RESUMEN
Background: This study explored the utilization of luffa sponge (LS) in enhancing acetification processes. LS is known for having high porosity and specific surface area, and can provide a novel means of supporting the growth of acetic acid bacteria (AAB) to improve biomass yield and acetification rate, and thereby promote more efficient and sustainable vinegar production. Moreover, the promising potential of LS and luffa sponge coated with κ-carrageenan (LSK) means they may represent effective alternatives for the co-production of industrially valuable bioproducts, for example bacterial cellulose (BC) and acetic acid. Methods: LS and LSK were employed as adsorbents for Acetobacter pasteurianus UMCC 2951 in a submerged semi-continuous acetification process. Experiments were conducted under reciprocal shaking at 1 Hz and a temperature of 32 °C. The performance of the two systems (LS-AAB and LSK-AAB respectively) was evaluated based on cell dry weight (CDW), acetification rate, and BC biofilm formation. Results: The use of LS significantly increased the biomass yield during acetification, achieving a CDW of 3.34 mg/L versus the 0.91 mg/L obtained with planktonic cells. Coating LS with κ-carrageenan further enhanced yield, with a CDW of 4.45 mg/L. Acetification rates were also higher in the LSK-AAB system, reaching 3.33 ± 0.05 g/L d as opposed to 2.45 ± 0.05 g/L d for LS-AAB and 1.13 ± 0.05 g/L d for planktonic cells. Additionally, BC biofilm formation during the second operational cycle was more pronounced in the LSK-AAB system (37.0 ± 3.0 mg/L, as opposed to 25.0 ± 2.0 mg/L in LS-AAB). Conclusions: This study demonstrates that LS significantly improves the efficiency of the acetification process, particularly when enhanced with κ-carrageenan. The increased biomass yield, accelerated acetification, and enhanced BC biofilm formation highlight the potential of the LS-AAB system, and especially the LSK-AAB variant, in sustainable and effective vinegar production. These systems offer a promising approach for small-scale, semi-continuous acetification processes that aligns with eco-friendly practices and caters to specialized market needs. Finally, this innovative method facilitates the dual production of acetic acid and bacterial cellulose, with potential applications in biotechnological fields.
Asunto(s)
Ácido Acético , Acetobacter , Biomasa , Carragenina , Carragenina/química , Acetobacter/metabolismo , Ácido Acético/química , Ácido Acético/metabolismo , Luffa/química , Adsorción , Celulosa/metabolismo , Celulosa/química , Biopelículas/crecimiento & desarrolloRESUMEN
Freshness is an important parameter that is indexed in the quality assessment of commercial cassava tubers. Cassava tubers that are not fresh have reduced starch content. Therefore, in this study, we aimed to develop a new approach to detect cassava root deterioration levels using thermal imaging with machine learning (ML). An underlying assumption was that nonfresh cassava roots may have fermentation inside that causes a difference in the inner temperature of the tuber. This creates the opportunity for the deterioration level to be measured using thermal imaging. The features (pixel intensity and temperature) that were extracted from the region of interest (ROI) in the form of tuber thermal images were analyzed with ML. Linear discriminant analysis (LDA), k-nearest neighbor (kNN), support vector machine (SVM), decision tree, and ensemble classifiers were applied to establish the optimal classification modeling algorithms. The highest accuracy model was developed from thermal images of cassava roots captured in a darkroom under a control temperature of 25 °C in the measurement chamber. The LDA, SVM, and ensemble classifiers gave the best overall performance for the discrimination of cassava root deterioration levels, with an accuracy of 86.7%. Interestingly, under uncontrolled environmental conditions, the combination of thermal imaging plus ML gave results that were of lower accuracy but still acceptable. Thus, our work revealed that thermal imaging coupled with ML was a promising method for the nondestructive evaluation of cassava root deterioration levels.
RESUMEN
The impact of different parboiled rice process conditions on physical (whiteness and yellowness), chemical (amylose and fat contents), and texture (hardness and toughness) properties was studied. The parboiled rice was produced from the Suphanburi 1 variety. The correlation between chemical and texture properties was also analyzed. To study the effect of the soaking process, the time (2, 3, and 6 hr) and temperature (65 and 75°C) of soaking were altered, while the steaming condition was fixed at 100°C for 20 min. To study the effect of the steaming process, the soaking condition was fixed at 65°C for 6 hr while steaming condition was altered, including time (10 and 20 min) and temperature (90 and 100°C). The results show that the different conditions influenced the physical and chemical properties of parboiled rice. The amylose content was negatively correlated (Hardness, r = -0.52) (Toughness, r = -0.38) and fat content was positive low correlated (Hardness, r = 0.20) (Toughness, r = 0.12) with textural properties. Due to the specification of parboiled rice for exportation varying according to customer requirements, the results of this research provided some useful information for parboiled rice factories.