TÜBİTAK Marmara Research Center, Life Sciences, Food Innovation Technologies Research Group, Gebze, Kocaeli, Türkiye.
Faculty of Engineering, Food Engineering Department, Yıldız Technical University, Istanbul, Türkiye.
J Food Sci. 2024 Aug;89(8):4806-4822. doi: 10.1111/1750-3841.17214. Epub 2024 Jul 16.
Turkey is the leading producer of hazelnuts, contributing to 62% of the total global production. Among 18 distinct local hazelnut cultivars, Giresun Tombul is the only cultivar that has received Protected Designation of Origin denomination from the European Comission (EC). However, there is currently no practical objective method to ensure its geographic origin. Therefore, in this study NIR and Raman spectroscopy, along with chemometric methods, such as principal component analysis, PLS-DA (partial least squares-discriminant analysis), and SVM-C (support vector machine-classification), were used to determine the geographical origin of the Giresun Tombul hazelnut cultivar. For this purpose, samples from unique 118 orchards were collected from eight different regions in Turkey during the 2021 and 2022 growing seasons. NIR and Raman spectra were obtained from both the shell and kernel of each sample. The results indicated that hazelnut samples exhibited distinct grouping tendencies based on growing season regardless of the spectroscopic technique and sample type (shell or kernel). Spectral information obtained from hazelnut shells demonstrated higher discriminative power concerning geographical origin compared to that obtained from hazelnut kernels. The PLS-DA models utilizing FT-NIR (Fourier transform near-infrared) and Raman spectra for hazelnut shells achieved validation accuracies of 81.7% and 88.3%, respectively, while SVM-C models yielded accuracies of 90.9% and 86.3%. It was concluded that the lignocellulosic composition of hazelnut shells, indicative of their geographic origin, can be accurately assessed using FT-NIR and Raman spectroscopy, providing a nondestructive, rapid, and user-friendly method for identifying the geographical origin of Giresun Tombul hazelnuts. PRACTICAL APPLICATION: The proposed spectroscopic methods offer a rapid and nondestructive means for hazelnut value chain actors to verify the geographic origin of Giresun Tombul hazelnuts. This could definitely enhance consumer trust by ensuring product authenticity and potentially help in preventing fraud within the hazelnut market. In addition, these methods can also be used as a reference for future studies targeting the authentication of other shelled nuts.
土耳其是榛子的主要生产国，其榛子产量占全球总产量的 62%。在 18 个不同的当地榛子品种中，吉雷松·图布尔是唯一获得欧盟委员会（EC）原产地保护名称的品种。然而，目前还没有实际可行的客观方法来确保其地理来源。因此，在这项研究中，我们使用近红外（NIR）和拉曼光谱以及化学计量学方法，如主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）和支持向量机分类（SVM-C），来确定吉雷松·图布尔榛子品种的地理来源。为此，在 2021 年和 2022 年生长季节，我们从土耳其八个不同地区的 118 个独特果园中采集了样本。我们从每个样本的壳和仁中获取了 NIR 和拉曼光谱。结果表明，无论使用哪种光谱技术和样本类型（壳或仁），榛子样本都表现出明显的基于生长季节的分组趋势。与榛子仁相比，榛子壳获得的光谱信息对地理起源具有更高的区分能力。使用傅里叶变换近红外（FT-NIR）和拉曼光谱对榛子壳进行 PLS-DA 模型的验证准确率分别为 81.7%和 88.3%，而 SVM-C 模型的准确率分别为 90.9%和 86.3%。结论是，榛子壳的木质纤维素组成可以准确地反映其地理起源，使用 FT-NIR 和拉曼光谱可以对其进行评估，为鉴定吉雷松·图布尔榛子的地理起源提供了一种无损、快速和用户友好的方法。实际应用：所提出的光谱方法为榛子价值链中的参与者提供了一种快速、无损的方法来验证吉雷松·图布尔榛子的地理起源。这肯定会通过确保产品的真实性来增强消费者的信任，并有可能帮助防止榛子市场中的欺诈行为。此外，这些方法还可以作为未来针对其他带壳坚果进行认证的研究的参考。
