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4. | | ÁVILA, S.; HORNUNG, P. S.; TEIXEIRA, G. L.; BEUX, M. R.; LAZZAROTTO, M.; RIBANI, R. H. A chemometric approach for moisture control in stingless bee honey using near infrared spectroscopy. Journal of Near Infrared Spectroscopy, v. 26, n. 6, p. 379-388, Dec. 2018. Biblioteca(s): Embrapa Florestas. |
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5. | | SALIBA, E. de O. S.; RODRIGUEZ, N. M.; PILÓ-VELOSO, D.; TEIXEIRA, G. L.; RIBEIRO, S. L. M. Estudo comparativo da digestibilidade pela técnica da coleta total com a lignina purificada como indicador de digestibilidade para ovinos em experimento com feno de tifton 85. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 40., 2003, Santa Maria, RS. Otimizando a produção animal: anais. Santa Maria: Sociedade Brasileira de Zootecnia, 2003. 3 f. 1 CD ROM. Biblioteca(s): Embrapa Caprinos e Ovinos. |
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7. | | FERREIRA, A. C. H.; RODRIGUES, N. M.; NEIVA, J. N. M.; LÔBO, R. N. B.; TEIXEIRA, G. L.; OLIVEIRA FILHO, G. S. de; NUNES, F. C. de S. Consumo voluntário e digestibilidade aparente da matéria seca das silagens de capim elefante com diferentes níveis de subprodutos da indústria do suco de abacaxi. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 40., 2003, Santa Maria, RS. Otimizando a produção animal: anais. Santa Maria: Sociedade Brasileira de Zootecnia, 2003. 5 f. 1 CD ROM. Biblioteca(s): Embrapa Caprinos e Ovinos. |
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9. | | ÁVILA, S.; LAZZAROTTO, M.; HORNUNG, P. S.; TEIXEIRA, G. L.; ITO, V. C.; BELLETTINI, M. B.; BEUX, M. R.; BETA, T.; RIBAN, R. H. Influence of stingless bee genus (Scaptotrigona and Melipona) on the mineral content, physicochemical and microbiological properties of honey. Journal of Food Science and Technology, v. 56, n. 10, p. 4742-4748, Oct. 2019. Sort communication. Biblioteca(s): Embrapa Florestas. |
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10. | | HORNUNG, P. S.; BARBI, R. C. T.; TEIXEIRA, G. L.; ÁVILA, S.; SILVA, F. L. de A. da; LAZZAROTTO, M.; SILVEIRA, J. L. M.; BETA, T.; RIBANI, R. H. Brazilian Amazon white yam (Dioscorea sp.) starch: impact on functional properties due to chemical and physical modifications processes. Journal of Thermal Analysis and Calorimetry, v. 134, n. 3, p. 2075-2088, Dec. 2018. Biblioteca(s): Embrapa Florestas. |
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11. | | FERREIRA, J. J. C.; BORGES, A. L. C. C.; SILVA, R. R. e; RIBEIRO, C. G. M.; RIBEIRO, P. V.; RIBEIRO JUNIOR, G. de O.; GONÇALVES, L. C.; RODRIGUES, J. A. S.; BORGES, I.; PATRIZI, W. L.; CAMPOS, M. M.; RODRIGUEZ, N. M.; TEIXEIRA, G. L. Componentes da parede celular das silagens de seis genótipos de sorgo (Sorghum bicolor (L.) Moench). In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 43., 2006, João Pessoa. Anais... João Pessoa: SBZ: UFPB, 2006. 1 CD-ROM. Biblioteca(s): Embrapa Milho e Sorgo. |
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Registro Completo
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
14/01/2019 |
Data da última atualização: |
14/01/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
ÁVILA, S.; HORNUNG, P. S.; TEIXEIRA, G. L.; BEUX, M. R.; LAZZAROTTO, M.; RIBANI, R. H. |
Afiliação: |
Suelen Ávila, UFPR; Polyanna Silveira Hornung, UFPR; Gerson Lopes Teixeira, UFPR; Márcia Regina Beux, UFPR; MARCELO LAZZAROTTO, CNPF; Rosemary Hoffmann Ribani, UFPR. |
Título: |
A chemometric approach for moisture control in stingless bee honey using near infrared spectroscopy. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Journal of Near Infrared Spectroscopy, v. 26, n. 6, p. 379-388, Dec. 2018. |
DOI: |
10.1177/0967033518805254 |
Idioma: |
Inglês |
Conteúdo: |
Honey is a product that is often adulterated by the addition of water. Stingless bee honey naturally has a higher moisture content than that produced by the traditional Apis mellifera. In most countries, there is a lack of quality standards and methods to characterise and assure the authenticity of stingless bee honey, which demands for the development of fast methods to assess its main properties, avoiding potential fraud. Thus, this work aimed to develop a non-destructive moisture determination method for stingless bee honey based on diffuse reflectance near infrared spectroscopy combined with chemometrics. Thirty-two honey samples from four stingless bee species (Melipona quadrifasciata, Melipona marginata, Melipona bicolor and Scaptotrigona bipuncata) were used to develop calibration models using partial least squares regression analyses. Results revealed intense absorption bands in C-H, O-H and C-O vibrations in the spectra of stingless bee honey. The calibration model was used to predict the moisture content in honey from an external group. The prediction of the honey's moisture showed good correlation (r2 = 0.93) with the refraction index method and an average error of 2.14%. The statistics variables for the calibration (R2 = 0.947, SEP = 1.005 and RPD = 4.3) revealed that this model can be used to predict the moisture from stingless bee honey and that near infrared spectroscopy is a reliable tool to be applied in quality control with rapid, simple and accurate results. MenosHoney is a product that is often adulterated by the addition of water. Stingless bee honey naturally has a higher moisture content than that produced by the traditional Apis mellifera. In most countries, there is a lack of quality standards and methods to characterise and assure the authenticity of stingless bee honey, which demands for the development of fast methods to assess its main properties, avoiding potential fraud. Thus, this work aimed to develop a non-destructive moisture determination method for stingless bee honey based on diffuse reflectance near infrared spectroscopy combined with chemometrics. Thirty-two honey samples from four stingless bee species (Melipona quadrifasciata, Melipona marginata, Melipona bicolor and Scaptotrigona bipuncata) were used to develop calibration models using partial least squares regression analyses. Results revealed intense absorption bands in C-H, O-H and C-O vibrations in the spectra of stingless bee honey. The calibration model was used to predict the moisture content in honey from an external group. The prediction of the honey's moisture showed good correlation (r2 = 0.93) with the refraction index method and an average error of 2.14%. The statistics variables for the calibration (R2 = 0.947, SEP = 1.005 and RPD = 4.3) revealed that this model can be used to predict the moisture from stingless bee honey and that near infrared spectroscopy is a reliable tool to be applied in quality control with rapid, simple and accurate result... Mostrar Tudo |
Palavras-Chave: |
Controle de umidade; Meliponini; Moisture; Multivariate calibration; Partial least square regression. |
Thesagro: |
Mel. |
Thesaurus NAL: |
Quality control. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 02346naa a2200277 a 4500 001 2103811 005 2019-01-14 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1177/0967033518805254$2DOI 100 1 $aÁVILA, S. 245 $aA chemometric approach for moisture control in stingless bee honey using near infrared spectroscopy.$h[electronic resource] 260 $c2018 520 $aHoney is a product that is often adulterated by the addition of water. Stingless bee honey naturally has a higher moisture content than that produced by the traditional Apis mellifera. In most countries, there is a lack of quality standards and methods to characterise and assure the authenticity of stingless bee honey, which demands for the development of fast methods to assess its main properties, avoiding potential fraud. Thus, this work aimed to develop a non-destructive moisture determination method for stingless bee honey based on diffuse reflectance near infrared spectroscopy combined with chemometrics. Thirty-two honey samples from four stingless bee species (Melipona quadrifasciata, Melipona marginata, Melipona bicolor and Scaptotrigona bipuncata) were used to develop calibration models using partial least squares regression analyses. Results revealed intense absorption bands in C-H, O-H and C-O vibrations in the spectra of stingless bee honey. The calibration model was used to predict the moisture content in honey from an external group. The prediction of the honey's moisture showed good correlation (r2 = 0.93) with the refraction index method and an average error of 2.14%. The statistics variables for the calibration (R2 = 0.947, SEP = 1.005 and RPD = 4.3) revealed that this model can be used to predict the moisture from stingless bee honey and that near infrared spectroscopy is a reliable tool to be applied in quality control with rapid, simple and accurate results. 650 $aQuality control 650 $aMel 653 $aControle de umidade 653 $aMeliponini 653 $aMoisture 653 $aMultivariate calibration 653 $aPartial least square regression 700 1 $aHORNUNG, P. S. 700 1 $aTEIXEIRA, G. L. 700 1 $aBEUX, M. R. 700 1 $aLAZZAROTTO, M. 700 1 $aRIBANI, R. H. 773 $tJournal of Near Infrared Spectroscopy$gv. 26, n. 6, p. 379-388, Dec. 2018.
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