Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (4,080)

Search Parameters:
Keywords = texture analysis

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 1792 KiB  
Article
The Effect of a Zeolite Addition to Modified Bitumen on the Properties of Stone Matrix Asphalt Lärmarmer Mixtures Produced as Warm Mix Asphalt
by Marta Wasilewska, Roman Pacholak, Pawel Gierasimiuk, Wladyslaw Gardziejczyk, Agnieszka Woszuk, Leslaw Bichajlo and Tomasz Siwowski
Materials 2024, 17(23), 5848; https://doi.org/10.3390/ma17235848 - 28 Nov 2024
Abstract
This paper presents the properties of an SMA LA (stone matrix asphalt Lärmarmer) mixture based on the polymer-modified binder PMB 45/80-55, formed by the addition of zeolites (synthetic zeolite type Na-P1 and natural zeolite—clinoptilolite). The compositions of the SMA 11, SMA 8 LA [...] Read more.
This paper presents the properties of an SMA LA (stone matrix asphalt Lärmarmer) mixture based on the polymer-modified binder PMB 45/80-55, formed by the addition of zeolites (synthetic zeolite type Na-P1 and natural zeolite—clinoptilolite). The compositions of the SMA 11, SMA 8 LA and SMA 11 LA mixtures based on modified bitumen with PMB 45/80-55 (reference mixture) or PMB 45/80-55 with Na-P1 or clinoptilolite were determined. Their resistance to permanent deformation, water sensitivity, water permeability and susceptibility to changes in texture and skid resistance during the period of use were verified. Adding zeolites reduced the production temperature by as much as 15 °C for the SMA 11 LA mixtures and 20 °C for SMA 8 LA. The addition of zeolites did not significantly affect the resistance to permanent deformation, the water permeability or the mass loss. The mixtures with clinoptilolite were resistant to the harmful effects of water, while the mixtures with Na-P1 proved more sensitive to water. Water permeability tests showed a higher permeability for SMA 11 LA compared to SMA 8 LA due to the higher nominal aggregate size. The Cantabro test showed greater particle loss for SMA 11 LA than for SMA 8 LA. A skid resistance and macrotexture analysis indicated that the SMA LA layers required special maintenance on the road due to the clogging of pores in the mix structure. Full article
(This article belongs to the Special Issue Advances in Asphalt Materials (Second Volume))
21 pages, 1220 KiB  
Article
Fermented Cashew Nut Cheese Alternative Supplemented with Chondrus crispus and Porphyra sp.
by Bruno M. Campos, Bruno Moreira-Leite, Abigail Salgado, Edgar Ramalho, Isa Marmelo, Manuel Malfeito-Ferreira, Paulo Sousa, Mário S. Diniz and Paulina Mata
Appl. Sci. 2024, 14(23), 11082; https://doi.org/10.3390/app142311082 - 28 Nov 2024
Abstract
This study is aimed at the development of a fermented cashew nut cheese alternative supplemented with Chondrus crispus and Porphyra sp. and the evaluation of the impact of seaweed supplementation through analysis of physicochemical, microbiological, and organoleptic properties of the developed food products. [...] Read more.
This study is aimed at the development of a fermented cashew nut cheese alternative supplemented with Chondrus crispus and Porphyra sp. and the evaluation of the impact of seaweed supplementation through analysis of physicochemical, microbiological, and organoleptic properties of the developed food products. The total lipid content decreased with the supplementation with seaweeds. Crude protein content also slightly decreased, while elemental analysis showed that mineral and trace element (Ca, K, Mg, Na, Fe, I, Se, and Zn) content increased when C. crispus was added to the paste. The analyses of color and textural (TPA) attributes showed that these were significantly influenced by adding seaweeds to the cashew paste. Generally, the microbiological results comply with the different European guidelines for assessing the microbiological safety of ready-to-eat foods placed on the market, except for aerobic mesophilic bacteria and marine agar counts. Flash Profile analysis allowed for distinguishing sample attributes, showing an increased flavor complexity of the plant-based cheese alternatives supplemented with seaweeds. Overall, the study indicates that seaweed enrichment mainly influenced the physicochemical and sensory characteristics of plant-based cheese alternatives. Full article
(This article belongs to the Special Issue Food Fermentation: New Advances and Applications)
Show Figures

Figure 1

Figure 1
<p>Representative images of the fermented cashew nut cheese alternatives (FCNCAs) after 15 days of ripening. From left to right: (<b>a</b>) fermented cashew nut cheese alternative control (FCNCA-C); (<b>b</b>) fermented cashew nut cheese alternative with <span class="html-italic">Chondrus crispus</span> (FCNCA-CC); and (<b>c</b>) fermented cashew nut cheese alternative with <span class="html-italic">Porphyra</span> sp. (FCNCA-P).</p>
Full article ">Figure 2
<p>Flowchart of the production and analysis processes of the fermented cashew nut cheese alternatives (FCNCAs).</p>
Full article ">Figure 3
<p>Biplot map of Generalized Procrustes Analysis (GPA) performed on Flash Profile (FP) data and the lexicon used to describe the various attributes of the fermented cashew nut cheese alternatives at the F<sub>1</sub> and F<sub>2</sub> dimensions: (<b>a</b>) appearance; (<b>b</b>) aroma; (<b>c</b>) flavor; (<b>d</b>) texture; and (<b>e</b>) after-taste.</p>
Full article ">
17 pages, 16316 KiB  
Article
Effects of Ozone Gas and Slightly Acidic Electrolyzed Water on the Quality of Salmon (Salmo salar) Fillets from the Perspective of Muscle Protein
by Yun-Fang Qian, Lu Sun, Jing-Jing Zhang, Cheng-Jian Shi and Sheng-Ping Yang
Foods 2024, 13(23), 3833; https://doi.org/10.3390/foods13233833 - 28 Nov 2024
Viewed by 128
Abstract
To elucidate the mechanisms of ozone gas (OG) and slight acid electrolyzed water (SA) on the quality changes in texture, water-holding capacity, and softening of salmon, the bacterial growth, total volatile basic nitrogen, thiobarbituric acid reactive substance, a* value, texture properties, carbonyl content [...] Read more.
To elucidate the mechanisms of ozone gas (OG) and slight acid electrolyzed water (SA) on the quality changes in texture, water-holding capacity, and softening of salmon, the bacterial growth, total volatile basic nitrogen, thiobarbituric acid reactive substance, a* value, texture properties, carbonyl content and free sulfhydryl content, myofibrillar fragmentation index, and proteolytic activities of salmon treated by OG (1 mg/m3 for 10 min) and SA (ACC 30 mg/L, 5 min) individually and in combination were studied. The results showed that total viable counts of SA + OG (dipped in SAEW for 5 min, followed by exposure to ozone for 10 min) was about 3.36 log CFU/g lower than the control (CK) (dipped in distilled water for 5 min) on day 10. Further studies indicate that at the end of storage, the hardness of SA + OG fillets only decreased by 33.95%, while the drip loss and myofibrillar fragmentation index (MFI) were the lowest (i.e., 14.76% and 101.07). The activity of cathepsin D was extensively inhibited by SA + OG, which was only 2.063 U/g meat at the end. In addition, the carbonyl content was 1.90 μmol/g protein, and the free sulfhydryl content was 39.70 mg/mL in the SA + OG group, indicating that protein oxidation was also effectively inhibited. Correlation analysis shows that bacteria and endogenous proteases are the main causes of protein degradation. Overall, the combination of OG and SAEW is an effective way to maintain the muscle quality of salmon by inhibiting bacterial growth and endogenous enzymes. Full article
(This article belongs to the Section Food Packaging and Preservation)
Show Figures

Figure 1

Figure 1
<p>Changes in TVC (<b>a</b>), PBC (<b>b</b>), TVB-N (<b>c</b>), TBARS (<b>d</b>), a* value (<b>e</b>), and TCA-soluble peptides (<b>f</b>) of salmon fillets after treatment with ozone gas and slightly acidic electrolyzed water. (Different letters represent significant differences between four groups on the same day (<span class="html-italic">p</span> &lt; 0.05)).</p>
Full article ">Figure 2
<p>Changes in hardness (<b>a</b>), springiness (<b>b</b>), gumminess (<b>c</b>), cohesiveness (<b>d</b>), and chewiness (<b>e</b>) of salmon fillets after treatment with ozone gas and slightly acidic electrolyzed water. (Different letters represent significant differences between four groups on the same day (<span class="html-italic">p</span> &lt; 0.05)).</p>
Full article ">Figure 3
<p>Changes in drip loss (<b>a</b>), and microstructural characteristics (<b>b</b>) of salmon fillets after treatment with ozone gas and slightly acidic electrolyzed water (Different letters represent significant differences between four groups on the same day (<span class="html-italic">p</span> &lt; 0.05)).</p>
Full article ">Figure 4
<p>Changes in carbonyl content (<b>a</b>), free sulfhydryl content (<b>b</b>), and FTIR spectra of salmon fillets (Fresh vs. samples on day 6 (<b>c</b>), Fresh vs. samples on day 12 (<b>d</b>)); secondary structure content (<b>e</b>–<b>h</b>) of salmon fillets treated with ozone gas and slightly acidic electrolyzed water (different letters represent significant differences between the four groups on the same day (<span class="html-italic">p</span> &lt; 0.05)).</p>
Full article ">Figure 5
<p>SDS-PAGE profiles of sarcoplasmic proteins (<b>a</b>) and myofibrillar proteins (<b>b</b>), the changes of MFI values (<b>c</b>), total proteolytic activity (<b>d</b>), cathepsin B activity (<b>e</b>), cathepsin D activity (<b>f</b>), cathepsin L activity (<b>g</b>), and calpain activity (<b>h</b>) of salmon fillets after treatment with ozone gas and slightly acidic electrolyzed water (different letters represent significant differences between the four groups on the same day (<span class="html-italic">p</span> &lt; 0.05)).</p>
Full article ">Figure 6
<p>Correlation analysis of texture characteristics, protein oxidation and degradation, and endogenous proteases in salmon treated with ozone gas and slightly acidic electrolyzed water.</p>
Full article ">Figure 7
<p>Mechanism diagram of ozone gas and slightly acidic electrolyzed water.</p>
Full article ">
19 pages, 5417 KiB  
Article
Effect of Carrot Callus Cells on the Mechanical, Rheological, and Sensory Properties of Hydrogels Based on Xanthan and Konjac Gums
by Elena Günter, Oxana Popeyko, Fedor Vityazev, Natalia Zueva, Inga Velskaya and Sergey Popov
Gels 2024, 10(12), 771; https://doi.org/10.3390/gels10120771 - 27 Nov 2024
Viewed by 190
Abstract
The study aims to develop a plant-based food gel with a unique texture using callus cells and a mixture of xanthan (X) and konjac (K) gums. The effect of encapsulation of carrot callus cells (0.1 and 0.2 g/mL) on properties of X-K hydrogels [...] Read more.
The study aims to develop a plant-based food gel with a unique texture using callus cells and a mixture of xanthan (X) and konjac (K) gums. The effect of encapsulation of carrot callus cells (0.1 and 0.2 g/mL) on properties of X-K hydrogels was studied using the mechanical and rheological analysis with a one-way ANOVA and Student’s t-test used for statistical analysis. Hedonic evaluation and textural features were obtained from 35 volunteers using a nine-point hedonic scale and a 100 mm visual analog scale with the Friedman’s test and the Durbin post hoc test used for statistical analysis. Mechanical hardness, gumminess, and elasticity increased by 1.1–1.3 and 1.1–1.8 times as a result of encapsulation 0.1 and 0.2 g/mL cells, respectively. The addition of cells to the hydrogels resulted in an increase in the complex viscosity, strength, and number of linkages in the gel. The hydrogel samples received identical ratings for overall and consistency liking, as well as taste, aroma, and texture features. However, the callus cell-containing hydrogel had a graininess score that was 82% higher than the callus cell-free hydrogel. The obtained hydrogels based on gums and immobilized carrot callus cells with unique textures may be useful for the development of diverse food textures and the production of innovative functional foods. Full article
(This article belongs to the Special Issue Recent Developments in Food Gels (2nd Edition))
Show Figures

Figure 1

Figure 1
<p>Нardness (<b>a</b>), cohesiveness (<b>b</b>), gumminess (<b>c</b>), elasticity (<b>d</b>), springiness (<b>e</b>), and chewiness (<b>f</b>) of hydrogels based on an aqueous mixture of xanthan (X) and konjac (K) gums. The data are presented as the mean ± S.D., <span class="html-italic">n</span> = 12. Different lowercase letters (a, b, and c) indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) between the means for different gum concentrations; # <span class="html-italic">p</span> &lt; 0.05 vs. X:K ratio of 1:1, * <span class="html-italic">p</span> &lt; 0.05 vs. X:K ratio of 2:1.</p>
Full article ">Figure 2
<p>Mechanical properties of gum/callus hydrogels based on a 1.0% aqueous mixture of xanthan and konjac gums in different ratios (1:1, 2:1, and 3:1) and 0.1 g/mL carrot callus cells (<b>a</b>). Cell-free gum hydrogels were used as controls (<b>b</b>). Hardness and elasticity are expressed in units of H and mm, respectively. The data are presented as the mean ± S.D., <span class="html-italic">n</span> = 8. # <span class="html-italic">p</span> &lt; 0.05 vs. X:K ratio of 1:1, * <span class="html-italic">p</span> &lt; 0.05 vs. X:K ratio of 2:1, ** <span class="html-italic">p</span> &lt; 0.05 vs. corresponding experimental characteristics in (<b>a</b>).</p>
Full article ">Figure 3
<p>Digital images of cell-free gum hydrogels (X2K1-J) (<b>a</b>) and gum/callus hydrogels based on carrot juice, a 1.0% mixture of xanthan and konjac gums in a 2:1 ratio, and carrot callus cells (0.2 g/mL) (X2K1-0.2DC-J) (<b>b</b>).</p>
Full article ">Figure 4
<p>The effect of carrot callus cell concentration (0.1 and 0.2 g/mL) on the mechanical properties of hydrogels based on carrot juice and a 1.0% mixture of xanthan and konjac gums in a 2:1 ratio. Hardness and elasticity are expressed in units of N and mm, respectively. The data are presented as the mean ± S.D., <span class="html-italic">n</span> = 40. Different lowercase letters (a, b, and c) indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) between the means for different callus cell concentrations. Cell-free gum hydrogels (X2K1-J) were used as controls.</p>
Full article ">Figure 5
<p>Mechanical properties of hydrogels based on a 1.0% mixture of xanthan and konjac gums in a 1:2 ratio, 0.2 g/mL carrot callus cells, and carrot juice. Hardness and elasticity are expressed in units of H and mm, respectively. The data are presented as the mean ± S.D., <span class="html-italic">n</span> = 12. Different lowercase letters (a and b) indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) between the means. # <span class="html-italic">p</span> &lt; 0.05 vs. X2K1-J (X:K ratio of 2:1) in <a href="#gels-10-00771-f004" class="html-fig">Figure 4</a>, * <span class="html-italic">p</span> &lt; 0.05 vs. X2K1-0.2DC-J (X:K ratio of 2:1) in <a href="#gels-10-00771-f004" class="html-fig">Figure 4</a>. Cell-free gum hydrogels (X1K2-J) were used as controls.</p>
Full article ">Figure 6
<p>Rheological properties of hydrogels based on 0.1 and 0.2 g/mL carrot callus cells, carrot juice, and a 1.0% mixture of xanthan and konjac gums in a 2:1 (<b>a</b>,<b>c</b>) and 1:2 (<b>b</b>,<b>d</b>) ratio. Storage modulus (G′, filled symbols) and loss modulus (G″, empty symbols) are represented as a function of shear strain (<b>a</b>,<b>b</b>) or frequency (<b>c</b>,<b>d</b>). Cell-free gum hydrogels (X2K1-J, X1K2-J) were used as controls.</p>
Full article ">Figure 7
<p>Complex viscosity as a function of frequency of hydrogels based on 0.1 and 0.2 g/mL carrot callus cells, carrot juice, and a 1.0% mixture of xanthan and konjac gums in a 2:1 (<b>a</b>) and 1:2 (<b>b</b>) ratio. Cell-free gum hydrogels (X2K1-J, X1K2-J) were used as controls.</p>
Full article ">
11 pages, 1721 KiB  
Article
Peptidomic Analysis Reveals Temperature-Dependent Proteolysis in Rainbow Trout (Oncorhynchus mykiss) Meat During Sous-Vide Cooking
by Miyu Sakuyama, Yuri Kominami and Hideki Ushio
Proteomes 2024, 12(4), 36; https://doi.org/10.3390/proteomes12040036 - 27 Nov 2024
Viewed by 199
Abstract
Sous vide, a cooking method that involves vacuum-sealed fish at low temperatures, yields a uniquely tender, easily flaked texture. Previous research on sous-vide tenderization has focused on thermal protein denaturation. On the other hand, the contribution of proteases, activated at low temperatures in [...] Read more.
Sous vide, a cooking method that involves vacuum-sealed fish at low temperatures, yields a uniquely tender, easily flaked texture. Previous research on sous-vide tenderization has focused on thermal protein denaturation. On the other hand, the contribution of proteases, activated at low temperatures in fish meat, has been suggested. However, the details of protein degradation remain unclear. This study employed SDS-PAGE/immunoblot and peptidomic analysis of rainbow trout to assess proteolysis during sous-vide cooking. The results from SDS-PAGE and immunoblot analysis indicated reduced thermal aggregation of sarcoplasmic proteins and increased depolymerization of actin under low-temperature cooking conditions. A comparison of the peptidome showed that the proteolysis of myofibrillar proteins was accelerated during sous-vide cooking, with distinct proteases potentially activated at different cooking temperatures. Terminome analysis revealed the contribution of specific proteases at higher temperatures in rainbow trout. The results of this study demonstrate the thermal denaturation of sarcoplasmic proteins and proteolysis of myofibrillar proteins in rainbow trout meat during sous-vide cooking and its temperature dependence. The methodology in the present study could provide insights into the optimization of cooking conditions for different fish species, potentially leading to improved texture and quality of sous-vide products. Full article
Show Figures

Figure 1

Figure 1
<p>Comparison of TPA parameters in raw and sous-vide-cooked rainbow trout meat: hardness (<b>a</b>); cohesiveness (<b>b</b>); springiness (<b>c</b>); and resilience (<b>d</b>) (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, Dunnett test vs. raw, <span class="html-italic">n</span> = 3).</p>
Full article ">Figure 2
<p>SDS-PAGE separation (<b>a</b>) and immunoreactive proteins (<b>b</b>). Separation of proteins extracted from raw and sous-vide-cooked rainbow trout meat with a low ionic strength buffer. Lane 1, raw; lane 2, SV-52; lane 3, SV-65; and lane 4, SV-80.</p>
Full article ">Figure 3
<p>Quantification of the degraded muscle proteins related to meat texture in the rainbow trout meat. The data bar indicates the amount of each degraded protein.</p>
Full article ">Figure 4
<p>Sequence specificity in the terminome of the rainbow trout: raw (<b>a</b>); SV-52 (<b>b</b>); SV-65 (<b>c</b>); and SV-80 (<b>d</b>). Each column corresponds to the P2−P2′ subsite.</p>
Full article ">
12 pages, 2687 KiB  
Article
Non-Destructive Monitoring of External Quality of Date Palm Fruit (Phoenix dactylifera L.) During Frozen Storage Using Digital Camera and Flatbed Scanner
by Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak and Krzysztof Rutkowski
Sensors 2024, 24(23), 7560; https://doi.org/10.3390/s24237560 - 27 Nov 2024
Viewed by 294
Abstract
The emergence of new technologies focusing on “computer vision” has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh and frozen ‘Mejhoul’ and ‘Boufeggous’ date [...] Read more.
The emergence of new technologies focusing on “computer vision” has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh and frozen ‘Mejhoul’ and ‘Boufeggous’ date palm cultivars stored for 6 months at −10 °C and −18 °C. Their quality was evaluated, in a non-destructive manner, based on texture features extracted from images acquired using a digital camera and flatbed scanner. The whole process of image processing was carried out using MATLAB R2024a and Q-MAZDA 23.10 software. Then, extracted features were used as inputs for pre-established algorithms–groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. Among 599 features, only 5 to 36 attributes were selected as powerful predictors to build desired classification models based on the “Functions-Logistic” classifier. The general architecture exhibited clear differences in classification accuracy depending mainly on the frozen storage period and imaging device. Accordingly, confusion matrices showed high classification accuracy (CA), which could reach 0.84 at M0 for both cultivars at the two frozen storage temperatures. This CA indicated a remarkable decrease at M2 and M4 before re-increasing by M6, confirming slight changes in external quality before the end of storage. Moreover, the developed models on the basis of flatbed scanner use allowed us to obtain a high correctness rate that could attain 97.7% in comparison to the digital camera, which did not exceed 85.5%. In perspectives, physicochemical attributes can be added to developed models to establish correlation with image features and predict the behavior of date fruit under storage. Full article
(This article belongs to the Special Issue Artificial Intelligence and Key Technologies of Smart Agriculture)
Show Figures

Figure 1

Figure 1
<p>Experimental design for frozen date fruit under storage. MEJ: ‘Mejhoul’; BFG: ‘Boufeggous’; FRZ10: freezing at −10 °C; M0: month 0; Cam: camera; Scan: scanner.</p>
Full article ">Figure 2
<p>Logical flowchart for date fruit image processing and analysis.</p>
Full article ">Figure 3
<p>Illustration of background images and their respective ROIs for ‘Mejhoul’ (<b>a</b>) and ‘Boufeggous’ (<b>b</b>) cultivars.</p>
Full article ">Figure 4
<p>Accuracy rates obtained using the flatbed scanner and digital camera for discrimination between frozen date samples under different temperatures.</p>
Full article ">Figure 5
<p>Confusion matrix, ROC area, and RRSE of freeze-stored ‘Mejhoul’ and ‘Boufeggous’ cultivars obtained using a flatbed scanner (<b>a</b>) and digital camera (<b>b</b>).</p>
Full article ">Figure 6
<p>Classification correctness between fresh and freeze-stored date fruit at 2, 4, and 6 months at −10 °C and −18 °C for ‘Mejhoul’ samples acquired with (<b>a</b>) a digital camera and (<b>b</b>) flatbed scanner and ‘Boufeggous’ samples acquired with (<b>c</b>) a digital camera and (<b>d</b>) flatbed scanner.</p>
Full article ">
13 pages, 2638 KiB  
Article
Effect of Pea Protein Isolate–Soybean Meal Ratio on Fiber Structure and Texture Properties of High-Moisture Meat Analogs
by Zhongjiang Wang, Yachao Tian, Fangxiao Lou and Zengwang Guo
Foods 2024, 13(23), 3818; https://doi.org/10.3390/foods13233818 - 27 Nov 2024
Viewed by 410
Abstract
Inadequate fibrous attributes and prohibitive pricing are pivotal barriers to the broader market penetration of meat analogs (MAs). This research endeavors to address these impediments by formulating a blend of cost-effective soybean meal (SM) and pea protein isolate (PPI) across a spectrum of [...] Read more.
Inadequate fibrous attributes and prohibitive pricing are pivotal barriers to the broader market penetration of meat analogs (MAs). This research endeavors to address these impediments by formulating a blend of cost-effective soybean meal (SM) and pea protein isolate (PPI) across a spectrum of ratios (PPI:SM = 1:0, 8:2, 6:4, 4:6, 2:8, and 0:1). The analysis of textural properties elucidated that the integration of SM markedly diminished the textural rigidity and mastication resistance of MAs. Employing scanning electron microscopy (SEM) and fibrillation degree metrics, it was ascertained that the most favorable fibrous architecture of MAs was attained at a PPI to SM ratio of 6:4. Further experimental evidence underscored that the synergistic interaction between SM and PPI catalyzed the conversion of free sulfhydryl groups into disulfide linkages, a pivotal mechanism in the augmentation of MAs’ fibrous matrices. The conclusions drawn from this study provide substantive contributions to the formulation of superior-quality, economically viable MAs, and could potentially accelerate their market acceptance. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the extruder.</p>
Full article ">Figure 2
<p>Influence of PPI:SM ratio on MA microscopic image.</p>
Full article ">Figure 3
<p>Influence of the PPI:SM ratio on MA rheological properties. (<b>A</b>–<b>C</b>) respectively represent G′, G″, and the viscosity diagrams of the MA.</p>
Full article ">Figure 4
<p>Influence of PPI:SM ratio on DSC thermal profiles.</p>
Full article ">Figure 5
<p>Influence of the PPI:SM ratio on MA T2 relaxation time.</p>
Full article ">
6 pages, 1701 KiB  
Proceeding Paper
Topography Pre-Treatment of Laser-Textured Surfaces for Friction Simulation in AVL Excite
by Gábor Laki, László Boros and András Lajos Nagy
Eng. Proc. 2024, 79(1), 95; https://doi.org/10.3390/engproc2024079095 - 27 Nov 2024
Viewed by 108
Abstract
This study presents the challenges arising during the numerical design and simulation of surface-microtextured piston rings. The evaluation of performance is based on the values of asperity and hydrodynamic friction, as well as the lubricant film thickness. The simulation tool AVL Excite Piston [...] Read more.
This study presents the challenges arising during the numerical design and simulation of surface-microtextured piston rings. The evaluation of performance is based on the values of asperity and hydrodynamic friction, as well as the lubricant film thickness. The simulation tool AVL Excite Piston & Rings is used to perform the calculations. The aim of this study is to understand how selected surface pre-processing (pre-treatment) steps affect the calculations. Two methods are presented to achieve a realistic surface topography representative of a state after running-in. Pre-treatment is performed through metrological filtering and thresholding of the topography, and Gaussian smoothing of the virtually applied micro-texture array is carried out. The results show the anticipated behavior of decreasing asperity and hydrodynamic friction losses with the concurrent application of both techniques. Full article
Show Figures

Figure 1

Figure 1
<p>Exemplary surface scan of cylinder’s running surface showing (<b>a</b>) topography before digital filtering (virtual running-in) and (<b>b</b>) topography after digital filtering. Red arrows highlight surface features, which were smoothed during virtual running-in: protruding asperities (1,2) are removed, while valleys (3) are rounded, which resembles naturally occurring phenomena due to wear (1,2) and accumulation of wear debris (3).</p>
Full article ">Figure 2
<p>A visual description of the effect of Gaussian smoothing, showing a stylized dimpled surface from a topside view and in a cross-section profile. As the transitional region between the plateau (hatched) and the dimple (dark gray) is rounded during smoothing, the dimple diameter increases (⌀<sub>smoothed</sub> &gt; ⌀<sub>original</sub>) and the total plateau area decreases (A<sub>smoothed</sub> &lt; A<sub>original</sub>).</p>
Full article ">Figure 3
<p>The mean asperity contact pressure (<span class="html-italic">p<sub>Asp</sub></span>) as a function of the ratio of the separation distance between the two contacting surfaces to the standard deviation of the surface roughness (<span class="html-italic">H</span>).</p>
Full article ">Figure 4
<p>Results of (<b>a</b>) mean asperity friction power loss, (<b>b</b>) mean hydrodynamic friction power loss, and (<b>c</b>) mean of minimum oil film thickness calculated on running face of top piston ring, represented as percentage change in mean value during one full cycle of 720 °C compared to calculation without pre-treatment.</p>
Full article ">
23 pages, 4780 KiB  
Article
Characteristic Description and Statistical Model-Based Method for Sea Clutter Modeling
by Huafeng He, Zhen Li, Xi Zhang, Jianguang Jia, Yaomin He and Yongquan You
Remote Sens. 2024, 16(23), 4429; https://doi.org/10.3390/rs16234429 - 26 Nov 2024
Viewed by 383
Abstract
The modeling and analysis of sea clutter are of great significance in radar target detection studies in marine environments. Sea clutter typically exhibits non-Gaussian characteristics and spatiotemporal correlations, posing challenges for modeling, especially when generating simulation data of continuous correlated non-Gaussian random processes. [...] Read more.
The modeling and analysis of sea clutter are of great significance in radar target detection studies in marine environments. Sea clutter typically exhibits non-Gaussian characteristics and spatiotemporal correlations, posing challenges for modeling, especially when generating simulation data of continuous correlated non-Gaussian random processes. This paper proposes a novel method for sea clutter modeling. First, feature description functions are constructed to individually characterize the amplitude, temporal, and spatial correlations of sea clutter, allowing for an accurate depiction of its characteristics with fewer parameters. Subsequently, simulation data are generated based on these feature description functions, satisfying the amplitude distribution, temporal correlation, and spatial correlation characteristics of sea clutter. Additionally, complex signal forms are introduced in the underlying signal processing to generate texture and speckle components of sea clutter, enhancing the alignment of simulation data with actual data. Through comparison with measured sea clutter data, the proposed method has been shown to accurately simulate complex sea clutter with real-world characteristics. Full article
Show Figures

Figure 1

Figure 1
<p>Flowchart of the proposed method in this paper.</p>
Full article ">Figure 2
<p>Amplitude feature extraction.</p>
Full article ">Figure 3
<p>Temporal correlation feature extraction.</p>
Full article ">Figure 4
<p>Spatial correlation feature extraction.</p>
Full article ">Figure 5
<p>Characteristic functions of the generated speckle component.</p>
Full article ">Figure 6
<p>Amplitude distribution function of the generated texture component.</p>
Full article ">Figure 7
<p>The feature functions of the mid–short–range sea clutter data from the file “20210106155330_01_staring” generated by the proposed method.</p>
Full article ">Figure 8
<p>The feature functions of the long-range sea clutter data from the file “20210106155330_01_staring “ generated by the proposed method.</p>
Full article ">Figure 9
<p>Characteristic functions of the sea clutter data from the file “19980204_221104_ANTSTEP” generated by the proposed method.</p>
Full article ">Figure 10
<p>Characteristic functions of the sea clutter data from the file “19980204_220325_ANTSTEP” generated by the proposed method.</p>
Full article ">
13 pages, 2080 KiB  
Article
Revealing the Surface and In-Depth Operational Performances of Oxygen-Evolving Anode Coatings: A Guideline for the Synthesis of Inert Durable Anodes in Metal Electrowinning from Acid Solutions
by Jovana Bošnjaković, Vladimir Panić, Maja Stevanović, Srecko Stopic, Jasmina Stevanović, Branimir Grgur and Gavrilo Šekularac
Metals 2024, 14(12), 1339; https://doi.org/10.3390/met14121339 - 26 Nov 2024
Viewed by 219
Abstract
The electrochemical performances of an oxygen-evolving anode produced by the reactivation of waste Ti substrate by a typical IrO2-Ta2O5 coating are correlated to the textural (non)uniformities of the coating and its exhaustion state. Coating degradation is considered operational [...] Read more.
The electrochemical performances of an oxygen-evolving anode produced by the reactivation of waste Ti substrate by a typical IrO2-Ta2O5 coating are correlated to the textural (non)uniformities of the coating and its exhaustion state. Coating degradation is considered operational loss of the activity in a metal electrowinning process. It was found that (pseudo)capacitive performances can vary over the coating surface by 20–30% and depend on the type of dynamics of the input perturbation: constant through cyclic voltammetry (CV) or discontinuous time-dependent through electrochemical impedance spectroscopy (EIS). CV-EIS data correlation enabled profiling of the capacitive properties through the depth of a coating and over its surface. The correlation was confirmed by the findings for the analysis of coating activity for an oxygen evolution reaction, finally resulting in the reliable proposition of a mechanism for the operational loss of the anode. It was found that the less compact and thicker coating parts performed better and operated more efficiently, especially at lower operational current densities. Full article
(This article belongs to the Special Issue Feature Papers in Extractive Metallurgy)
Show Figures

Figure 1

Figure 1
<p>Digital image of coated electrode.</p>
Full article ">Figure 2
<p>Cyclic voltammograms of IrO<sub>2</sub>-Ta<sub>2</sub>O<sub>5</sub> coatings on Ti substrate recorded before (full line) and after (dashed line) the accelerated stability test (AST) at positions 1–3 ((<b>a</b>–<b>c</b>), respectively). (<b>d</b>) Voltammetric capacitances calculated from the curves in (<b>a</b>–<b>c</b>).</p>
Full article ">Figure 2 Cont.
<p>Cyclic voltammograms of IrO<sub>2</sub>-Ta<sub>2</sub>O<sub>5</sub> coatings on Ti substrate recorded before (full line) and after (dashed line) the accelerated stability test (AST) at positions 1–3 ((<b>a</b>–<b>c</b>), respectively). (<b>d</b>) Voltammetric capacitances calculated from the curves in (<b>a</b>–<b>c</b>).</p>
Full article ">Figure 3
<p>Plots of the EIS data (symbols) of the IrO<sub>2</sub>-Ta<sub>2</sub>O<sub>5</sub> coating on Ti obtained at the open circuit potential before (full symbols) and after (empty symbols) an accelerated stability test (AST) in 10% H<sub>2</sub>SO<sub>4</sub> for coating surface positions 1 (<b>a</b>), 2 (<b>b</b>) and 3 (<b>c</b>). The responses of the transmission line’s equivalent electrical circuits are shown as lines.</p>
Full article ">Figure 4
<p>Surface (positions 1–3) and in-depth (effective coating depth) distribution of the coating capacitance (<b>a</b>,<b>c</b>) and pore resistance (<b>b</b>,<b>d</b>) through the coating layer of the as-prepared (<b>a</b>,<b>b</b>) and exhausted (<b>c</b>,<b>d</b>) oxygen-evolving electrode (effective coating depth correlated to the nth order of equivalent transmission line equivalent circuit). Here, 1 = coating surface, n = coating/substrate interface, and ∅ = no data for n = 7 at position 3 after the AST.</p>
Full article ">Figure 5
<p>IR drop-corrected (<b>a</b>) and normalized (<b>b</b>) polarization curves for oxygen evolution reaction on IrO<sub>2</sub>-Ta<sub>2</sub>O<sub>5</sub> coating on Ti obtained before (full lines) and after (dash lines) an accelerated stability test (AST) in 10% H<sub>2</sub>SO<sub>4</sub> at three different coating surface positions.</p>
Full article ">
15 pages, 431 KiB  
Article
Plant-Based Meat Alternatives Predicted by Theory of Planned Behavior Among Midwest Undergraduates
by Rachel H. Luong, Donna M. Winham, Mack C. Shelley and Abigail A. Glick
Foods 2024, 13(23), 3801; https://doi.org/10.3390/foods13233801 - 26 Nov 2024
Viewed by 407
Abstract
Plant-based meat alternatives (PBMAs) such as the Impossible Burger® imitate animal meat appearance, taste, feel, and texture. Part of their consumer appeal are the views that PBMAs are more environmentally friendly, reduce inhumane treatment of animals, and/or have preferred nutritional attributes. College-educated [...] Read more.
Plant-based meat alternatives (PBMAs) such as the Impossible Burger® imitate animal meat appearance, taste, feel, and texture. Part of their consumer appeal are the views that PBMAs are more environmentally friendly, reduce inhumane treatment of animals, and/or have preferred nutritional attributes. College-educated adults are one of the larger markets for these products. This cross-sectional online survey utilized the Theory of Planned Behavior to predict self-reported intakes of PBMAs among 536 undergraduates aged 18–25 at a Midwest university. Sixty-one percent had eaten PBMAs, and 17% wanted to try them. Twenty-two percent were uninterested non-consumers. Their top reason for not eating PBMAs was that they had no reason to decrease their meat intake. Multinomial logistic regression analysis showed subjective norms and positive attitudes about PBMAs increased the odds of more frequent intake, whereas non-consumers had less support from social contacts, but greater perceived behavioral control over general food access. Thus, those with supportive social influences, concerns about the environment, and animal welfare are more likely to consume PBMAs. More frequent PBMA consumption was observed among U.S.-born multicultural students, food insecure students, and those with less perceived behavioral control over food access. Future research should investigate the nuances between these associations further by examining the types of PBMAs consumed, their costs, and retail sources across student demographics. Full article
(This article belongs to the Section Plant Foods)
Show Figures

Figure 1

Figure 1
<p>Theory of planned behavior conceptual framework for plant-based meat alternatives (PBMA) consumption.</p>
Full article ">
26 pages, 8854 KiB  
Article
Deep Fat Frying Characteristics of Malpoa: Kinetics, Heat, and Mass Transfer Modeling
by Puneeta Gupta, Imdadul Hoque Mondal, Kshirod Kumar Dash, Geetika, Tejas Suthar, Khadija Ramzan, Endre Harsanyi, Ayaz Mukarram Shaikh and Kovács Béla
Processes 2024, 12(12), 2662; https://doi.org/10.3390/pr12122662 - 26 Nov 2024
Viewed by 369
Abstract
This article investigated deep-frying characteristics of malpoa for varied frying time (2–10 min) and temperature (170–190 °C). The evaluation encompassed a comprehensive analysis of textural and color kinetics and heat and mass transfer modeling during deep fat frying of malpoa balls. Such investigations [...] Read more.
This article investigated deep-frying characteristics of malpoa for varied frying time (2–10 min) and temperature (170–190 °C). The evaluation encompassed a comprehensive analysis of textural and color kinetics and heat and mass transfer modeling during deep fat frying of malpoa balls. Such investigations confirmed an enhancement in fat content from 10.2 to 41.65%. On the other hand, textural properties such as hardness, cohesiveness, and springiness varied from 3.14 to 22.59 N/mm, 0.22 to 0.76, and 15.5 to 49.56, respectively. Similarly, color parameters such as b*/a* and ΔE varied from 3.31 to 1.55 and 55.36 to 75.48. For the textural and color kinetics, the activation energies ranged between 58.65 and 85.82 kJ/mol and 31.34 and 64.34 kJ/mol. Similarly, for a variation in frying time from 2 to 10 min, responses (hardness, cohesiveness, springiness, and overall color) varied across the following ranges: 3.15–13.57 N, 0.22–0.66, 15.5–35.5, and 55.63–63.50 and 5.60–20.60 N, 0.30–0.77, 22.35–49.56, and 62.26–75.65 for temperatures of 170 and 190 degrees, respectively. On the other hand, heat and mass transfer analysis indicated a Biot number and heat transfer coefficient within the range of 0.31–0.65 and 25.58–34.64 for 170–190 °C. Thus, this investigation provides a deeper insight of the deep fat frying characteristics of malpoa. This provides a guideline for the food processing sector for such products. Full article
Show Figures

Figure 1

Figure 1
<p>Variation in hardness with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 2
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for hardness. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 3
<p>Arrhenius plot of temperature dependence of rate constant for various textural parameters. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 4
<p>Variation in cohesion with frying time at various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 5
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for cohesion. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 5 Cont.
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for cohesion. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 6
<p>Variation in springiness with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 7
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for springiness. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 7 Cont.
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for springiness. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 8
<p>Variation in L<sup>*</sup> with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 9
<p>Model fitness plot for (<b>a</b>) zero-order (<b>b</b>) first-order reaction for L<sup>*</sup>. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 10
<p>Arrhenius plot of the temperature dependence of rate constant for color parameters. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 11
<p>Variation in a<sup>*</sup>/b<sup>*</sup> with frying time for various temperature. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 12
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for b<sup>*</sup>/a<sup>*</sup>. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 12 Cont.
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for b<sup>*</sup>/a<sup>*</sup>. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 13
<p>Variation in ΔE with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 14
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for ΔE. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 14 Cont.
<p>Model fitness plot for (<b>a</b>) zero-order and (<b>b</b>) first-order reaction for ΔE. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 15
<p>Variation in the logarithm of temperature ratio with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 16
<p>Variation in the logarithm of moisture ratio with frying time for various temperatures. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 17
<p>Variation in fat content with frying time and temperature for deep fat fried malpoa. Results are expressed as mean ± standard deviation (n = 3).</p>
Full article ">
15 pages, 4814 KiB  
Article
Impact of Cooking on Tuber Color, Texture, and Metabolites in Different Potato Varieties
by Jun Hu, Jinxue Hu, Shaoguang Duan, Fankui Zeng, Shuqing Zhang and Guangcun Li
Foods 2024, 13(23), 3786; https://doi.org/10.3390/foods13233786 - 25 Nov 2024
Viewed by 298
Abstract
Potatoes are a globally important crop with high nutritional value. Different potato varieties display notable variations in color, texture, and nutrient composition. However, the influence of cooking on tuber color, texture, and metabolites has not been comprehensively explored. This study evaluated the color [...] Read more.
Potatoes are a globally important crop with high nutritional value. Different potato varieties display notable variations in color, texture, and nutrient composition. However, the influence of cooking on tuber color, texture, and metabolites has not been comprehensively explored. This study evaluated the color and texture of five potato varieties before and after cooking. Cooking significantly altered tuber color, decreased hardness and adhesiveness, and increased springiness, particularly after steaming. The metabolomic analysis of Zhongshu 49 (ZS49) and Shishu 3 (SH3) tubers was conducted using gas chromatography–mass spectrometry (GC-MS) and ultra-high performance liquid chromatography (UHPLC)-MS/MS. GC-MS identified 122 volatile metabolites, with 42 significantly varying between cooking treatments, while UHPLC-MS/MS detected 755 nonvolatile metabolites, 445 of which showed significant differences. Compared to ZS49, SH3 exhibited a marked increase in umami- and flavor-related metabolites, especially after cooking. This study provides new insights into how cooking affects the quality, texture, and metabolite profiles of potato tubers. Full article
(This article belongs to the Section Nutraceuticals, Functional Foods, and Novel Foods)
Show Figures

Figure 1

Figure 1
<p>Analysis of color difference of five potato varieties. Morphological observation of different cooking methods (<b>A</b>). L* value (<b>B</b>), a* value (<b>C</b>), b* value (<b>D</b>), and delta E value (<b>E</b>) of five potato varieties that were cooked using different cooking methods were investigated, <span class="html-italic">n</span> = 3. Different letters represent significant differences between different treatment and varieties at <span class="html-italic">p</span> &lt; 0.05 level.</p>
Full article ">Figure 2
<p>Analysis of tuber texture of five potato varieties. Hardness (<b>A</b>), gumminess (<b>B</b>), cohesiveness (<b>C</b>), springiness (<b>D</b>), adhesiveness (<b>E</b>), and chewiness (<b>F</b>). Different letters represent significant difference between different treatment and varieties at <span class="html-italic">p</span> &lt; 0.05 level; <span class="html-italic">n</span> = 3.</p>
Full article ">Figure 3
<p>Correlation analysis of relationship between starch content, granule size, starch viscosity, and texture traits. Amylose: amylose content; Starch: starch content; BH: boiling hardness; BG: boiling gumminess; BC: boiling cohesiveness; BS: boiling springiness; BA: boiling adhesiveness; BCH: boiling chewiness; RH: raw hardness; RG: raw gumminess; RC: raw cohesiveness; RS: raw springiness; RA: raw adhesiveness; RCH: raw chewiness; SH: steaming hardness; SG: steaming gumminess; SC: steaming cohesiveness; SS: steaming springiness; SA: steaming adhesiveness; SCH: steaming chewiness; VT: viscosity temperature; PV: peak viscosity; FV: final viscosity; BV: breakdown viscosity; SV: setback viscosity; PVT: peak viscosity time; D4: D[4,3]; D3: D[3,2]. Purple indicates a positive correlation, green indicates a negative correlation, and numerical values are correlation coefficient values that are significant at the <span class="html-italic">p</span> &lt; 0.05 level.</p>
Full article ">Figure 4
<p>Comparison of volatile compounds in potato tubers of ZS49 and SH3 after using various cooking methods. (<b>A</b>) Statistical analysis of volatile compounds. (<b>B</b>) PCA score plot illustrating independent experiment replicates. (<b>C</b>) Heat map displaying differential metabolites; white blocks show the average relative expression intensity of all volatile compounds, while red blocks show metabolites that were upregulated and blue blocks show metabolites that were downregulated.</p>
Full article ">Figure 5
<p>Analysis of nonvolatile metabolites in potato tubers treated with different cooking methods. (<b>A</b>) PCA score plot illustrating independent experiment replicates of nonvolatile metabolites. (<b>B</b>) Statistics of different metabolite categories. (<b>C</b>–<b>E</b>) Volcano plot visualization of different metabolites in raw, steamed, and cooked potato tubers. Red spots represent upregulated metabolites and green spots represent downregulated metabolites. (<b>F</b>) K-means cluster analysis for differential metabolites.</p>
Full article ">
18 pages, 355 KiB  
Review
A Global Review of Cheese Colour: Microbial Discolouration and Innovation Opportunities
by Ana Rita Ferraz, Cristina Santos Pintado and Maria Luísa Serralheiro
Dairy 2024, 5(4), 768-785; https://doi.org/10.3390/dairy5040056 - 25 Nov 2024
Viewed by 367
Abstract
Cheese is a biologically active food product, characterised by its colour, texture, and taste. Due to its rich matrix of fats and proteins, as well as the fact that the cheese’s surface acts as its own packaging, the cheese becomes more susceptible to [...] Read more.
Cheese is a biologically active food product, characterised by its colour, texture, and taste. Due to its rich matrix of fats and proteins, as well as the fact that the cheese’s surface acts as its own packaging, the cheese becomes more susceptible to contamination by microorganisms during the ripening process, particularly bacteria and fungi. The ripening of cheese involves several biochemical reactions, with the proteolytic activity of the cheese microbiota being particularly significant. Proteolysis results in the presence of free amino acids, which are precursors to various metabolic mechanisms that can cause discolouration (blue, pink, and brown) on the cheese rind. Surface defects in cheese have been documented in the literature for many years. Sporadic inconsistencies in cheese appearance can lead to product degradation and economic losses for producers. Over the past few decades, various defects have been reported in different types of cheese worldwide. This issue also presents opportunities for innovation and development in edible and bioactive coatings to prevent the appearance of colour defects. Therefore, this review provides a comprehensive analysis of cheese colour globally, identifying defects caused by microorganisms. It also explores strategies and innovation opportunities in the cheese industry to enhance the value of the final product. Full article
16 pages, 8003 KiB  
Article
Characterization of Cell Wall Compositions of Sodium Azide-Induced Brittle Mutant Lines in IR64 Variety and Its Potential Application
by Anuchart Sawasdee, Tsung-Han Tsai, Yi-Hsin Chang, Jeevan Kumar Shrestha, Meng-Chun Lin, Hsin-I Chiang and Chang-Sheng Wang
Plants 2024, 13(23), 3303; https://doi.org/10.3390/plants13233303 - 25 Nov 2024
Viewed by 249
Abstract
The rice brittle culm is a cell wall composition changed mutant suitable for studying mechanical strength in rice. However, a thorough investigation of brittle culm has been limited due to the lack of diverse brittle mutants on similar genetic backgrounds in cell walls. [...] Read more.
The rice brittle culm is a cell wall composition changed mutant suitable for studying mechanical strength in rice. However, a thorough investigation of brittle culm has been limited due to the lack of diverse brittle mutants on similar genetic backgrounds in cell walls. In this study, we obtained 45 various brittle mutant lines (BMLs) from the IR64 mutant pool induced by sodium azide mutagenesis using the finger-bending method and texture profile analysis. The first scoring method was established to differentiate the levels of brittleness in rice tissues. The variation of cell wall compositions of BMLs showed that the brittleness in rice primarily correlated with cellulose content supported by high correlation coefficients (R = −0.78) and principal component analysis (PCA = 81.7%). As demonstrated using PCA, lower correlation with brittleness, hemicellulose, lignin, and silica were identified as minor contributors to the overall balance of cell wall compositions and brittleness. The analysis of hydrolysis and feeding indexes highlighted the importance of diversities of brittleness and cell wall compositions of BMLs and their potential applications in ruminant animals and making bioenergy. These results contributed to the comprehension of brittleness and mechanical strength in rice and also extended the applications of rice straw. Full article
Show Figures

Figure 1

Figure 1
<p>The breaking force of a fresh flag leaf of 45 BMLs and IR64 at the maturity stage. Breaking force (N/mm) was the highest force required to break the sample when using the texture profile analyzer (TPA) divided by its leaf width. The error bar is SD obtained by three repetitions (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 2
<p>Diverse phenotypes of the BMLs from the IR64 mutant pool. (<b>A</b>) Pigmentation diversity in different tissues. (<b>B</b>) Diversity of leaf character. (<b>C</b>) Diversity of leaf green intensity by IRRI’s leaf color chart. (<b>D</b>) Diversity of grain characters (Bar = 1 cm).</p>
Full article ">Figure 3
<p>Correlation coefficients of phenotypes of BMLs. Larger numerical values and sizes indicate a stronger correlation. LL, leaf length; LW, leaf width; TH, time to heading date; SL, stem length; PN, panicle number; TM, time to maturity; PL, panicle length; GL, grain length; GW, grain width; GR, grain L/W ratio; PF, percentage of fertility; BF, breaking force. The interpretation of coefficient intervals: 0–0.19 (very low), 0.2–0.39 (low), 0.4–0.59 (middle), 0.6–0.79 (strong), and 0.8–1.0 (very strong). The asterisk indicates a significance (* = <span class="html-italic">p</span> &lt; 0.05; ** = <span class="html-italic">p</span> &lt; 0.01; *** = <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 4
<p>Correlation coefficient and principal component analysis of the cell wall compositions, breaking force, and brittleness score. (<b>A</b>) Correlation between the cell wall compositions: cellulose, hemicellulose, lignin, silica, brittleness score, and the breaking force of the flag leaf of brittle culm mutant lines was illustrated. Larger numerical values and sizes indicate a stronger correlation. The interpretation of coefficient intervals: 0–0.19 (very low), 0.2–0.39 (low), 0.4–0.59 (middle), 0.6–0.79 (strong), and 0.8–1.0 (very strong). The asterisk indicates a significance (** = <span class="html-italic">p</span> &lt; 0.01; *** = <span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) Principal component analysis (PCA) biplot of BMLs on the phenotypic variables (arrows). The first two (PC1 + PC2) components accounted for 81.7% of the variance.</p>
Full article ">Figure 5
<p>The practice of BMLs for rice farming machinery. (<b>A</b>) Bar chart showing the average percentage of leaf damage in each brittleness score group after the Megi typhoon in 2016. The red arrow pointed to the damaged leaves. (<b>B</b>) Seedling of the brittle mutant line (AZ1805) was transplanted using a transplanting machine. (<b>C</b>) The grain of the brittle mutant line was harvested using a combiner. (<b>D</b>) The degradation of stubble of the brittle mutant line (<b>Left</b>) was faster than the wild type (<b>Right</b>).</p>
Full article ">Figure 6
<p>The hydrolysis means the wild type (IR64, score 0) and BMLs (score 5) within 24 h of incubation. * = significant difference by t-test (<span class="html-italic">p</span>-value &lt; 0.05).</p>
Full article ">
Back to TopTop