In the contemporary era of global and sustainable information management, blockchain has made a cutting-edge transformation in online learning. To apprehend this new trajectory, this current systematic review with bibliographic visualization aims to identify the thematic clusters of underlying aspects concerning the sustainable nexus of blockchain and online learning. Using the updated guidelines of the PRISMA flowchart, a total of 434 scholarly research papers from the mainstream research databases, i.e., Web of Science, Scopus, IEEE Xplore, and ScienceDirect, were inspected to be categorized into 15 relevant publications. Bibliographic data were assembled and analyzed accordingly to construct network visualization maps, such as co-authorship, citation, co-citation, bibliographic coupling, and term co-occurrence using VOSviewer 1.6.18. Significant terms were reported and later cross-mapped with those identified by critically reviewing the applicable 15 papers. Standardized scholarship, behavior pattern, and digital badging have been found and derived as themes from the connected clusters. Therefore, current research findings reveal these three broad clutches of themes concerning the sustainable nexus of blockchain and online learning.

• The abundance of most volatile compounds in lamb shashliks varied significantly between roasting methods. • Buttery odor may result from a combination of processing methods with multiple volatile compounds. • K and L methods may replace traditional charcoal grilling as a new roasting method. • Predicting the concentrations and roasting methods by five machine learning methods. • The CNN-SVM models achieved a better predictive performance than other models.

Generation Z (Gen Z) consumers account for an increasing proportion of the food market. The aim of this study took lamb shashliks as an example and developed novel products from the perspective of cooking methods in order to develop a traditional food suitable for Gen Z consumers. The sensory characterization of electric heating air (EH), microwave heating (MH), air frying (AF), and control (traditional burning charcoal (BC) of lamb shashliks) was performed using the CATA methodology with 120 Gen Z consumers as assessors. A 9-point hedonic scale was used to evaluate Gen Z consumers’ preferences for the cooking method, as well as a CATA ballot with 46 attributes which described the sensory characteristics of lamb shashliks. The machine learning algorithms were used to identify consumer preferences for different cooking methods of lamb shashliks as a function of sensory attributes and assessed the relationship between products and attributes present in the perceptual map for the degree of association. Meanwhile, sensory attributes as important variables play a relatively more important role in each cooking method. The most important variables for sensory attributes of lamb shashliks using BC are char-grilled aroma and smoky flavor. Similarly, the most important variables for AF samples are butter aroma, intensity aroma, and intensity aftertaste, the most important variables for EH samples are dry texture and hard texture, and the most important variables for MH samples are light color regarding external appearance and lumpy on chewing texture. The interviews were conducted with Gen Z consumers to investigate why they prefer innovative products—AF. Grounded theory and the social network analysis (SNA) method were utilized to explore why consumers chose AF, demonstrating that Gen Z consumers who had previously tasted AF lamb shashliks could easily perceive the buttery aroma. This study provides a theoretical and practical basis for developing lamb shashliks tailored to Gen Z consumers.