Author(s):
Dos Santos Neto, J. P. [UNESP] ; De Carvalho, L. C. [UNESP] ; Leite, G. W.P. [UNESP] ; Cunha Júnior, L. C. ; Gratão, P. L. [UNESP] ; De Freitas, S. T. ; Almeida, D. P.F. ; De Almeida Teixeira, G. H. [UNESP]
Date: 2020
Persistent ID: http://hdl.handle.net/11449/199972
Origin: Oasisbr
Subject(s): Chemometrics; Dry matter; Mangifera indica L. 'Palmer'; Partial least squares regression; Portable visible-near infrared (Vis-NIR) spectrometer; Chemometrics; Chemometrics; Dry matter; Dry matter; Mangifera indica L. 'Palmer'; Mangifera indica L. 'Palmer'; Partial least squares regression; Partial least squares regression; Portable visible-near infrared (Vis-NIR) spectrometer; Portable visible-near infrared (Vis-NIR) spectrometer
Description
Made available in DSpace on 2020-12-12T01:54:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01
Introduction - 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). 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 a different region (Petrolina, PE), but with high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2P (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 R2V = 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.
Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n
Universidade Estadual Paulista (UNESP) Faculdade de Ciências Farmacêuticas (FCFAR) Departamento de Alimentos e Nutrição Campus de Araraquara, Rodovia Araraquara-Jaú, km 1 - CP 502
Universidade Federal de Goiás Escola de Agronomia Setor de Horticultura Campus Samambaia, Rodovia Goiânia Nova Veneza km 0
Empresa Brasileira de Pesquisa Agropecuária, Semiárido Rodovia BR-428 Km 152 s/n
Universidade de Lisboa Instituto Superior de Agronomia
Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n
Universidade Estadual Paulista (UNESP) Faculdade de Ciências Farmacêuticas (FCFAR) Departamento de Alimentos e Nutrição Campus de Araraquara, Rodovia Araraquara-Jaú, km 1 - CP 502
