Due to an increase in interest towards functional and health-related foods, Panax ginseng sprout has been in the spotlight since it contains a significant amount of saponins which have anti-cancer, -stress, and -diabetic effects. To increase the amount of production as well as decrease the cultivation period, sprouted ginseng is being studied to ascertain its optimal cultivation environment in hydroponics. Although there are studies on functional components, there is a lack of research on early disease prediction along with productivity improvement. In this study, the ginseng sprouts were cultivated in four different hydroponic conditions: control treatment, hydrogen-mineral treatment, Bioblock treatment, and highly concentrated nitrogen treatment. Physical properties were measured, and environmental data were acquired using sensors. Using three algorithms (artificial neural networks, support vector machines, random forest) for germination and rottenness classification, and leaf number and length of stem prediction models, we propose a hierarchical machine learning model that predicts the growth outcome of ginseng sprouts after a week. Based on the results, a regression model predicts the number of leaves and stem length during the growth process. The results of the classifier models showed an F1-score of germination classification of about 99% every week. The rottenness classification model showed an increase from an average of 83.5% to 98.9%. Predicted leaf numbers for week 1 showed an average nRMSE value of 0.27, which decreased by about 33% by week 3. The results for predicting stem length showed a higher performance compared to the regression model for predicting leaf number. These results showed that the proposed hierarchical machine learning algorithm can predict germination and rottenness in ginseng sprout using physical properties.

The food industry has tried to enhance production processes in response to the increasing demand for safe, high-quality Home Meal Replacement (HMR) products. While robotic automation systems are recognized for their potential to improve efficiency, their high costs and risks make them less accessible to small and medium-sized enterprises (SMEs). This study presents a simulation-based approach to evaluating the feasibility and impact of robotic automation on HMR production, focusing on two distinct production cases. By modeling large-scale and order-based production cases using simulation software, the study identified key bottlenecks, worker utilization, and throughput improvements. It demonstrated that robotic automation increased throughput by 31.2% in large-scale production (Case A) and 12.0% in order-based production (Case B). The actual implementation showed results that closely matched the simulation, validating the approach. Moreover, the study confirmed that a single worker could operate the robotic system effectively, highlighting the practicality of robotics for SMEs. This research provides critical insights into integrating robotics to enhance productivity, reduce labor dependency, and facilitate digital transformation in food manufacturing.

Panax ginseng sprouts have important medicinal properties and thus the optimization of growth conditions is an important research goal. The effects of LED treatment and plasma-activated water on the growth and quality of Panax ginseng sprouts (PGS) in hydroponic cultivation were evaluated. Using 1-year-old ginseng plants, light was applied 9-18 h for the CGS, TGS1, TGS2, and TGS3 groups and 24 h for TGS4. Plasma-activated water was used in all groups except CGS and TGS1, and fermentation nutrient solutions (NO) were added to TGS1, TGS3, and TGS4. The TGS4 group had a high total length and initial length on days 7 and 14. At 21 days, the growth of TGS1, TGS3, and TGS4 with NO nutrient solutions increased. The total decay rate (%) was low (4.24-4.65%) for TGS1, TGS2, and TGS3. Although the chlorophyll a, b, and total chlorophyll contents were significantly higher in TGS4 than in other groups (p<0.05), TGS3 tended to show higher carotenoid levels. Therefore, for the hydroponic cultivation of PGS, nutrient solutions and plasma-activated water influence growth, and the LED treatment duration influences growth and functional substances. During hydroponic cultivation, TGS4 conditions resulted in high growth, saponin contents, and radical scavenging activity, with excellent functionality. However, considering the high rate of root decay, further studies of the effects of different wavelengths and treatment durations (light and dark cycles) on growth are needed.

This study intended to analyze growth changes and antioxidant activities of Romaine lettuce by different treatments of microbubble plasma discharge water and bioblock (far-infrared radiation). Hydroponics were performed in smart farm environments, and the used Romaine lettuce was the Caesar's Green variety. The treatment conditions of Romaine lettuce (TRL) are as follows: TRL-1 was treated with plasma discharge water and 30 bioblocks, and TRL-2 was treated with plasma discharge water and 40 bioblocks. On the other hand, TRL-3 was not treated. Romaine lettuce was grown for a total of 49 days and the growth changes were measured at every seven days. In growth changes, TRL-2 was significantly higher (p<0.05) than other treatments in germination rate and weight, leaf length, and leaf count. The total polyphenol and flavonoid contents were analyzed as similar levels between the samples, but TRL-2 showed higher antioxidant activities in ABTS radical scavenging (%) compared to the other samples. As a result of this study, TRL-2 conditions are evaluated to affect the growth and antioxidant functions of Romaine lettuce.

For the distribution of fresh produce, the thermoelectric cooling system combined with thermo electric materials (TEM) and phase change material (PCM) was studied. The PCM used this study was produced by in-situ polymerization technology which referred microencapsulation of hydrocarbon (n-tetradecane and n-hexadecane). In this study, quality characteristics of bell peppers in thermoelectric cooling system combined with TEM and PCM were analyzed and control was placed in an EPS (expanded polystyrene) box. As a result of quality characteristics analysis, weight of bell peppers decreased and moisture content of bell peppers was 90.96~94.43% during storage. Vitamin C content of bell pepper decreased during storage and reduction ratio of control was higher than that of BPT-5 treatment(bell pepper in thermoelectric cooling system with PCM which is kept the temperature at 5℃). The result of color value, on 21 day, ΔE value of BPT-5 treatment was 5.05 while that of control was 41.8. On 21 day, total bacteria count of BPT-5 treated bell pepper shown less than that of control. In conclusion, it suggested that the thermoelectric cooling system combined with PCM improved quality of fresh produce during transportation and storage.