BACKGROUND: The vitamin C and polyphenol content of apples constitute quality and nutritional parameters of great interest for consumers, especially in terms of health. They are commonly measured using laborious reference methods. The purpose of this study was to evaluate the potential of near-infrared (NIR) spectroscopy as a rapid and non-destructive method to determine the sugar, vitamin C and total polyphenol content in apples. RESULTS: The quality parameters of more than 150 apple genotypes were analyzed using NIR and reference methods. The results obtained using the least squares support vector machine regression method showed good to very good prediction performance. Low standard error of prediction values, in addition to relatively high ratio to prediction (RPD) values, demonstrated the precision of the models, especially for polyphenol and sugar content. High RPD values (5.1 and 4.3 for polyphenol and sugar, respectively) indicated that an accurate classification of apples based on their content could be achieved. CONCLUSION: NIR spectroscopy coupled with the multivariate calibration technique could be used to accurately measure the quality parameters of apples. In addition, in the case of breeding programs, NIR spectroscopy can be considered an interesting tool for sorting varieties according to a range of concentrations.
BACKGROUND: The vitamin C and polyphenol content of apples constitute quality and nutritional parameters of great interest for consumers, especially in terms of health. They are commonly measured using laborious reference methods. The purpose of this study was to evaluate the potential of near-infrared (NIR) spectroscopy as a rapid and non-destructive method to determine the sugar, vitamin C and total polyphenol content in apples. RESULTS: The quality parameters of more than 150 apple genotypes were analyzed using NIR and reference methods. The results obtained using the least squares support vector machine regression method showed good to very good prediction performance. Low standard error of prediction values, in addition to relatively high ratio to prediction (RPD) values, demonstrated the precision of the models, especially for polyphenol and sugar content. High RPD values (5.1 and 4.3 for polyphenol and sugar, respectively) indicated that an accurate classification of apples based on their content could be achieved. CONCLUSION: NIR spectroscopy coupled with the multivariate calibration technique could be used to accurately measure the quality parameters of apples. In addition, in the case of breeding programs, NIR spectroscopy can be considered an interesting tool for sorting varieties according to a range of concentrations.
Authors: Sangam L Dwivedi; Hari D Upadhyaya; Ill-Min Chung; Pasquale De Vita; Silverio García-Lara; Daniel Guajardo-Flores; Janet A Gutiérrez-Uribe; Sergio O Serna-Saldívar; Govindasamy Rajakumar; Kanwar L Sahrawat; Jagdish Kumar; Rodomiro Ortiz Journal: Front Plant Sci Date: 2016-06-03 Impact factor: 5.753