Development and storage study of reduced calorie aloe vera (Aloe barbadensis Miller) based pineapple fruit jam

A Novel Strategy for Mixed Jam Evaluation: Apparent Indicator, Sensory, Metabolomic, and GC-IMS Analysis

Jam is a popular traditional and modern food product for daily consumption. However, the benefits of mixed jams over single-fruit jams have not been thoroughly explored, with analyses limited to superficial indices. In this study, Xinjiang special Morus nigra L. and Prunus domestica L. were used as raw materials to prepare single-fruit and mixed jams, and their differences in antioxidants, organoleptic qualities, pH, texture, and color were analyzed. The dynamics of metabolites before and after thermal processing were assessed using untargeted metabolomics. The results indicate that the main metabolites were flavonoids, terpenoids, amino acids, phenolic acids, and carbohydrates. Flavonoid metabolites changed significantly after thermal processing, with 40 up-regulated and 13 down-regulated. During storage, polyphenols were the prominent differential metabolites, with fifty-four down-regulated and one up-regulated. Volatile aroma components were analyzed using gas chromatography-ion mobility spectrometry (GC-IMS); the aroma components E-2-hexenal, E-2-pentenal, 3-methylbutanal, 1-penten-3-ol, tetrahydro-linalool, 1-penten-3-one, hexyl propionate, isoamyl acetate, α-pinene, and propionic acid in mixed jam were significantly higher than in single-fruit jam. In this study, untargeted metabolomics and GC-IMS were used to provide a more comprehensive and in-depth evaluation system for jam analysis.

Ultrasound-mediated hydration of finger millet: Effects on antinutrients, techno-functional and bioactive properties, with evaluation of ANN-PSO and RSM optimization methods

Finger millet, rich in nutrients, faces bioavailability limitations due to antinutrients like phytates and tannins that can be reduced by ultrasound mediated hydration (USH). Here, USH process of finger millet was optimized by varying ultrasound amplitude, water to grain ratio (W:G), treatment time, and frequency for reducing antinutrients and improving techno-functional attributes. USH resulted in a maximum reduction of 73% and 71% in phytates and tannins, respectively. The process was modeled using artificial neural network (ANN) and response surface methodology (RSM). ANN outperformed RSM in process prediction, and particle swarm optimization (ANN-PSO) suggested optimal conditions: 76% amplitude, W:G of 3.5:1, 17.5 min treatment time at 40 kHz. USH samples showed higher β-sheet, β-turn, and random coil proportions, with lower α-helix levels. Multivariate analysis also identified higher amplitude and frequency, with shorter treatment time as desirable USH conditions. USH could aid in enhancing commercial viability and nutritional quality of finger millet.

Effect of Storage Time on the Physical, Chemical, and Rheological Properties of Blueberry Jam: Experimental Measurements and Artificial Neural Network Simulation

Reversible data hiding (RDH) is crucial in modern data security, ensuring confidentiality and tamper-proofness in various industries like copyright protection, medical imaging, and digital forensics. As technology advances, RDH techniques become essential, but the trade-off between embedding capacity and visual quality must be heeded. In this paper, the relative correlation between the pixel's local complexity and its directional prediction error is employed to enhance an efficient RDH without using a location map. An embedding process based on multiple cumulative peak region localization (MCPRL) is proposed to hide information in the 3D-directional prediction error histogram with a lower local complexity value and avoid the underflow/overflow problems. The carrier image is divided into three color channels, and then each channel is split into two non-overlapping sets: blank and shadow. Two half-directional prediction errors (the blank set and the shadow set) are constructed to generate a full-directional prediction error for each color channel belonging to the host image. The local complexity value and directional prediction error are critical metrics in the proposed embedding process to improve security and robustness. By utilizing these metrics to construct a 3D stego-Blank Set, the 3D stego-shadow Set will be subsequently constructed using the 3D blank set. The proposed technique outperforms other state-of-the-art techniques in terms of embedding capacity, image quality, and robustness against attacks without an extra location map. The experimental results illustrate the effectiveness of the proposed method for various 3D RDH techniques.

Nutritional probing and storage stability of papaya jam supplemented with date pit powder

Jam Quality is a factor robustly influenced by storage conditions. The current research aimed to develop papaya jam with improved nutritional attributes, rheological profile, and shelf-life utilizing date pit powder as a functional ingredient. The effect of date pit powder on the formulated product's physicochemical, microbial, and organoleptic properties was analyzed. Results revealed that overall mineral profile (0.35-1.11%), crude fiber (0.56-2.01%), pH (3.51-3.70%), and antioxidant properties (22.97-30.67%) were significantly increased while water activity reduced (0.77-0.73). Moreover, date pit powder improved the color scores like a*(10.10-10.67), b* (8.13-8.78), L* (25.56-28.09), and textural attributes (Cohesiveness: 0.83-0.90; Firmness: 6.82-6.93) of functional papaya jam. Microbial count reduced from 3.60 × 10⁵-3.06 × 10⁵ cfu/ml by adding date pit powder and staying within the acceptable limit (4.13 × 10⁵-3.60 × 10⁵ cfu/ml) during 2-month storage at refrigeration. Organoleptic evaluation depicted that samples treated with date pit powder scored better than the control, and a sample with 75% pectin replacement was considered best.

Effect of Marjoram Leaf Powder Addition on Nutritional, Rheological, Textural, Structural, and Sensorial Properties of Extruded Rice Noodles

Food-to-food fortification is an emerging technique to enrich the micronutrients in foods. Pertaining to this technique, noodles could also be fortified with natural fortificants. In this study, marjoram leaf powder (MLP) at a level of 2-10% was used as a natural fortificant to produce fortified rice noodles (FRNs) through an extrusion process. The MLP addition caused a significant increase in the iron, calcium, protein, and fiber in the FRNs. The noodles had a lower whiteness index than unfortified noodles but had a similar water absorption index. The water solubility index increased significantly due to the higher water retention ability of MLP. A rheological study showed a minimal effect of fortification on the gelling strength of the FRNs at lower levels. The microstructural studies found incremental cracks, which facilitated a lower cooking time and hardness but had an insignificant effect on the cooked noodle texture. Fortification improved the total phenolic content, antioxidant capacity, and total flavonoid content. However, no significant changes in bonds were observed, but a reduction in the noodles' crystallinity could be seen. The sensory analysis of the noodles reflected a higher acceptability of the 2-4% MLP fortified samples compared to the others. Overall, the MLP addition improved the nutritional content, antioxidant activity, and the cooking time but slightly affected the rheological, textural, and color properties of the noodles.