Effects of Morphology on the Bulk Density of Instant Whole Milk Powder

Co-fermentation improves the functional properties and nutritional quality of infant complementary food products

Food-to-food fortification and fermentation are effective strategies to enhance the product functionality and nutrient density of infant complementary foods. However, their effectiveness hinges on a deep understanding of ingredient combinations. Our research focused on the physicochemical and techno-functional aspects of sorghum-baobab blends, comparing two processes: 'co-ferment-cook' and 'ferment-cook-fortify'. The results show that both techniques improved the water absorption capacity by 17-20% and the water solubility index increased by over 100% while maintaining a comparable nutritional composition and energy density. The calculated energy density (2048.8-2345 kJ day-1) was sufficient for both blends for infants 6-11 months old with an average breast milk intake. Viscosity, another crucial factor for complementary feeding, improved significantly (P < 0.05) after co-ferment-cook compared to ferment-cook-fortify reaching a value suitable for children older than 18 months. Starch digestibility increased with co-ferment-cook, while protein digestion increased with fortified non-fermented foods. In conclusion, our findings emphasize that combining fermentation and fortification processing steps is optimal for balancing the nutritional and techno-functional properties of sorghum porridges for infant complementary foods. Processing parameters must be optimized to reach the viscosity suitable for complementary feeding at the assigned soluble solid contents for the age group 6-24 months.

Integrating Image Analysis and Machine Learning for Moisture Prediction and Appearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment

The appearance of dried fruit clearly influences the consumer's perception of the quality of the product but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online. This paper describes a method that combines several simple strategies to assess a suitable surrogate for the elusive quality using imaging, combined with multivariate statistics and machine learning. With such a convenient tool, this study also shows how one can vary the pretreatments and drying conditions to optimize the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (area, perimeter, and compactness) features. The accuracy of this method was verified using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture ratio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing device. This study also explored determining the optimal drying strategy based on appearance quality using principal component analysis. Optimal drying was achieved at 60 °C with 4 mm thick slices under ultrasonic pretreatment. For the 70 °C, 6 mm sample groups, citric acid showed decent performance.

A novel approach to increase calcium and fiber content in pasta using kadamb fruit (Neolamarckia cadamba) powder and study of functional and structural characteristics

Kadamb is a unique and underutilized fruit having rich nutritional profile. The utilization of kadamb fruit in value addition is very limited. In this study, pasta was made using kadamb fruit powder (KFP). The effect of fortification of KFP on the quality parameters (color, solid loss, percent expansion, hardness, bulk density, and overall acceptability) of pasta was studied. Pasta was prepared using semolina as the base ingredient, and various proportions of KFP (ranging from 0 to 20%) were added for fortification. Dietary fiber and calcium contents of dry pasta were increased from 5.21 ± 0.02 to 15.36 ± 0.02 and 17.57 ± 0.15 to 37.97 ± 0.03, respectively. As the proportion of KFP increased, the cooking time, hardness, and percent solid loss of the cooked pasta also increased. The highest values for overall acceptability, hardness, cooking solid loss, and bulk density were achieved with 10% KFP and 90% semolina were 7.93 ± 0.41, 19.92 ± 0.21 N, 6.30 ± 0.46%, and 331.67 ± 9.60 kg/m3 respectively. Percent expansion of the pasta was noted to be around 98.33 ± 6.5%. The optimal proportion of KFP was found to be 10% for achieving the best overall quality attributes. FTIR (Fourier-transform infrared spectroscopy) and SEM (scanning electron microscopy) analyses were conducted on the pasta, confirming the presence of functional groups and revealing structural changes due to fiber content of KFP. KFP can be used to create functional and nutritious food products, and further research could explore its application in other food formulations as well.

The Application of Artificial Intelligence and Big Data in the Food Industry

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

Application of Three-Dimensional Digital Photogrammetry to Quantify the Surface Roughness of Milk Powder

The surface appearance of milk powders is a crucial quality property since the roughness of the milk powder determines its functional properties, and especially the purchaser perception of the milk powder. Unfortunately, powder produced from similar spray dryers, or even the same dryer but in different seasons, produces powder with a wide variety of surface roughness. To date, professional panelists are used to quantify this subtle visual metric, which is time-consuming and subjective. Consequently, developing a fast, robust, and repeatable surface appearance classification method is essential. This study proposes a three-dimensional digital photogrammetry technique for quantifying the surface roughness of milk powders. A contour slice analysis and frequency analysis of the deviations were performed on the three-dimensional models to classify the surface roughness of milk powder samples. The result shows that the contours for smooth-surface samples are more circular than those for rough-surface samples, and the smooth-surface samples had a low standard deviation; thus, milk powder samples with the smoother surface have lower Q (the energy of the signal) values. Lastly, the performance of the nonlinear support vector machine (SVM) model demonstrated that the technique proposed in this study is a practicable alternative technique for classifying the surface roughness of milk powders.

Optimization of alcohol extraction and spray-drying conditions for efficient processing and quality evaluation of instant tea powder from lotus and green tea leaves

Lotus and Green Tea leaves are two frequently used medicinal plants in Vietnam, utilized as food, drink, or in traditional treatments to help with weight loss and cholesterol reduction. The study’s major goal is to determine the parameters of the process preparation in order to generate instant tea powder that satisfies quality criteria for customer demand. Twenty experiments are conducted using the D-optimal model to evaluate the cause-effect relationship and optimize the production process of instant tea powder. Four independent variables are selected for the survey namely alcohol concentration (40%; 50%; 60%), carrier mass (10 g; 20 g; 30 g), inlet air temperature (160 °C; 170 °C) and flow rate (4 rpm/min; 5 rpm/min). The instant tea powder is effectively created and met quality parameters, with a drying performance, moisture content, total phenol and flavonoid content of 29.15%, 4.83%, 45.29 mg GA/g, and 70.68 mg QE/g, respectively. In conclusion, the optimal parameters of the preparation process were identified, which included an alcohol content of 60%, a carrier mass of 10 g, an inlet air temperature of 165 °C, and a flow rate of 4 rpm/min.

Assessing and Quantifying the Surface Texture of Milk Powder Using Image Processing

Milk powders produced from similar spray dryers have different visual appearances, while the surface appearance of the powder is a key quality attribute because the smoothness of the milk powder also affects flowability and handling properties. Traditionally quantifying this nuanced visual metric was undertaken using sensory panelists, which is both subjective and time consuming. Therefore, it is advantageous to develop an on-line quick and robust appearance assessment tool. The aim of this work is to develop a classification model which can classify the milk powder samples into different surface smoothness groups. This work proposes a strategy for quantifying the relative roughness of commercial milk powder from 3D images. Photogrammetry equipment together with the software RealityCapture were used to build 3D models of milk powder samples, and a surface normal analysis which compares the area of the triangle formed by the 3 adjacent surface normals or compares the angle between the adjacent surface normals was used to quantify the surface smoothness of the milk powder samples. It was found that the area of the triangle of the smooth-surface milk powder cone is smaller than the area of the triangle of the rough-surface milk powder cone, and the angle between the adjacent surface normals of the rough-surface milk powder cone is larger than the angle between the adjacent surface normals of the smooth-surface milk powder cone, which proved that the proposed area metrics and angle metrics can be used as tools to quantify the smoothness of milk powder samples. Finally, the result of the support vector machine (SVM) classifier proved that image processing can be used as a preliminary tool for classifying milk powder into different surface texture groups.

Formulation and Evaluation of Sustained Release Matrix Tablets of Aceclofenac

This study aimed to improve the dissolution rate of aceclofenac and release the drug in a controlled manner over a period of 24 hours. Matrix tablets were prepared by direct compression method, using hydrophilic polymers (HPMC/guar gum). Matrix tablets were prepared by wet granulation method using different hydrophilic polymers (HPMC/guar gum). Tablets were evaluated for in vitro drug release profile in phosphate buffer with pH 6.8 (without enzymes). The thickness and hardness of prepared tablets were 3.23 ± 0.035 to 3.28 ± 0.008 mm and 3.26 ± 0.115 to 3.60 ± 0.200 kg/cm2, respectively. The friability was within the acceptable limits of pharmacopoeial specifications (0.31 to 0.71%), which indicates the good mechanical strength of the tablets. Drug release was retarded with an increase in polymer concentration due to the gelling property of polymers. The in vitro drug release from the proposed system was best explained by Higuchi’s model, indicating that drug release from tablets displayed a diffusion-controlled mechanism. The results clearly indicate that guar gum could be a potential hydrophilic carrier in developing oral controlled drug delivery systems. Based on the study results, formulations F8 was selected as the best formulation.

Enhanced Microencapsulation of C-Phycocyanin from Arthrospira by Freeze-Drying with Different Wall Materials

RESEARCH BACKGROUND

C-phycocyanin (C-PC), a water-soluble blue pigment, was extracted from microalgae Arthrospira sp. C-PC could be a good substitute for synthetic pigments with high antioxidant activity. However, C-PC is unstable due to sensitivity to temperature, light, pH and oxygen; therefore, applications of C-PC in food and other products are limited. Microencapsulation of C-PC using freeze-drying is a solution to this problem and is considered a suitable method for drying the heat-sensitive pigment.

EXPERIMENTAL APPROACH

C-phycocyanin was extracted from Arthrospira platensis. C-PC microcapsules were modified by freeze-drying, with maltodextrin and gum Arabic used as microencapsulation wall materials at different fractions from 0 to 100%. The physical properties including moisture content and water activity, solubility, hygroscopicity, bulk density, colour appearance, particle morphology and size distribution of the produced powders were evaluated. Thermal stability and antioxidant activity of freeze-dried microencapsulated C-PC powders were also assessed.

RESULTS AND CONCLUSIONS

Freeze-dried microencapsulated C-PC powders with maltodextrin and gum Arabic as wall materials gave high encapsulation efficiency of around 99%. At higher gum Arabic mass fraction, moisture content decreased and water activity improved. Maltodextrin gave higher solubility of C-PC powders whereas gum Arabic led to a similar colour of C-PC to those without microencapsulation. Freeze-dried microencapsulated C-PC powders were composed of different sized microparticles regardless of the combination of wall materials with amorphous glassy shapes. Thermal stability of encapsulated C-PC increased and also showed high antioxidant properties.

NOVELTY AND SCIENTIFIC CONTRIBUTION

This study demonstrates that the freeze-dried microencapsulated C-PC powders have pigment stability with antioxidant properties and are resistant to high temperatures. Therefore, they may have a potential for the development of microencapsulated C-PC as a functional ingredient with improved colour and bioactive properties. Such a product can be applied in food, cosmetic, biotechnology and nutraceutical industries.