• Food Science of Animal Resources
• /
• v.44 no.3
• /
• pp.635-650
• /
• 2024

In this study, we analyzed the physicochemical and sensory properties of black goat jerky marinated with various spices (non-spice, control; rosemary, RO; basil, BA; ginger, GI; turmeric, TU; and garlic, GA). The physicochemical properties of black goat jerky analyzed were pH, water holding capacity, color, cooking yield, shear force, and fatty acid composition. The sensory characteristics were analyzed through the aroma profile (electronic nose), taste profile (electronic tongue), and sensory evaluation. The pH and water holding capacity of the GI showed higher values than the other samples. GI and GA showed similar values of CIE L^* and CIE a^* to that of the control. The shear force of the GI and TU was significantly lower than that of other samples (p<0.05). Regarding fatty acid composition, GI showed high unsaturated and low saturated fatty acid contents compared with that of the other samples except for RO (p<0.05). In the aroma profile, the peak area of hexanal, which is responsible for a faintly rancid odor, was lower in all treatment groups than in the control. In the taste profile, the umami of spice samples was higher than that of the control, and among the samples, GI had the highest score. In the sensory evaluation, the GI sample showed significantly higher scores than the control in terms of flavor, aroma, goaty flavor, and overall acceptability (p<0.05). Therefore, marinating black goat jerky with ginger powder enhanced the overall flavor and reduced the goat odor.

• Korean Journal of Food Science and Technology
• /
• v.53 no.4
• /
• pp.375-381
• /
• 2021

This study investigated the physicochemical properties and chemosensory characteristics of radish samples. Brix results in Matdong-radish showed the highest value (1.5±0.1%), and Mansahyungtong-radish showed the lowest. In terms of salinity, Mansahyungtong-radish had the highest value (1.2±0.1%), and there were no significant differences among samples except Mansahyungtong-radish. In pH analysis, Cheongjunggowon-radish had the highest value at 6.69±0.02. The pH in Mansahyungtong-radish showed the lowest value at 6.10±0.01. In the electronic tongue, sourness was high in the Seoho-radish (8.2), and saltiness was high in the Matdong-radish (8.1). Umami was high in the Seoho-radish (8.3), and sweetness was high in the Matdong-radish (8.1). In the electronic nose, sulfur-containing compounds were high in all the samples. Methanethiol, which represented the odor description of cabbage, garlic, and sulfurous, was abundant in sulfur-containing compounds. Multivariate analysis using physicochemical and chemosensory properties can be used as a database for the food industry.

• Food Science of Animal Resources
• /
• v.41 no.4
• /
• pp.563-588
• /
• 2021

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.