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Registro Completo |
Biblioteca(s): |
Embrapa Instrumentação. |
Data corrente: |
16/11/2004 |
Data da última atualização: |
08/03/2010 |
Autoria: |
HERMANN, P. S. DE P.; YOSHIDA, C. M. P.; ANTUNES, A. J.; MARCONDES, J. A. |
Título: |
Surface evaluation of whey protein films by atomic force microscopy and water vapour permeability analysis. |
Ano de publicação: |
2004 |
Fonte/Imprenta: |
Packaging Technology and Science, Sussex, v.17, n. 5, p. 267-273, 2004. |
Idioma: |
Português |
Conteúdo: |
The atomic force microscopy (AFM) technique is a powerful tool for studying
surfaces and has been used to provide qualitative and quantitative information
about nanometer-scale matter properties that are often inaccessible by any other experimental technique. In this work AFM was used to evaluate the surfaces of
edible films produced with whey protein concentrate (WPC). The morphology and the roughness of the films were analysed. The effects of WPC and plasticizer
concentration were characterized in terms of water vapour permeability (WVP) and roughness parameters. Roughness was calculated through the images captured with AFM. AFM can be useful to identify structural changes of the film resulting from sample preparation. The results showed a relation between water vapour permeability and area roughness, through different sample preparation. The analyses of topography through roughness (Jbtained with AFM, demonstrated the correlation between the morphology of the film, obtained with nanometer resolution and WVP. |
Palavras-Chave: |
Filmes comestíveis; Força atômica microscópica. |
Thesaurus Nal: |
roughness. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01645naa a2200193 a 4500 001 1028675 005 2010-03-08 008 2004 bl --- 0-- u #d 100 1 $aHERMANN, P. S. DE P. 245 $aSurface evaluation of whey protein films by atomic force microscopy and water vapour permeability analysis. 260 $c2004 520 $aThe atomic force microscopy (AFM) technique is a powerful tool for studying surfaces and has been used to provide qualitative and quantitative information about nanometer-scale matter properties that are often inaccessible by any other experimental technique. In this work AFM was used to evaluate the surfaces of edible films produced with whey protein concentrate (WPC). The morphology and the roughness of the films were analysed. The effects of WPC and plasticizer concentration were characterized in terms of water vapour permeability (WVP) and roughness parameters. Roughness was calculated through the images captured with AFM. AFM can be useful to identify structural changes of the film resulting from sample preparation. The results showed a relation between water vapour permeability and area roughness, through different sample preparation. The analyses of topography through roughness (Jbtained with AFM, demonstrated the correlation between the morphology of the film, obtained with nanometer resolution and WVP. 650 $aroughness 653 $aFilmes comestíveis 653 $aForça atômica microscópica 700 1 $aYOSHIDA, C. M. P. 700 1 $aANTUNES, A. J. 700 1 $aMARCONDES, J. A. 773 $tPackaging Technology and Science, Sussex$gv.17, n. 5, p. 267-273, 2004.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
28/08/2023 |
Data da última atualização: |
26/10/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 4 |
Autoria: |
CASTRO, V. H. M. e de; PARREIRAS, T. C.; BOLFE, E. L. |
Afiliação: |
VICTÓRIA HELLENA MATUSEVICIUS E DE CASTRO, UNIVERSIDADE ESTADUAL DE CAMPINAS; TAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; EDSON LUIS BOLFE, CNPTIA, UNIVERSIDADE ESTADUAL DE CAMPINAS. |
Título: |
Disease detection in citrus crops using optical and thermal remote sensing: a literature review. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Engenharia na Agricultura, v. 31, p. 140-157, 2023. |
ISSN: |
2175-6813 |
DOI: |
https://doi.org/10.13083/reveng.v30i1.15448 |
Idioma: |
Português |
Notas: |
Errata - The acknowledgments of the article include: To the State of São Paulo Research Foundation (FAPESP), process number 2019/26222-6. The correct process number is 2022/09319-9. |
Conteúdo: |
Brazil stands out in the international citrus trade, especially due to its oranges, having produced around 16 million tons in 2021. However, productivity could be increased with greater control of diseases such as greening, which has spread around the world and leads to the total loss of affected trees. Given this scenario, it is necessary to perform fast and accurate detections in order to better manage actions and inputs. Since remote sensing is a pillar of digital agriculture, a literature review was carried out to analyze the use of optical and thermal sensors for the detection of diseases that affect citrus groves. For this purpose, the international databases Scopus and Web of Science were used to select references published between 2012 and 2022, resulting in twelve studies - most from China or the United States of America. The results showed a prevalence of methodologies that combine bands and spectral indices obtained through the use of multispectral and hyperspectral sensors, predominantly on board unmanned aircrafts (UAVs). Machine learning (ML) and deep learning (DL) classification algorithms produced good results in the detection of citrus groves affected by diseases, mainly greening. These results are affected by the stage of the infection, the presence or absence of symptoms, and the spectral and spatial resolutions of the sensors: the Red-Edge band and data with higher spatial detail result in more accurate classification models. However, the analyzed literature is still inconclusive regarding the early detection of infected plants. MenosBrazil stands out in the international citrus trade, especially due to its oranges, having produced around 16 million tons in 2021. However, productivity could be increased with greater control of diseases such as greening, which has spread around the world and leads to the total loss of affected trees. Given this scenario, it is necessary to perform fast and accurate detections in order to better manage actions and inputs. Since remote sensing is a pillar of digital agriculture, a literature review was carried out to analyze the use of optical and thermal sensors for the detection of diseases that affect citrus groves. For this purpose, the international databases Scopus and Web of Science were used to select references published between 2012 and 2022, resulting in twelve studies - most from China or the United States of America. The results showed a prevalence of methodologies that combine bands and spectral indices obtained through the use of multispectral and hyperspectral sensors, predominantly on board unmanned aircrafts (UAVs). Machine learning (ML) and deep learning (DL) classification algorithms produced good results in the detection of citrus groves affected by diseases, mainly greening. These results are affected by the stage of the infection, the presence or absence of symptoms, and the spectral and spatial resolutions of the sensors: the Red-Edge band and data with higher spatial detail result in more accurate classification models. However, the analyzed literat... Mostrar Tudo |
Palavras-Chave: |
Agricultura digital; Algoritmos de aprendizado de máquina; Citriculture; Digital agriculture; NDVI. |
Thesagro: |
Citricultura; Doença de Planta; Sensoriamento Remoto. |
Thesaurus NAL: |
Citrus; Greening disease; Plant diseases and disorders; Remote sensing. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/257157/1/AP-Disease-detection-2023.pdf
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Marc: |
LEADER 02737naa a2200325 a 4500 001 2156159 005 2023-10-26 008 2023 bl uuuu u00u1 u #d 022 $a2175-6813 024 7 $ahttps://doi.org/10.13083/reveng.v30i1.15448$2DOI 100 1 $aCASTRO, V. H. M. e de 245 $aDisease detection in citrus crops using optical and thermal remote sensing$ba literature review.$h[electronic resource] 260 $c2023 500 $aErrata - The acknowledgments of the article include: To the State of São Paulo Research Foundation (FAPESP), process number 2019/26222-6. The correct process number is 2022/09319-9. 520 $aBrazil stands out in the international citrus trade, especially due to its oranges, having produced around 16 million tons in 2021. However, productivity could be increased with greater control of diseases such as greening, which has spread around the world and leads to the total loss of affected trees. Given this scenario, it is necessary to perform fast and accurate detections in order to better manage actions and inputs. Since remote sensing is a pillar of digital agriculture, a literature review was carried out to analyze the use of optical and thermal sensors for the detection of diseases that affect citrus groves. For this purpose, the international databases Scopus and Web of Science were used to select references published between 2012 and 2022, resulting in twelve studies - most from China or the United States of America. The results showed a prevalence of methodologies that combine bands and spectral indices obtained through the use of multispectral and hyperspectral sensors, predominantly on board unmanned aircrafts (UAVs). Machine learning (ML) and deep learning (DL) classification algorithms produced good results in the detection of citrus groves affected by diseases, mainly greening. These results are affected by the stage of the infection, the presence or absence of symptoms, and the spectral and spatial resolutions of the sensors: the Red-Edge band and data with higher spatial detail result in more accurate classification models. However, the analyzed literature is still inconclusive regarding the early detection of infected plants. 650 $aCitrus 650 $aGreening disease 650 $aPlant diseases and disorders 650 $aRemote sensing 650 $aCitricultura 650 $aDoença de Planta 650 $aSensoriamento Remoto 653 $aAgricultura digital 653 $aAlgoritmos de aprendizado de máquina 653 $aCitriculture 653 $aDigital agriculture 653 $aNDVI 700 1 $aPARREIRAS, T. C. 700 1 $aBOLFE, E. L. 773 $tEngenharia na Agricultura$gv. 31, p. 140-157, 2023.
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