Animal Fibers Research Articles

Agroforestry systems: an alternative to intensify forage-based livestock in the Brazilian Amazon

Brazil is one of the few countries in the world that can produce animal products, grains, fibers, and bioenergy in the same area, either in a consortium, rotation, or succession. Our objective was to compare pasture productivity and animal performance in agroforestry systems with grass monoculture in the Brazilian Amazon Biome. The experiment was carried out in Sinop, MT, Brazil, with Nellore steers in a continuous stocking with variable stocking rate. The experimental design was a randomized complete block, with four systems and four replicates. The palisadegrass [Brachiaria brizantha (Hochst. ex A. Rich.) R. D. Webster cv. Marandu] was planted in the four systems: livestock (grass monoculture); livestock–forestry [eucalyptus trees (Eucalyptus urograndis; hybrid of Eucalyptus grandis W. Hill ex Maiden and Eucalyptus urophylla S. T. Blake) arranged in three-row groves spaced 30 m apart]; crop–livestock (palisadegrass after two years of crops); and crop–livestock–forestry (palisadegrass after two years of crops with single rows of eucalyptus trees spaced 37 m apart). The herbage accumulation was greater in the systems with the two previous cropping years (crop–livestock and crop–livestock–forestry) than in the livestock and livestock–forestry, in both seasons. In the crop–livestock–forestry, the greatest herbage accumulation associated with the modified microclimate supported the greatest average daily gain (0.750 kg BW day− 1), stocking rate in both seasons, resulting in the greatest gain per area (940 kg BW ha− 1). We conclude that agroforestry systems assure pasture productivity and animal performance similar or greater than livestock (grass monoculture). Furthermore, the combination of two previous crop years and the least tree density optimized the synergy between crop, livestock, and forestry components, improving beef cattle productivity in crop–livestock–forestry systems.

Inner Mongolian Cashmere Goat Secondary Follicle Development Regulation Research Based on mRNA-miRNA Co-analysis

Inner Mongolia cashmere goats, as an important part of animal husbandry production, play an important role in animal fiber industry. In recent years, scientific research has made a lot of explorations on the molecular regulation mechanism of hair follicle cycle growth, but few studies have been reported on the development of cashmere hair in fetal period. This study was based on the completion of 21 skin samples of mRNA and miRNA sequencing in 7 fetal periods (45 days, 55 days,65 days,75 days,95 days,115 days and 135 days) of the Inner Mongolia Cashmere goat. The target genes of miRNA associated with the development of secondary hair follicles in the cashmere goats were selected through the combination analysis of mRNA and miRNA data. Then the overexpression vector was constructed and the interaction between the miRNA and the target gene was identified by Dual-Luciferase Reporter Gene System. The function and interaction relationship of chi-miR-199a-5p and TGF-β2 were verified by RT-qPCR and western blot at the level of the fibroblasts in Inner Mongolia Cashmere goat. It provides a theoretical basis for further study of miRNA and its target genes regulating the occurrence and development of skin hair follicles. As the result shows, the expression trends of 7 genes (BAMBI, SMAD1, LTBP1, PPP2R1B, ID4, BMP8B and PITX2) and 7 miRNA (chi-miR-17-5p, chi-miR-125b-3p, chi-miR-21-5p, chi-miR-143-5p and chi-miR-106b-5p) in the skin samples for the seven stages of the fetus were shown to be consistent with the sequencing results. the results of sequencing are reliable. The correlation coefficient of TGF-β2 and chi-miR-199a-5p in fetal 45d-135d expression is −0.84, showing a strong negative correlation, The target relationship was preliminarily judged. The results of double luciferase vector report showed that chi-miR-199a-5p significantly decreased the expression of luciferase in TGF-β2 3′UTR, It is determined that there is a reciprocal relationship between them at a specific time. We transfected chi-miR199a-5p-FAM mimics into fibroblasts cultured in vitro from Inner Mongolia cashmere goats. After transfection, the cells were harvested to extract total RNA and protein. The mRNA and protein expression levels of TGF-β2 in fibroblasts were detected by RT-qPCR and western blot. It was verified that chi-miR-199a-5p inhibited TGF-β2 expression at both mRNA and protein translation levels in fibroblasts. At the same time, it was again proved that the TGF-β2 gene is a target gene of chi-miR199a-5p.

Identification of wool and mohair fibres with texture feature extraction and deep learning

Wool and mohair fibres are both animal-based fibres and having circular scales on their microscopic images from the longitudinal view. Although they look very similar in their microscopic view, they show different physical/chemical properties which determine their usage area. Thus, in textile industry, they need to be separated carefully from each other. The separation of wool/mohair fibres is an important issue and can be performed with human eye by using the microscopic images, that is not time/cost effective and not objective. The novelty of the presented study is to design an objective, easy, rapid, time and cost-effective method in order to separate wool fibre from mohair fibre by using a texture analysis based identification method. For this purpose, microscopic images of both wool and mohair fibres were preprocessed as the texture images. Local binary pattern-based feature extraction process and deep learning were separately used to get determinative information from the fibres. In order to identify the samples, the classification based method was completed. Experimental results indicated that an accurate texture analysis for this kind of animal fibres is possible to identify wool and mohair fibres by using deep learning and machine learning with 99.8% and 90.25% accuracy rates, respectively.

Effect of chemical treatment on mechanical properties of prawn antenna reinforced waste plastic particulates filled polymer composites

In today’s world, the need for the alternate materials is escalating nowadays due to the scarcity for the traditional materials. Mostly the composites are reinforced with natural fibers like plant fibers. Only some animal fibers are used as reinforcement in the polymer composites. Due to this there are numerous research works are under progress in identifying the suitable fibers for enhancing the properties of the composites. In this work, the antenna of the prawns is used as reinforcement in the polyester matrix. The influences of the chemical treatments are studied by treating the fibers in three types of chemicals. The fibers are reinforced and filled by waste plastic particulates to enhance the mechanical properties. The fibers are treated with hydrogen peroxide, potassium hydroxide and sodium hydroxide. The treated fibers and waste plastic particulates are reinforced to the matrix at fixed weight proportions and the optimum combination levels and treatment were found using ANOVA.

Study of mechanical properties of the polymer matrix composite material (solid wool)

The work describe in our project refers to the mechanical characterization of Animal fibers (wool) for the production of composite materials. The use of wool fiber is pointing the ecological problem of composite material recyclability. We manufacture the most natural, lowest impact and highest quality wool composite material. Hardness test are used to determine the hardness of material. Compression test are used to determine the compression resistance capacity of the material.

Raw feeding in dogs and cats

This article reviews the reasons for feeding domestic dogs and cats a diet based on raw meaty bones. Dogs, though able and willing to eat a wide variety of foods, exhibit numerous carnivorous traits, and are classified as carnivores. Dogs have been shown to prefer foods with nutrient profiles much closer to those of a wild wolf diet than those of kibbled diets, raising the possibility that dogs fed modern commercial diets, low in protein, and high in carbohydrate and additives, might face physiological and metabolic challenges. Cats are strict, obligate carnivores with characteristic dentition and a short digestive tract. A well-constructed raw food diet is high in protein, nutrient-rich, satiating, extremely palatable, and high in prebiotic ‘animal fibre’. Early domestic dogs were not ‘fed’ but allowed to forage for themselves like their wild ancestors. Today, most of our pets are fed on highly processed, dried diets, known commonly as ‘biscuit’ or ‘kibble’, barely recognisable from canine and feline ancestral diets. The intestinal microbiota has been found to vary significantly between raw-fed and non-raw-fed dogs. A species-appropriate, nutrient-rich diet, most closely resembling canine and feline ancestral diets, would seem a sensible option if our pets are to achieve optimal health. Feeding real, whole food consisting mainly of good quality raw meat on the bone, skin, offal, eggs and fish, is perhaps as close as we can come, in modern, Western society, to achieve this.

Comparison of Physico-mechanical Properties of Fibre and Yarn Made of Alpaca, Sheep, and Goat Wool

ABSTRACT Textile industry is one of the most important branches of the economy of many countries in the world and the importance of wool is still huge. Due to the unique properties of natural animal fibers and their positive effect on the human organism, the authors decided to evaluate and compare the quality of fibers and yarn coming from three animal species, i.e., sheep, goats, and alpacas. The study was included the physico-mechanical analysis of properties of fiber and yarn: such as diameter, breaking force, elongation at break, Young modulus, breaking strain and strain energy. The study on the selected physical and mechanical properties of the fibers showed that goat fibers are the stiffest, but concurrently the most durable, while the yarn made of sheep fibers is the most resistant, the yarn of alpaca fibers is the most elastic, and that of goat fibers is the most rigid.

Automatic identification of cashmere and wool fibers based on the morphological features analysis

Identification of wool and cashmere extremely similar fibers is always an important topic in the textile industry. In order to solve this problem much better, a novel fiber identification method based on the extraction and analysis of the morphological features was proposed in this paper. Firstly, the original fiber images were captured by the self-developed system including the optical microscope and digital camera. The influence of the acquisition process may lead to the low contrast and impurities, so the original fiber images needed to be processed by the image enhancement and de-noise to obtain the available fiber images with a better quality. Then the hessian matrix of processed images was put into the Frangi filter to detect the edge of the fiber scales, and the binary images of filter output images were processed to obtain the signal-pixel scale skeleton. The connected region labeling algorithm can be adopted for the scale skeleton images to mark and extract every scale from the whole fiber according to the different color information. Next, the three morphological features including scale height, fiber diameter and their ratio can be calculated by the self-defined vertical line rotation analysis method, and the mean value of five different scales was calculated as the final features to describe one fiber. In the experiment, 500 fiber cashmere and 500 wool fiber images were collected for the whole research, and a Bayesian classification model for identifying wool and cashmere fibers was established based on the statistical assumptions of three morphological characteristics. The results show that the identification accuracy of the method proposed in this paper could reached the 94.2%. It also proves that this novel method can be used for the identification of cashmere and wool extremely similar animal fibers.

Effect of stabiliser classes (animal proteins, vegetable proteins, starches, hydrocolloids and dietary fibre) on the physicochemical properties of a model lean meat product

SummaryThe effects of eleven ingredients (originating from various ingredient classes: animal proteins, plant proteins, starches, hydrocolloids and fibres) applied in two different concentrations on drip loss, rheological characteristics and hardness were evaluated in a lean meat model system. The high concentration of potato starch, insoluble citrus fibre, rice starch or pea protein significantly (P < 0.05) reduced drip losses (6.92%, 17.87%, 15.70%, 17.60%, respectively) compared to control (30.80%), while rheological measures and hardness remained unchanged (P > 0.05). Moreover, the addition of low concentrations of soluble citrus fibre did not significantly affect hardness (4.11 N), whereas its inclusion at high concentrations had a significant effect on the final hardness (7.17 N). Among all the tested ingredients, xanthan presented the lowest drip loss value (0.12% and 0.40% for high and low concentration, respectively). Finally, gelatine did not show any differences in water holding capacity, storage modulus nor hardness compared with the control group.

Development of the anti-cancer food scoring system 2.0: Validation and nutritional analyses of quantitative anti-cancer food scoring model.

BACKGROUND/OBJECTIVESWe have previously designed the anti-cancer food scoring model (ACFS) 1.0, an evidence-based quantitative tool analyzing the anti-cancer or carcinogenic potential of diets. Analysis was performed using simple quantitative indexes divided into 6 categories (S, A, B, C, D, and E). In this study, we applied this scoring model to wider recipes and evaluated its nutritional relevance.MATERIALS/METHODSNational or known regional databases were searched for recipes from 6 categories: Korean out-dining, Korean home-dining, Western, Chinese, Mediterranean, and vegetarian. These recipes were scored using the ACFS formula and the nutrition profiles were analyzed.RESULTSEighty-eight international recipes were analyzed. All S-graded recipes were from vegetarian or Mediterranean categories. The median code values of each category were B (Korean home-dining), C (Korean out-dining), B (Chinese), A (Mediterranean), S (vegetarian), and D (Western). The following profiles were correlated (P < 0.05) with ACFS grades in the univariate trend analysis: total calories, total fat, animal fat, animal protein, total protein, vitamin D, riboflavin, niacin, vitamin B12, pantothenic acid, sodium, animal iron, zinc, selenium, and cholesterol (negative trends), and carbohydrate rate, fiber, water-soluble fiber, vitamin K, vitamin C, and plant calcium (positive trends). Multivariate analysis revealed that animal fat, animal iron, and niacin (negative trends) and animal protein, fiber, and vitamin C (positive trends) were statistically significant. Pantothenic acid and sodium showed non-significant negative trends (P < 0.1), and vitamin B12 showed a non-significant positive trend.CONCLUSIONThis study provided a nutritional basis and extended the utility of ACFS, which is a bridgehead for future cancer-preventive clinical trials using ACFS.

Tensile and Hardness Properties of Sheep Wool Fiber Reinforced Polyester Composite

Modern industries are looking for a replacement of existing materials with a lightweight polymer-based reinforced material. In general, the polymer materials are reinforced with natural fiber, animal fiber, and wood fiber. This work deals with the importance of animal fiber in making a composite. The most widely used polyester resin is used as matrix materials and uniform sized (10-20mm) sheep wool fiber is used as reinforcement materials for making sheep wool reinforced composite. The random orientation of fibers was adopted for three different weight percentage (wt%) as 20%, 30%, and 40%. All the different weight fraction of composites is developed by using a compression molding technique. The compression mold ejected material is sized as per the ASTM standards for various tests. The tensile properties and hardness of the composite is determined experimentally. Scanning Electron Microscope image is taken to analysis the interfacial properties, internal structure and cracks of the fabricated composite.

Animal fibre use in the Keriya valley (Xinjiang, China) during the Bronze and Iron Ages: A proteomic approach

Textile technology strongly advanced with sedentism and pastoralism. During prehistory, many populations settled in central Eurasia, a place of extensive exchange and cultural contact. In the Taklamakan desert, the dry climate enabled good preservation of ancient textiles. The study presented here aimed to identify animal fibres from Bronze Age and Iron Age sites in the Keriya valley (Xinjiang, China) using proteomics. A large corpus of 109 keratin extracts obtained from raw fibres or textiles was analysed, enabling us to establish a corrected and improved list of peptide markers for the identification of species, not only among the family Bovidae, but also for camels and humans. In total, we were able to identify 97% of the sampled objects to the taxonomic level of tribe and 85% of caprines to the level of genus. The assemblage was dominated by hair of sheep (57.8%) followed by goat (16.5%), cattle (8.3%), camel (0.9%), human (0.9%) and non-differentiated Caprinae (sheep or goat) (12.8%). The study showed a continuity between the two sites in this respect. It revealed a choice of raw material linked to the function of the textile, with most woven textiles being made from sheep's wool and most pelts being obtained from goat. Comparison with the bone assemblage of one of the sites provided insight into the herd management strategies. The results confirm the heuristic potential of the proteomic approach for the determination of archaeological fibres and for textile studies in general. Data are available via ProteomeXchange with identifier PXD012189.

Comparative transcriptome analysis reveals the genetic basis of coat color variation in Pashmina goat

The genetics of coat color variation remains a classic area. Earlier studies have focused on a limited number of genes involved in color determination; however, the complete set of trait determinants are still not well known. In this study, we used high-throughput sequencing technology to identify and characterize intricate interactions between genes that cause complex coat color variation in Changthangi Pashmina goats, producer of finest and costly commercial animal fiber. We systematically identified differentially expressed mRNAs and lncRNAs from black, brown and white Pashmina goat skin samples by using RNA-sequencing technique. A pairwise comparison of black, white and brown skin samples yielded 2479 significantly dysregulated genes (2422 mRNA and 57 lncRNAs). Differentially expressed genes were enriched in melanin biosynthesis, melanocyte differentiation, developmental pigmentation, melanosome transport activities GO terms. Our analysis suggested the potential role of lncRNAs on color coding mRNAs in cis and trans configuration. We have also developed online data repository as a component of the study to provide a central location for data access, visualization and interpretation accessible through http://pcd.skuastk.org/.

An image-based method for the automatic recognition of cashmere and wool fibers

Due to the similarity of the morphological and textural structure between cashmere and wool fibers, it is a great challenge to identify these two animal fibers automatically. In this paper, one set of image-based method using the gray level co-occurrence matrix algorithm, the interactive measurement algorithm and the k-means clustering algorithm were proposed to identify cashmere and wool fibers quickly and accurately. Firstly, thousands of fiber images were observed by optical microscope and captured by digital camera and two different preprocessing methods were used to obtain the input images for the different feature extraction algorithm. Then the texture features were extracted by the gray level co-occurrence matrix and the diameter of fibers was measured by the interactive measurement algorithm. Finally, the extracted features were fed into the fiber identification system based on k-means algorithm for classification. The experimental results indicated that the proposed method was feasible for the recognition of cashmere and wool fibers with a high recognition of 94.29%.

Homogeneous melanin/silica core-shell particles incorporated in poly (methyl methacrylate) for enhanced UV protection, thermal stability, and mechanical properties

Natural melanin is abundant in wide ranges of sources, especially in dark colored animal fibers. Despite the unique features and functionalities, its extensive analyses and applications have greatly been hindered due to its serious self-aggregation. To tackle this issue, this study uses the Stöber method to encapsulate the melanin particles extracted from colored alpaca fibers with a thin layer of silica. It was observed that the melanin/silica core-shell particles (MSCPs) with 20 h encapsulation time provided excellent dispersity and optical performance. Different concentrations of MSCPs were then doped in poly (methyl methacrylate) (PMMA) through an in-situ polymerization process to obtain MSCP/PMMA bulk materials. The produced composite materials showed homogeneous appearance, controllable UV absorbance and visible light transmittance. The thermal stability, durability under UV, and mechanical properties of the fabricated composites were examined and the role of melanin on the obtained results was elucidated. It was observed that the PMMA samples with MSCPs showed excellent durability under UV even after 100 h irradiation. Testing the thermal stability and mechanical properties (hardness and elastic modulus) of MSCP/PMMA samples confirmed the positive effect of MSCPs presence in PMMA. These results demonstrated the applicability of natural melanin-based materials and composites in UV-protection related fields.

Microstructure of Thermoplastic Composites Reinforced with Wool and Wood

In the last decades the studies on thermoplastic composites reinforced with natural fibres have been mostly focused on vegetable lignocellulosic or cellulosic fibres. These materials provide eco-sustainable solutions for a large range of applications and have been actually adopted by multiple industries. The interest on fibres of animal origin is more recent and research on composites reinforced with these fibres predominantly composed of keratin, such as wool, feathers or silk, is increasing in virtue of some advantageous properties that may overcome some of the intrinsic limitations from vegetable fibres. The combined use of vegetable and animal fibres in composites appropriate for melt blending processing is at early stages of research. After chemical treatments, the fibres of animal origin have been mostly applied as binders between vegetable fibres and polymers, not as main constituents of these composites. The use of both types of fibres simultaneously in composites of thermoplastic matrices is the subject of the present study wherein the fibres of animal origin (wool) are different kinds of residues from a textile industry and the fibres of vegetable origin (wood) are residues from carpentry activities. The chemical composition, the macro and microstructure of the fibres is analyzed, as well as that of composites that combine non-biodegradable and biodegradable polymers with diverse ratios of fibres in different conditions (wool as cards, yarns and felt cloths; wood as sawdust). The addition of coupling agents to enhance the compatibility between wool, wood and different polymers is also analysed.

Characterizing historical textiles and clothing with proteomics

This paper is a review of proteomics and mass spectrometric techniques used for the study of historical textiles and garments. First applied on archaeological animal fibers over a decade ago, proteomics has made important contributions to the analysis of ancient proteins and to cultural heritage studies. The field of proteomics has the potential to give a better understanding of the modes of fabrication of ancient textiles, their composition and pathways of degradation, as well as the development of animal fibers through domestication and breeding. This review summarizes current analytical methods, describes the different sources of animal fibers and their biomolecular characteristics and methods of analysis, and finally presents the main applications of proteomics to historical clothing.

The Effect of Fermentation Bran and Chitosan in Ration to Percentage of Tegal Duck Digestive Tract Weight

Duck productivity is largely determined by the optimization of bodily functions. The food consumed greatly determines the development of digestive organs and internal organs of livestock. Digestive organs that are well developed and function optimally will be very decisive in turning feed into meat and eggs. Chitosan is a crustacean waste product known as animal fiber and is antimicrobial. Whereas fermented bran contains natural fiber rich in nutrients and is hypocholesterol. The aim of the study was to look at the role of chitosan and bran fermented on the weight percentage of digestive organs of ducks. The study used a completely randomized design (CRD) with 4 treatments and 5 replications. Each test consists of 2 ducks as a unit of experiment. The treatment is R0 = 45% corn + 35% concentrate + 20% bran without fermentation, R1 = 45% corn + 35% concentrate + 20% fermented bran, R2 = 45% corn + 35% concentrate + 19.5% fermented bran + 0.5% chitosan and R3 = 45% corn + 35% concentrate + 17.5% fermented + 2.5% chitosan bran. The variable measured is the weight percentage of the digestive organs (gizzard, small intestine and pancreas) in ducks. Data was processed using SAS Windows 16. The results showed that the administration of fermented chitosan and bran gave an average percentage of gizzard weight (ventriculus) and pancreatic weight percentage was not significantly different between treatments (P> 0.05), while treatment R1 (20% fermented bran) It was shown that the percentage of small intestine weight was higher (31.85%) than control R0.

Investigation of a novel automatic micro image-based method for the recognition of animal fibers based on Wavelet and Markov Random Field

In the analysis of fiber recognition, the challenge lies in the texture feature extraction. The main aim of this paper is to present a novel texture feature analysis method based on wavelet multi-scale analysis to fully extract texture features of microscopic images resulting in better recognition of similar animal fibers. Thousands of three kinds of similar fiber images including cashmere, sheep wool and goat hair were captured by the optical microscope and the digital camera. They were pre-processed to obtain the enhanced images with background removed. Then the pretreated fiber images were decomposed by 3-layer wavelet transform, four sub-images under the third-layer wavelet decomposition scale were analyzed by Gauss Markov Random Field (GMRF) model and their model parameters were obtained. Through the difference analysis of different kinds of fibers, two model parameters were selected from each sub-image to generate an 8-dimensional feature vectors, which was used to describe the fiber images. The parameters, which were extracted from 1000 images of each kind of fiber, were copied three times and randomly arranged to generate the final data sets. Finally, the data sets were processed by 10-times cross validation method as the training set and testing set of support vector machine (SVM). Ten different recognition rates could be obtained through the experiment, and the mean value was used as the final recognition accuracy of wool and cashmere fibers. The experimental results indicated that the method had a great recognition rate with 90.07% and the performance was robust. It verifies that the method based on wavelet multi-scale analysis is effective for the recognition of similar fibers.

Fibrous pore structure of silk fabric, cattle leather and wallpaper base paper and their adsorption properties

In recent years, encapsulation of fragrances and flavors in nanostructured matrices as well as related aromatic finishing techniques have emerged as promising means for achieving significant improvement of long-term release of flavor essence; therefore, understanding the interaction mechanism between nanocarriers and substrates is of vital importance for the application of fragrance nanotechnologies. In this work, the morphology, pore structure and pore size distribution of three kinds of animal and plant fiber materials were studied by taking silk fabric, cattle leather and wallpaper base paper as objects. Then, we investigated the adsorption property of the abovementioned fibrous substrates utilizing silica nanoparticles with different diameters as a simple model carrier. The results demonstrated that the adhesion strength and distribution of nanoparticles on the substrate are heavily dependent on their own size as well as on the fiber nature and the pore structure. Silica particles with a diameter of 20 nm can be strongly adsorbed on the fiber surface. For larger particles, such as 100, 500 and 1000 nm in diameters, they tend to be embedded in the gaps of the fiber or attached to the edge of the gaps. The preliminary studies could provide theoretical support for the design of fragrance-loaded nanoparticles and the development of long-lasting aromatic products.