Determination of some internal quality parameters of apricot using Fourier transform-NIR spectroscopy

The aim of this study was to predict the characteristics of internal quality attributes (firmness, soluble solids content and color values) of the Tokaloğlu apricot cultivar (Prunus armeniaca L) by nondestructive measurements using FT-NIR spectrometer. The experiments were conducted on two different apricot groups, one collected from a the tree with short intervals during a period of about 20 days and the other once all collected stored in cold storage (0-0,5 0C, 90-95 % humidity) for about 20 days. Reflectance measurements of apricots were performed using bifurcated fiber optic probe between 780 and 2500 nm. After spectral measurements, firmness and soluble solids content were measured using standard methods which damaged the apricots. Calibration methods were developed between the physical parameters, which were measured using standard methods, and the spectral measurements using Partial Least Squares method (PLS). Good correlations were obtained in calibration and validation for Magness-Taylor (MT) maximum force, with a coefficient of determination (R2) of 0,82 (RMSEE=4,45) in calibration and 0,80 (RMSECV=4,68) in validation for tree application. However, coefficient of determination for the cold storage apricots was low compared to tree application with 0,47 (RMSEE=4,65) in calibration and 0,41 (RMSEE=5,51) in validation. For MT slope , with a coefficient of determination (R2) of 0,79 (RMSEE=0,83) in calibration and 0,77 (RMSECV=0,88) in validation for tree application. And for the cold storage apricots the coefficient of determination was (R2) 0,56 (RMSEE=0,69) in calibration and 0,47 (RMSECV=0,80) for validation. Good correlations obtained for MT area which coefficient of determination (R2) 0,75 (RMSEE=20,1) in calibration and R2=0,71 (RMSECV=21) in validation for tree application.Good prediction values were obtained for soluble solids content for both applications (tree and cold storage) using FT-NIR spectroscopy. The best coefficient of determination was obtained for tree application with 0,77 (RMSEE=1,45) in calibration and 0,75 (RMSECV=1,51) in validation. Similar results were obtained for soluble solids content prediction for cold storage apricots. Correlation values for prediction of chroma and hue were low for tree application, with R2= 0,55 (RMSECV= 3,38) for chroma and with R2=0,16 (RMSECV= 0,49) for hue. The results showed that NIR spectroscopy has a good potential to predict internal quality assessments of apricots and partly surface quality features non-destructively.