I-Corps: Determination of syrup adulterants and geographical and floral origin of honey using chemometrics

这个I-Corps项目更广泛的影响/商业潜力是在蜂蜜掺假检测领域。蜂蜜掺假是故意在蜂蜜中添加掺杂物，如玉米，甘蔗，甜菜和大米糖浆的过程，可能会产生重大的经济和感官后果。该技术将允许蜂蜜进口商，包装商和零售商以及食品认证机构通过以简单方便的方式量化上述掺假糖浆，在供应链的每个步骤快速跟踪其蜂蜜产品的真实性。这将大大提高产品的真实性和可追溯性。此外，现场测试蜂蜜掺假物的存在以及花卉和地理指纹将允许各种蜂蜜细分市场在全球市场上为其纯蜂蜜产品要求适当的价格。随着食品欺诈在全球范围内持续升级，到2023年，食品真实性市场预计将增长至83亿美元。掺假蜂蜜占食品欺诈案件的7%，到2023年将造成5.81亿美元的市场规模破坏。这个I-Corps项目基于便携式中红外光谱仪和智能手机应用系统的开发，可以同时量化各种糖浆的存在（即，玉米、甘蔗、甜菜和大米）以及糖含量（即，葡萄糖，果糖和蔗糖）在蜂蜜中不到2分钟。目前用于检测蜂蜜中这些掺假物的方法被认为是昂贵、耗时、过时和繁琐的。这些测试大多是通过第三方实验室使用昂贵和复杂的分析设备进行的。智能手机应用系统将包含研究小组专有开发的多变量校准系统，该系统可以使用中红外光谱设备以简单，方便和经济的方式同时量化蜂蜜中上述掺假物的存在。此外，多元校准算法系统还将具有与确定蜂蜜的植物和地理来源相关的方面。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is in the area of honey adulteration detection. Honey adulteration which is the process of deliberately adding adulterants such as corn, cane, beet, and rice syrups in honey can have significant economic and organoleptic consequences. The proposed technology will allow honey importers, packers, and retailers, as well as food authentication agencies to quickly track the authenticity of their honey products at each step of the supply chain by quantifying the abovementioned adulterant syrups in a facile and convenient manner. This will significantly improve the product’s authenticity and traceability. Further, in situ testing for the presence of honey adulterants as well as floral and geographic fingerprinting will allow various honey market segments to demand the appropriate price for their pure honey products in the global market. With food fraud continuing to escalate globally, the food authenticity market is expected to grow to $8.3 billion (USD) by 2023. Adulterated honey constitutes 7% of food fraud cases, amounting to $581 million (USD) by 2023 in total market size disruption.This I-Corps project is based on the development of a portable mid-infrared spectrometric device and a smartphone application system that can simultaneously quantify the presence of various syrups (i.e., corn, cane, beet, and rice) as well as sugar content (i.e., glucose, fructose, and sucrose) in honey in less than 2 minutes. Current methods for detecting these adulterants in honey are considered expensive, time consuming, archaic, and cumbersome. Most of these tests are being conducted via third-party laboratories using expensive and complex analytical equipment. The smartphone application system will contain the research group’s proprietary developed multivariate calibration system that can simultaneously quantify the presence of the aforementioned adulterants in honey in a facile, convenient, and affordable manner using the mid-infrared spectrometric device. Further, the multivariate calibration algorithmic system will also feature aspects related to determining the floral and geographical origin of honey.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.