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| 106. |  | BRANDAO, Z. N.; GREGO, C. R.; JORGE, L. A. de C.; MANJOLIN, R. C. Multispectral reflectance and geostatistic methods to estimate leaf nitrogen content and cotton yield. In: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 14, p. 143-154.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Algodão; Embrapa Instrumentação. |
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| 107. | | FASIABEN, M. do C. R.; GREGO, C. R.; MORAES, A. S.; ALMEIDA, M. M. T. B. Pecuária de corte na agropecuária brasileira: evolução segundo os Censos Agropecuários 2006 e 2017. In: CONGRESSO DA SOCIEDADE BRASILEIRA DE ECONOMIA, ADMINISTRAÇÃO E SOCIOLOGIA RURAL, 60., 2002, Natal. Agricultura familiar, sistemas agroalimentares e mudanças climáticas: desafios rumo aos ODS: anais. Natal: Universidade Federal do Rio Grande do Norte, 2022. 16 p. Sober 2022. GT07.| Biblioteca(s): Embrapa Soja. |
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| 118. | | MANGABEIRA, J. A. de C.; ROMEIRO, A. R.; TOSTO, S. G.; GREGO, C. R. Valuation of environment services provided by woodlands to agriculture: the coffee example in Machadinho d'Oeste, RO, Brazil. In: INTERNATIONAL SOCIETY FOR ECOLOGICAL ECONOMICS, 1., 2012, Rio de Janeiro, RJ. Anais... Rio de Janeiro: ISEE, 2012. 4 p.| Biblioteca(s): Embrapa Territorial. |
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| Registros recuperados : 281 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Rondônia. |
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Data corrente: |
15/09/2020 |
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Data da última atualização: |
15/09/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
DIAS, J. A.; PACHECO, I. F.; GREGO, C. R.; FARIA, G. V.; CRUZ, P. G. da. |
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Afiliação: |
JULIANA ALVES DIAS, CPAF-RO; IVANETE FRANCESCHINI PACHECO, UNIR; CELIA REGINA GREGO, CNPTIA; GUILHERME VIEIRA FARIA, CPAF-RO; PEDRO GOMES DA CRUZ, CPAF-RO. |
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Título: |
Spatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Semina: Ciências Agrárias, v. 41, n. 5, p. 2195-2208, 2020. |
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DOI: |
http://dx.doi.org/10.5433/1679-0359.2020v41n5supl1p2195 |
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Idioma: |
Inglês |
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Notas: |
Suplemento 1. |
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Conteúdo: |
Abstract. Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state?s production chain. There were no significant differences in this frequency for SCC and SPC, neither between the microregions studied, nor between the dry and rainy season (p > 0.05). The analysis of variance considered the period of year and type of cooling tank and showed higher SPC and SCC in the rainy season (p < 0.05); SCC and SPC were higher in collective tanks used by more than 5 farmers (p < 0.05). Spatial dependence was weak for SCC (DD = 22.02) and moderate for SPC (DD = 25.93), indicating the Machadinho do Oeste region as a priority area for mastitis control, and the Ariquemes microregion and west of the Porto Velho microregion as areas of high SPC. The results demonstrated the feasibility of spatial analysis as a tool for evaluating of refrigerated raw milk quality indicators and may support the definition of public and private strategies and policies to improve the milk quality and legislation adequacy. MenosAbstract. Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state?s production chain. There were no significant differences... Mostrar Tudo |
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Palavras-Chave: |
Amazônia Ocidental; Bacterial count; Contagem bacteriana; Contagem de bactérias; Contagem de células somáticas; Krigagem; Leite cru resfriado; Qualidade do leite; Rondônia; Western Amazon. |
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Thesagro: |
Leite. |
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Thesaurus NAL: |
Kriging; Milk quality; Somatic cell count. |
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Categoria do assunto: |
--
Q Alimentos e Nutrição Humana |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/216006/1/cpafro-18438.pdf
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Marc: |
LEADER 03496naa a2200361 a 4500
001 2124935
005 2020-09-15
008 2020 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.5433/1679-0359.2020v41n5supl1p2195$2DOI
100 1 $aDIAS, J. A.
245 $aSpatial characterization of hygienic-sanitary indicators of refrigerated raw milk from three microregions of the Rondônia state.$h[electronic resource]
260 $c2020
500 $aSuplemento 1.
520 $aAbstract. Bacterial count (SPC) and somatic cell count (SCC) are considered universal indicators of milk quality. The objective of this study was to identify SPC and SCC clusters in milk samples from three microregions of the state of Rondônia and to evaluate the influence of year period and tank type on these indicators. A total of 566 milk cooling tanks linked to dairy industries with the Federal Inspection Service located in the Ariquemes, Ji-Paraná and Porto Velho microregions were evaluated. The SPC and SCC results of the tank samples and the geographical coordinates were obtained from the dairy industry database; the study focused on the results of official analyses carried out by the Laboratories of Milk Quality accredited to the Ministry of Agriculture, Livestock and Food Supply (MAPA) in 2015, constituting a pool of 6,792 data subsets from 2,209 farmers. To elaborate the spatial distribution maps of the quality indicators, the ArcView 3.1® software was used. Spatial dependence was evaluated by geostatistics, using the ordinary kriging method for data interpolation. Variance analysis (ANOVA) was performed using the SAS 9.0 GLM procedure on the logarithmic transformation of SCC and SPC, using as variables the type of tank (individual and collective) and season (dry and rainy). The frequency of milk quality adjustments to the limits defined in the legislation has shown that SPC is a major challenge for the state?s production chain. There were no significant differences in this frequency for SCC and SPC, neither between the microregions studied, nor between the dry and rainy season (p > 0.05). The analysis of variance considered the period of year and type of cooling tank and showed higher SPC and SCC in the rainy season (p < 0.05); SCC and SPC were higher in collective tanks used by more than 5 farmers (p < 0.05). Spatial dependence was weak for SCC (DD = 22.02) and moderate for SPC (DD = 25.93), indicating the Machadinho do Oeste region as a priority area for mastitis control, and the Ariquemes microregion and west of the Porto Velho microregion as areas of high SPC. The results demonstrated the feasibility of spatial analysis as a tool for evaluating of refrigerated raw milk quality indicators and may support the definition of public and private strategies and policies to improve the milk quality and legislation adequacy.
650 $aKriging
650 $aMilk quality
650 $aSomatic cell count
650 $aLeite
653 $aAmazônia Ocidental
653 $aBacterial count
653 $aContagem bacteriana
653 $aContagem de bactérias
653 $aContagem de células somáticas
653 $aKrigagem
653 $aLeite cru resfriado
653 $aQualidade do leite
653 $aRondônia
653 $aWestern Amazon
700 1 $aPACHECO, I. F.
700 1 $aGREGO, C. R.
700 1 $aFARIA, G. V.
700 1 $aCRUZ, P. G. da
773 $tSemina: Ciências Agrárias$gv. 41, n. 5, p. 2195-2208, 2020.
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Registro original: |
Embrapa Rondônia (CPAF-RO) |
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