EVALUATION THE PERFORMANCE OF HYPERSPECTRAL REFLECTANCE SENSOR FOR ESTIMATING THE HARDNESS AND BIOCHEMICAL PARAMETERS OF TOMATO FRUITS | ||
| Misr Journal of Agricultural Engineering | ||
| Article 16, Volume 34, Issue 3, July 2017, Pages 1389-1408 PDF (1.08 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/mjae.2017.97481 | ||
| Authors | ||
| S. Elsayed1; M. I. Ghazy2 | ||
| 1Assoc. Prof. of Agric. Eng., Evaluation of Natural Resources Department, Environmental Studies and Research Institute, Sadat City University, Egypt. | ||
| 2Lecturer of Agric. Eng., Faculty of Agric., Mansoura University, Egypt. | ||
| Abstract | ||
| Mechanical and biochemical analysis for assessing tomato fruit quality in food processing are the traditional methods, which leads to the destruction of fruits and is time consuming. Similarly, for valuating large quantities of tomato fruits for export, numerous observations are required to characterize them; such methods cannot easily account for rapid changes in these parameters. In this study the performance of hyperspectral passive reflectance sensing at various ripening degrees of tomato fruits was test its relationship to hardness, fruit water content, soluble solids content percentage, titratable acidity and pH via simple linear regression analysis. The results showed that statistically significant relationships between all spectral reflectance indices derived from near infrared (NIR) with measured parameters were found. The spectral index R1000/R716, showed the highest coefficients of determination for the hardness of tomato (R2 = 0.85***), the spectral index R970/R964, showed the highest coefficients of determination for the fruit water content (R2= 0.70***), soluble solids content (R2= 0.86***) and titratable acidity (R2= 0.82***) as well as the spectral index R970/R726, showed the highest coefficients of determination for the titratable acidity (R2= 0.78***) of tomato fruits. In conclusion, the using of spectral sensing may open an avenue in post-harvest and food processing for fast, high-throughput assessments mechanical and biochemical of tomato fruits. | ||
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