Volume 18, Issue 1

Food safety plays an essential role in our daily lives, and it becomes serious with the development of worldwide trade. To tackle the food safety issues, many advanced technologies have been developed to monitor the process of the food industry (FI) to ensure food safety, including the process of food production, processing, transporting, storage, and retailing. These technologies are often referred to as artificial intelligence (AI), big data, and blockchain, which have been widely applied in many research areas. In this review, we introduce these technologies and their applications in the food safety domain. Firstly, basic concepts of these technologies are presented. Then, applications for food safety from a data perspective based on these technologies are analyzed. Finally, future challenges of the applications of AI, big data, and blockchain are discussed.

This paper presents a method for extracting rice bran oil using magnetic immobilized cellulase (MIC) in a magnetic fluidized bed (MFB). Cellulase was immobilized on Fe 3 O 4 /SiO x -g-P (glycydylmethacrylate) with an average grain size of 120 nm. The rice bran was hydrolyzed using MIC combined with magnetic immobilized alkaline protease to extract rice bran oil. Under intermittent conditions, the MIC concentration was 1.6 mg/g, the liquid to material ratio was 4:1, the enzymatic hydrolysis time was 150 min, and the oil yield was as high as 85.6 ± 1.20% at 55 °C. The fluid in the MFB had a magnetic field strength of 0.022 T, a flow velocity of 0.005 m/s, and an oil extraction rate of 90.3%. This provides a theoretical basis for the extraction of rice bran oil using the subsequent MFB hydroenzyme method.

Shallot harvesting and processing produce various waste streams, and the current study aims to investigate the effects of shallot bio-waste powder (SWP) substitution on different flour properties. Increased SWP to 50% substitution of stalk and petiole showed a rise in swelling capacity (43.33%) and water absorption (342.22%), and oil absorption (320.73%), respectively. Foaming capacity improved from 48.00% in control to 60.26% in 30% flower substitution and further decreases to 51.28% at 50%. Pasting properties reduced at higher SWP substitution and the highest drop in peak viscosity was observed at Stalk-50 (457.33 cP). Subsequently, developed functional cookies showed enhanced fiber, ash, total phenol, and total flavonoids with 3, 2, 7, and 5 fold, respectively. Cookies developed with higher substitution were of darker color and higher hardness and fracturability. Sensory evaluation with fuzzy analysis revealed better acceptance for stalk and petiole (10%) and peel (5%) of final cookies with elevated nutritional value.

In this study, the effect of bacterial cellulose nanofibers (BCNF) incorporation on the structural and rheological properties of casein gels was investigated, where the mixed BCNF and casein gels were prepared by adding gluconic acid δ-lactone (GDL) to acidify the mixed polymer solutions at 3.0% casein concentration ( w / v ) and varying BCNF concentrations (0–0.5%, w / v ). By changing the addition amount of GDL, the mechanical and structural properties of the mixed gels were studied at above, near and below the electric point (pI) of the casein. At pH above the pI of the casein, the introduction of BCNF initially increased the gel strength, but further addition of BCNF weakened the mixed gels. At near and below the pI of the casein, the incorporation of BCNF continuously increased the gel strength. Besides, all gels showed good structural homogeneity, without macroscopic phase separation occurring, which indicated good compatibility of BCNF with the casein gels.

Chavil ( Ferulago angulata ) extract (CE) and microencapsulated chavil extract (MCE) were added to UF- Feta-type Cheese. The aim of this study was to comprising CE and MCE on physicochemical and microbiological properties in cheese. The scanning electron microscope images demonstrate the MCE had elliptical shape. The average size diameter curve of the MCE revealed bimodal distribution with two peaks (1541 and 2222 nm) separately. The hardness value of MCE cheese (212.83 ± 17.63 g) was lower than that of CE (343.67 ± 25.53 g) because of canola oil used in the microencapsulation process. The MCE-cheese showed lower values of acidity (1.67%) in comparison with CE-cheese (1.87%). The viable numbers of Streptococcus thermophilus and Lactococcus lactis were equal among the samples (4.6–4.9 log 10  CFU/g respectively). The acid degree value of MCE (2.07 ± 0.21%) and CE (1.83 ± 0.25%) cheese were nearly equal at the end of storage time.

An inclined flow channel instrument that can be developed to be a structurally simple and easy-to-use rheometer was applied to control the thickness, specifically the viscosity and elasticity, of liquids thickened to support swallowing in nursing-care practice. Aqueous solutions containing salt or acid, which might be used as ingredients in drinks, were thickened with a commercial thickener. The thickener efficacy decreased because of the salt or acid in liquid phase. Analysis of the flows in the instrument by experimentation yielded a dimensionless relation representing changes of the Deborah number in the flow process, as indicated by the relative flow length, considering the shear rate in oral processing. One unique methodology to evaluate the viscoelasticities of thickened liquids during the swallowing process was presented utilizing the measurements such as elapsed time and velocity in the instrument.

Four types of cereals (glutinous rice, purple rice, red rice, yellow millet) were selected to produce sweet fermented grains. Flavor profiles of sweet fermented grains are comparatively studied to distinguish various flavor types by using GC-MS, electronic nose (E-nose), and sensory analysis, and the amino acid composition and physicochemical properties of sweet fermented grains were analyzed. The results showed that the volatile compounds of sweet fermented grains were significantly different. Esters and alcohols were the major volatile compounds in sweet fermented grains. The electronic nose, electronic tongue and sensory analysis jointly verified that the volatile components of sweet fermented grains had differences between them. The sweet fermented grains could be classified based on differences in volatile compounds. In the amino acids analysis, Glu, Pro, Asp and Leu were the most abundant. The difference in physicochemical properties is more helpful to distinguish different types of sweet fermented grains. Correlation analysis between antioxidant active substances and color value showed a positive correlation between with a * value, and a negative correlation with L *, b * value. Our results suggested that there were differences in the flavor characteristics of sweet fermented grains fermented from different types of cereals. The results of the study will provide valuable information for the selection of raw materials for sweet fermented grains.