02578naa a2200337 a 450000100080000000500110000800800410001902400480006010000270010824501650013526000090030052015360030965000170184565000280186265000230189065000120191365000100192565000210193565000180195665000180197465300360199265300120202870000230204070000200206370000250208370000190210870000220212770000220214970000260217177300430219721229602020-06-03       2020    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.17660/th2019/74.6.42DOI1 aSANTOS NETO, J. P. dos  aPostharvest behavior of mangoes nondestructively sorted based on dry matter content during and after storage under controlled atmosphere.h[electronic resource]  c2020  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.  aChemometrics  aDry matter accumulation  aDry matter content  aMangoes  aManga  aMangifera Indica  aMatéria Seca  aPós-Colheita  aEspectrômetro de infravermelho  aVis-NIR1 aCARVALHO, L. C. de1 aLEITE, G. W. P.1 aCUNHA JÚNIOR, L. C.1 aGRATÃO, P. L.1 aFREITAS, S. T. de1 aALMEIDA, D. P. F.1 aTEIXEIRA, G. H. de A.  tFruitsgv. 74, n. 6, p. 294-302, 2020.