible and near-infrared spectra. The design and practical use of an overall quality index for food produts. Patter recognition: finding and using regularities in multivariate data. Classification of olive oils from their fatty acid composition. Some useful multivaritate techniques relevant to classifying and identifying microbes. Multivariate infrared and near-infrared spectroscopy. Rapid analysis of protein fat and water in meat. Multivariate calibration of fluorescence data for quntitative analysis of cereal composition. Individual differences scaling of taste and smell. Evaluation of the performance of panel judges. Qauntification of sensory colour differences from physical measurement. Implications for food appearance. Analysis of sensory data on food texture. Simplication of sensory assessment profiles and their relationship to preference and acceptability data. Projection for computes hardware development and use. Intelligent instruments of the future. Closing remarks. Matrix algebra for data analysis. A layman's guide to multivariate data analysis. |
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Palavras-Chave: |
Analise de alimentos; Statistic. |
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Thesagro: |
Estatística. |
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Thesaurus Nal: |
food analysis. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01813nam a2200193 a 4500
001 1412733
005 1998-08-20
008 1983 bl uuuu 00u1 u #d
020 $a0-85334-206-7
100 1 $aMARTENS, H.
245 $aFood research and data analysis.
260 $aLondon: Applied Science Publishers$c1983
300 $a535p.
520 $aIntroductory remarks. Uderstanding food reserach data. Data analysis: multivariate or univariate and other difficulties. Quantitative analysis of qualitative data. Extracting information from spectrophotometric curves. Predicting chemical composition from visible and near-infrared spectra. The design and practical use of an overall quality index for food produts. Patter recognition: finding and using regularities in multivariate data. Classification of olive oils from their fatty acid composition. Some useful multivaritate techniques relevant to classifying and identifying microbes. Multivariate infrared and near-infrared spectroscopy. Rapid analysis of protein fat and water in meat. Multivariate calibration of fluorescence data for quntitative analysis of cereal composition. Individual differences scaling of taste and smell. Evaluation of the performance of panel judges. Qauntification of sensory colour differences from physical measurement. Implications for food appearance. Analysis of sensory data on food texture. Simplication of sensory assessment profiles and their relationship to preference and acceptability data. Projection for computes hardware development and use. Intelligent instruments of the future. Closing remarks. Matrix algebra for data analysis. A layman's guide to multivariate data analysis.
650 $afood analysis
650 $aEstatística
653 $aAnalise de alimentos
653 $aStatistic
700 1 $aRUSSWURM JR. H. ed.
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Registro original: |
Embrapa Agroindústria de Alimentos (CTAA) |
