Département Sciences du vivant, Unité Amélioration des espèces et biodiversité, Centre wallon de Recherches agronomiques, B-5030 Gembloux, France.
J Sci Food Agric. 2013 Jan;93(2):238-44. doi: 10.1002/jsfa.5779. Epub 2012 Jul 2.
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.
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.
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.
苹果的维生素 C 和多酚含量是消费者非常关注的质量和营养参数,尤其是在健康方面。这些参数通常采用繁琐的参考方法进行测量。本研究旨在评估近红外(NIR)光谱法作为一种快速、无损的方法来测定苹果中的糖、维生素 C 和总多酚含量的潜力。
使用 NIR 和参考方法分析了 150 多种苹果基因型的质量参数。使用最小二乘支持向量机回归方法获得的结果表明,预测性能良好到非常好。低预测值标准误差,加上相对较高的预测比(RPD)值,证明了模型的精度,尤其是对于多酚和糖含量。高 RPD 值(分别为 5.1 和 4.3 用于多酚和糖)表明,可以根据其含量对苹果进行准确的分类。
NIR 光谱法与多元校准技术相结合,可用于准确测量苹果的质量参数。此外,在育种计划中,NIR 光谱法可以被认为是根据一系列浓度对品种进行分类的一种有趣工具。