Rapid and non-destructive prediction of mango quality attributes using Fourier transform near infrared spectroscopy and chemometrics

被引:37
作者
Munawar A.A. [1 ]
von Hörsten D. [2 ]
Wegener J.K. [2 ]
Pawelzik E. [3 ]
Mörlein D. [4 ]
机构
[1] Department of Agricultural Engineering, Syiah Kuala University, Banda Aceh
[2] Division of Agricultural Engineering, Department of Crop Science, University of Göttingen
[3] Division of Quality of Plant Products, Department of Crop Science, University of Göttingen
[4] Division of Product Knowledge - Quality of Animal Products, Department of Animal Science, University of Göttingen
关键词
Chemometrics; FT-NIR; Mango; NIRS; Quality;
D O I
10.1016/j.eaef.2015.12.004
中图分类号
学科分类号
摘要
To establish a non-destructive method for prediction of mango quality attributes, near infrared reflectance spectroscopy (NIRS) combined with chemometrics was studied. NIR spectra were recorded on intact mangos (cv. Kent, n = 58) in the wavelength range of 1000–2500 nm using a Fourier transform near infrared (FT-NIR) spectrometer, followed by its quality attributes measurement. Partial least squares (PLS) and principal component regression (PCR) based on various spectral pre-treatment (MSC, SNV and first derivative) were used to develop prediction models for quality attributes such as soluble solids content (SSC), titratable acidity (TA) and ascorbic acid (AA). The models yielded satisfactory results with coefficient of determination of calibration ranging from 0.66 to 0.91 (SSC), 0.94 to 0.98 (TA) and 0.62 to 0.92 (AA) while in cross validation the coefficient ranging from 0.51 to 0.66 (SSC), 0.90 to 0.95 (TA) and 0.43 to 0.61 (AA). Standard error resulted in calibration and cross validation were low. It is concluded that NIRS and chemometrics is feasible for rapid and non-destructive prediction of mango quality. © 2015 Asian Agricultural and Biological Engineering Association
引用
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页码:208 / 215
页数:7
相关论文
共 33 条
[1]  
Arya S.P., Mahajan M., Jain P., Non-spectrophotometric methods for the determination of vitamin C, Anal. Cimica Acta, 417, pp. 1-14, (2000)
[2]  
Bureau S., Ruiz D., Reich M., Gouble B., Bertrand D., Audergon J.M., Renard C.M., Rapid and non-destructive analysis of apricot fruit quality using FT-near-infrared spectroscopy, Food Chem., 113, pp. 1323-1328, (2009)
[3]  
Cen H., He Y., Theory and application of near infrared reflectance spectroscopy in determination of food quality, Trends Food Sci. Technol., 18, pp. 72-83, (2007)
[4]  
Clark R.N., Spectroscopy of rocks and minerals and principles of spectroscopy, Manual of Remote Sensing, Remote Sensing for the Earth Sciences, 3, pp. 3-58, (1999)
[5]  
Constantinou M.A., Papakonstantinou E., Benaki D., Spraul M., Shulpis K., Koupparis M.A., Mikros A., Application of nuclear magnetic resonance spectroscopy combined with principal component analysis in detecting inborn errors of metabolism using blood spots: a metabonomic approach, Anal. Cimica Acta, 511, pp. 303-312, (2004)
[6]  
Cozzolino D., Cynkar W.U., Shah N., Smith P., Multivariate data analysis applied to spectroscopy: potential application to juice and fruit quality, Food Res. Int., 44, pp. 1888-1896, (2011)
[7]  
Fearn T., Assessing calibrations: SEP, RPD, RER and R<sup>2</sup>, NIR News, 13, pp. 12-14, (2002)
[8]  
Flores K., Sanchez M.T., Perez-Marin D., Guerrero J.E., Garrido-Varo A., Feasibility in NIRS instruments for predicting internal quality in intact tomato, J. Food Eng., 91, pp. 311-318, (2009)
[9]  
Gomez A.H., He Y., Pereira A.G., Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques, J. Food Eng., 77, pp. 313-319, (2006)
[10]  
Jha S.N., Kingsly A.R.P., Chopra S., Non-destructive determination of firmness and yellowness of mango during growth and storage using visual spectroscopy, Biosyst. Eng., 94, pp. 397-402, (2006)