Savela-Huovinen Ulriikka, Toom Auli, Knaapila Antti, Muukkonen Hanni
Department of Economics and Management Faculty of Agriculture and Forestry University of Helsinki Helsinki Finland.
Centre for University Teaching and Learning Faculty of Educational Sciences University of Helsinki Helsinki Finland.
Food Sci Nutr. 2021 Jun 13;9(8):4254-4265. doi: 10.1002/fsn3.2393. eCollection 2021 Aug.
The increase in digitalization, software applications, and computing power has widened the variety of tools with which to collect and analyze sensory data. As these changes continue to take place, examining new skills required among sensory professionals is needed. The aim with this study was to answer the following questions: (a) How did sensory professionals perceive the opportunities to utilize facial expression analysis in sensory evaluation work? (b) What skills did the sensory professionals describe they needed when utilizing facial expression analysis? Twenty-two sensory professionals from various food companies and universities were interviewed by using semistructural thematic interviews to map development intentions from facial expression recognition data as well as to describe the established skills that were needed. Participants' facial expressions were first elicited by an odor sample during a sensory evaluation task. The evaluation was video recorded to characterize a facial expression software response (FaceReader™). The participants were interviewed regarding their opinions of the data analysis the software produced. The study findings demonstrate how using facial expression analysis contains personal and field-specific perspectives. Recognizability, associativity, reflectivity, reliability, and suitability were perceived as a personal perspective. From the field-specific perspective, professionals considered the received data valuable only if they had skills to interpret and utilize it. There is a need for an increase in training not only in IT, mathematics, statistics, and problem-solving, but also in skills related to self-management and ethical responsibility.
数字化、软件应用和计算能力的提升拓宽了用于收集和分析感官数据的工具种类。随着这些变化不断发生,有必要审视感官专业人员所需的新技能。本研究的目的是回答以下问题:(a)感官专业人员如何看待在感官评价工作中利用面部表情分析的机会?(b)感官专业人员在利用面部表情分析时描述了他们需要哪些技能?通过半结构化主题访谈,对来自不同食品公司和大学的22名感官专业人员进行了访谈,以梳理面部表情识别数据的发展意向,并描述所需的既定技能。在感官评价任务中,首先通过气味样本引发参与者的面部表情。对评价过程进行录像,以表征面部表情软件的响应(FaceReader™)。就他们对软件生成的数据分析的看法对参与者进行了访谈。研究结果表明,使用面部表情分析包含个人和特定领域的观点。可识别性、关联性、反思性、可靠性和适用性被视为个人观点。从特定领域的角度来看,专业人员只有具备解释和利用所接收数据的技能,才会认为这些数据有价值。不仅需要增加在信息技术、数学、统计学和解决问题方面的培训,还需要增加与自我管理和道德责任相关的技能培训。