Food Analytical Methods

, Volume 6, Issue 3, pp 826-837

First online:

Application of NIRS for Nondestructive Measurement of Quality Parameters in Intact Oranges During On-Tree Ripening and at Harvest

  • María-Teresa SánchezAffiliated withDepartment of Bromatology and Food Technology, University of Cordoba Email author 
  • , María-José De la HabaAffiliated withDepartment of Bromatology and Food Technology, University of Cordoba
  • , Ildefonso SerranoAffiliated withDepartment of Bromatology and Food Technology, University of Cordoba
  • , Dolores Pérez-MarínAffiliated withDepartment of Animal Production, University of Cordoba Email author 

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External and internal quality parameters were measured in oranges (Citrus sinensis (L.) Osbeck cv. “Powell Summer Navel”) during on-tree ripening and at harvest using near-infrared reflectance (NIR) spectroscopy. The performance of two NIRS instruments was evaluated: a handheld microelectromechanical system spectrophotometer working in the 1,600- to 2,400-nm range, and a diode array visible–NIR spectrophotometer working in the 380- to 1,700-nm range. Spectra and analytical data were used to construct MPLS prediction models for quantifying weight, size (equatorial and axial diameters), color (L*, a*, b*, C*, h*, and color index), texture (firmness and maximum penetration force), yield (pericarp thickness, juice weight, and juice content), and chemical parameters (soluble solids content, pH, titratable acidity, and maturity index). Both instruments yielded promising results for on-tree and at-harvest quality measurements, but models constructed using the diode array instrument provided greater predictive capacity, particularly for fruit size (equatorial and axial diameters) and total soluble solids content. Subsequent evaluation of the LOCAL algorithm revealed that it increased the predictive capacity of models constructed for all the main parameters tested. These results confirm that noninvasive NIRS technology can be used to simultaneously evaluate external and internal quality parameters in intact oranges both during on-tree ripening and at harvest, thus making it easier for farmers to monitor the ripening process and also to optimize harvest timing in order to meet the demands of the citrus-fruit industry.


Near-IR spectroscopy Portable sensors MEMS technology Orange Quality parameters On-tree At harvest