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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
03/06/2020 |
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Data da última atualização: |
03/06/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SANTOS NETO, J. P. dos; CARVALHO, L. C. de; LEITE, G. W. P.; CUNHA JÚNIOR, L. C.; GRATÃO, P. L.; FREITAS, S. T. de; ALMEIDA, D. P. F.; TEIXEIRA, G. H. de A. |
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Afiliação: |
J. P. dos Santos Neto, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Campus de Jaboticabal; L. C. de Carvalho, UNESP; G. W. P. Leite, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Campus de Jaboticabal; L. C. Cunha Júnior, Universidade Federal de Goiás; P. L. Gratão, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Campus de Jaboticabal; SERGIO TONETTO DE FREITAS, CPATSA; D. P. F. Almeida, Universidade de Lisboa, Instituto Superior de Agronomia, Tapada da Ajuda, Lisboa; G. H. de Almeida Teixeira, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Campus de Jaboticabal. |
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Título: |
Postharvest behavior of mangoes nondestructively sorted based on dry matter content during and after storage under controlled atmosphere. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Fruits, v. 74, n. 6, p. 294-302, 2020. |
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DOI: |
https://doi.org/10.17660/th2019/74.6.4 |
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Idioma: |
Inglês |
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Conteúdo: |
As maturity plays an important role during controlled atmosphere (CA) storage, the objective of this study was to evaluate if mangoes sorted based on visual characteristics behave differently during CA storage than mangoes sorted based on 150 g kg-1 dry matter (DM) content using near-infrared (Vis-NIR) spectrometer. Materials and methods ? ?Palmer? mangoes were harvested and DM predicted by partial least squares regression (PLSR) model developed. Fruit quality was evaluated at harvest, after 30 d of CA storage, and after 30 d plus 4 d at ambient conditions. Results and discussion PLSR model developed with fruit from 2015/2016 and 2016/2017 seasons was able to predict DM content from mangoes produced in different regions (Petrolina, PE), but with high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2 P (0.19). Therefore, Vis-NIR spectra from mangoes produced in Petrolina, PE were incorporated into the data set and a new model was developed (RMSEv = 13.8 g kg-1, and R2 V = 0.63). With the new PLSR model it was possible to sort mangoes produced in Petrolina, PE with 150 g kg-1 DM. Quality differences were not observed between fruit sorted based on 150 g kg-1 DM and based on visual appearance. However, the mangoes sorted based on 150 g kg-1 DM presented lower standard deviation, indicating a more homogeneous fruit batch. Conclusion ? The use of portable Vis-NIR spectrometer allows a more uniform sorting of mangoes, which can be used to improve the quality of mangoes that reach the consumer. MenosAs maturity plays an important role during controlled atmosphere (CA) storage, the objective of this study was to evaluate if mangoes sorted based on visual characteristics behave differently during CA storage than mangoes sorted based on 150 g kg-1 dry matter (DM) content using near-infrared (Vis-NIR) spectrometer. Materials and methods ? ?Palmer? mangoes were harvested and DM predicted by partial least squares regression (PLSR) model developed. Fruit quality was evaluated at harvest, after 30 d of CA storage, and after 30 d plus 4 d at ambient conditions. Results and discussion PLSR model developed with fruit from 2015/2016 and 2016/2017 seasons was able to predict DM content from mangoes produced in different regions (Petrolina, PE), but with high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2 P (0.19). Therefore, Vis-NIR spectra from mangoes produced in Petrolina, PE were incorporated into the data set and a new model was developed (RMSEv = 13.8 g kg-1, and R2 V = 0.63). With the new PLSR model it was possible to sort mangoes produced in Petrolina, PE with 150 g kg-1 DM. Quality differences were not observed between fruit sorted based on 150 g kg-1 DM and based on visual appearance. However, the mangoes sorted based on 150 g kg-1 DM presented lower standard deviation, indicating a more homogeneous fruit batch. Conclusion ? The use of portable Vis-NIR spectrometer allows a more uniform sorting of mangoes, which can be used to improve the quality of ... Mostrar Tudo |
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Palavras-Chave: |
Espectrômetro de infravermelho; Vis-NIR. |
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Thesagro: |
Manga; Mangifera Indica; Matéria Seca; Pós-Colheita. |
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Thesaurus Nal: |
Chemometrics; Dry matter accumulation; Dry matter content; Mangoes. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02578naa a2200337 a 4500
001 2122960
005 2020-06-03
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.17660/th2019/74.6.4$2DOI
100 1 $aSANTOS NETO, J. P. dos
245 $aPostharvest behavior of mangoes nondestructively sorted based on dry matter content during and after storage under controlled atmosphere.$h[electronic resource]
260 $c2020
520 $aAs maturity plays an important role during controlled atmosphere (CA) storage, the objective of this study was to evaluate if mangoes sorted based on visual characteristics behave differently during CA storage than mangoes sorted based on 150 g kg-1 dry matter (DM) content using near-infrared (Vis-NIR) spectrometer. Materials and methods ? ?Palmer? mangoes were harvested and DM predicted by partial least squares regression (PLSR) model developed. Fruit quality was evaluated at harvest, after 30 d of CA storage, and after 30 d plus 4 d at ambient conditions. Results and discussion PLSR model developed with fruit from 2015/2016 and 2016/2017 seasons was able to predict DM content from mangoes produced in different regions (Petrolina, PE), but with high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2 P (0.19). Therefore, Vis-NIR spectra from mangoes produced in Petrolina, PE were incorporated into the data set and a new model was developed (RMSEv = 13.8 g kg-1, and R2 V = 0.63). With the new PLSR model it was possible to sort mangoes produced in Petrolina, PE with 150 g kg-1 DM. Quality differences were not observed between fruit sorted based on 150 g kg-1 DM and based on visual appearance. However, the mangoes sorted based on 150 g kg-1 DM presented lower standard deviation, indicating a more homogeneous fruit batch. Conclusion ? The use of portable Vis-NIR spectrometer allows a more uniform sorting of mangoes, which can be used to improve the quality of mangoes that reach the consumer.
650 $aChemometrics
650 $aDry matter accumulation
650 $aDry matter content
650 $aMangoes
650 $aManga
650 $aMangifera Indica
650 $aMatéria Seca
650 $aPós-Colheita
653 $aEspectrômetro de infravermelho
653 $aVis-NIR
700 1 $aCARVALHO, L. C. de
700 1 $aLEITE, G. W. P.
700 1 $aCUNHA JÚNIOR, L. C.
700 1 $aGRATÃO, P. L.
700 1 $aFREITAS, S. T. de
700 1 $aALMEIDA, D. P. F.
700 1 $aTEIXEIRA, G. H. de A.
773 $tFruits$gv. 74, n. 6, p. 294-302, 2020.
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