Abstract
The increased demand for hops with distinctive aromas by the craft brewing industry has elevated the risk of fraudulent activities linked to their origin. Given the significant rise in food fraud and consumers’ growing attention to origin transparency, there is a need for rapid authentication methods to verify origin. This study employed near-infrared (NIR) spectroscopy combined with multivariate data analysis for the geographical origin traceability of New Zealand hops at the regional and farm levels. Three hop cultivars were collected from eight farms in the Tasman region of New Zealand. Additionally, six cultivar pairs were compared between the Tasman and Central Otago regions. The raw NIR spectra were preprocessed, and partial least squares discriminant analysis (PLS-DA) was employed for classification. The Suderdelic™ cultivar displayed the highest separation between the farms, with each sample forming distinct groups without any overlap. The Nectaron® cultivar displayed three primary clusters, while the Nelson Sauvin™ cultivar illustrated the least variation between farm origins. The regional samples PLS-DA classification model revealed genetics as the dominant factor, where the samples from the same cultivar were positioned close to each other. Interestingly, an apparent location effect emerged in the third dimension of the PLS-DA model. This study demonstrated the potential of NIR spectroscopy combined with multivariate data analysis to rapidly classify hop samples by their geographical origin at different scales (farms and regions), thereby aiding in the prevention and detection of food fraud related to origin.