scholarly journals Diversity of milk traits in 25 goat breeds

2022 ◽  
Vol 335 ◽  
pp. 00009
Author(s):  
Ferdy Saputra ◽  
Anneke Anggraeni
Keyword(s):  
Cluster Analysis ◽  
Protein Content ◽  
Statistical Approach ◽  
Fat Content ◽  
High Fat ◽  
Milk Traits ◽  
Preference Analysis ◽  
Average Linkage ◽  
Linkage Cluster ◽  
Relationship Of

Goats are livestock that is mostly raised by small farmers in Indonesia because they are easier to raise. Apart from having the potential to become meat, several breeds of which are kept as milk-purpose. Milk traits of each breed differ from one another. Therefore, this study tried to observe genetic differences of 25 goat breeds with statistical approach. Information about milk traits from 25 goat breeds is obtained from published journal. Multidimensional preference analysis and average linkage cluster analysis were performed using SAS 9.4 to determine the differences in goat breeds from three traits, namely milk yield, fat content, and protein content. Multidimensional preference analysis was able to see the advantages of breeds from the three observed traits. Goat breeds with superior milk yields are Saanen, Camosciata delle Alpi, and Charmoisée. Sarda Primitiva, Sarda, Etawah Grade have high fat content in milk. In addition, Arsi-Bale and Somali have high protein content. Average linkage cluster analysis is able to observe the genetic relationship of goat breeds based on three traits. According to average linkage cluster analysis, we found four clusters for goat breeds in this study. With existing statistical approaches, we can evaluate genetic diversity in milk traits.

scholarly journals MOLECULAR GENODIAGNOSTICS OF PRODUCER BULLS BY ECONOMICALLY VALUABLE CHARACTERISTICS

2021 ◽  
Vol 247 (3) ◽  
pp. 75-79
Author(s):  
F.F. Zinnatov ◽  
◽  
Keyword(s):  
Gene Polymorphism ◽  
Protein Content ◽  
Milk Yield ◽  
Fat Content ◽  
Mass Yield ◽  
Milk Productivity ◽  
Dgat1 Gene ◽  
Economically Valuable Traits ◽  
Relationship Of ◽  
The Relationship

Based on the results of the analysis of the relationship between the DGAT1 gene polymorphism and economically valuable traits, it was concluded that animals with the DGAT1KK genotype have the highest milk yield and fat content. When analyzing the relationship of CSN3 gene polymorphism with milk productivity, it was found that higher rates are characteristic of mothers cows with a homozygous CSN3BB genotype. Animals of this group have an advantage, in comparison with the AB and AA genotypes, in milk yield, protein content, mass yield of fat and protein. When studying the data of the relationship between the LGB gene polymorphism and economically valuable traits, it was concluded that animals with the homozygous LGBBB genotype have the highest milk yield, fat, protein content, mass fat and protein yield.

Infrared analyzers for breast milk analysis: fat levels can influence the accuracy of protein measurements

2017 ◽  
Vol 55 (12) ◽  
Author(s):  
Celia Kwan ◽  
Gerhard Fusch ◽  
Aldin Bahonjic ◽  
Niels Rochow ◽  
Christoph Fusch
Keyword(s):  
Breast Milk ◽  
Protein Content ◽  
Neonatal Intensive Care ◽  
Near Infrared ◽  
Fat Content ◽  
Milk Analysis ◽  
High Fat ◽  
Before And After ◽  
The Matrix ◽  
Calibration Algorithm

Abstract:Background:Currently, there is a growing interest in lacto-engineering in the neonatal intensive care unit, using infrared milk analyzers to rapidly measure the macronutrient content in breast milk before processing and feeding it to preterm infants. However, there is an overlap in the spectral information of different macronutrients, so they can potentially impact the robustness of the measurement. In this study, we investigate whether the measurement of protein is dependent on the levels of fat present while using an infrared milk analyzer.Methods:Breast milk samples (n=25) were measured for fat and protein content before and after being completely defatted by centrifugation, using chemical reference methods and near-infrared milk analyzer (Unity SpectraStar) with two different calibration algorithms provided by the manufacturer (released 2009 and 2015).Results:While the protein content remained unchanged, as measured by elemental analysis, measurements by infrared milk analyzer show a difference in protein measurements dependent on fat content; high fat content can lead to falsely high protein content. This difference is less pronounced when measured using the more recent calibration algorithm.Conclusions:Milk analyzer users must be cautious of their devices’ measurements, especially if they are changing the matrix of breast milk using more advanced lacto-engineering.

scholarly journals TECHNOLOGICAL EVALUATION OF SOYBEAN SEED QUALITY DEPENDING ON THE VARIETY

2020 ◽  
Vol 2 ◽  
pp. 32-37
Author(s):  
V. V. Liubych
Keyword(s):  
Protein Content ◽  
Seed Yield ◽  
Soybean Seed ◽  
Weather Conditions ◽  
Fat Content ◽  
High Protein ◽  
Protein Yield ◽  
Soybean Variety ◽  
High Fat ◽  
Fat Yield

The biochemical component (protein content and fat content) of soybean seed, yield and fat and protein yield significantly depends on weather conditions and variety. It was found that the protein content in soybean seed, on average over two years of research on new varieties can vary from 36.1 to 44.4 %. Khana, Lenka and Alaska varieties have the highest protein content in soybean seed – 43.4–44.4 %. Protein content significantly depends on the weather conditions of the study year. Thus, soybean varieties of Kofu, Siberia, Volta, Asuka, Arisa, Khana, Lenka and Alaska, grown in 2020, have this figure 10–19 % higher than in 2019. In the seeds of Nordica, Carra, Kyoto, Ezra, Amadeus and Taurus soybean varieties, the protein content is 4–10 % lower. On average, over two years of research, the fat content in soybean seeds varies from 18.9 to 21.7 % depending on the variety. Only three out of 14 soybean varieties have the fat content ≤ 20.0 % – Khana, Alaska, Arisa. In seeds of other varieties, this figure is ≥ 20 %. Weather conditions reduce the fat content in the seeds by 7–20 % depending on the variety. Studies have shown that soybean seed yields vary significantly depending on the soybean variety. Thus, on average over two years of research, this figure varies from 1.30 t/ha in Amadeus variety to 1.88 t/ha in Siberia one. The highest yields (≥ 1.70 t/ha) were formed by Arisa, Volta and Siberia varieties. However, this figure varies greatly depending on the weather conditions of the study year. Thus, in a more favourable 2019, the yield is from 1.65 to 2.41 t/ ha, depending on the soybean variety. Moisture deficiency and small reserves of moisture in the deeper layers of the soil reduce seed yield from 0.95 to 1.35 t/ha or by 1.7–3.7 times, depending on the soybean variety. Two soybean varieties (Arisa, Siberia) have the highest protein yield at the level of 706–721 kg/ha. The highest fat yield was obtained by Siberia growing – 415 kg/ha. Under the conditions of the Right Bank forest-steppe, for stable formation of high protein yield in different weather conditions, it is necessary to grow Arisa soybean variety which has high protein content and high seed yield, and Alaska variety which has high protein content in seeds. In addition, in the best hydration years it is able to form a high fat yield. Volta, Asuka, Khana and Lenka varieties should be grown in years with sufficient moisture, as they provide the highest protein yield. These varieties should also be grown to obtain a high fat yield under the best moisture conditions. Siberia soybean should be used to produce fat in different weather conditions

Gene LPL, STAT5 and AGPAT6 Polymorphisms Relationship with Goat Milk Traits

2020 ◽  
Author(s):  
B. Šlyžienë ◽  
L. Anskienë ◽  
E. Šlyžius ◽  
R. Bižienë ◽  
V. Juozaitienë
Keyword(s):  
The Netherlands ◽  
Protein Content ◽  
Milk Yield ◽  
Milk Fat ◽  
Goat Milk ◽  
Fat Content ◽  
Gene Analysis ◽  
Nucleotide Polymorphisms ◽  
Milk Traits ◽  
Result Analysis

Background: Several single nucleotide polymorphisms had been detected in goats and for the researchers it is important to reveal candidate genes with substantial effects on the traits of economic importance. The aim of this study was to investigate the association between LPL, STAT5 and AGPAT6 gene polymorphisms and milk traits of goats. Methods: We investigated about 204 goats, four different breeds (Czech White Shorthaired, Saanen, Anglo Nubian, Alpine) and two crossbreeds (Saanen and Alpine, Saanen and Anglo Nubian). The milk samples were analysed using spectrophotometers LactoScope 550 and LactoScope FTIR (Delta Instruments, the Netherlands). The somatic cell count (SCC) in milk was determined by flow cytometry method using the Somascope CA-3A4 (Delta Instruments, the Netherlands). Variations of the goat AGPAT6, STAT5, LPL genes were detected by PCR-RFLP method. Result: Analysis of AGPAT6 gene revealed that goats with GC genotype had higher milk yield, fat content and lactose content; goats with CG genotype had higher protein content. STAT5 gene analysis showed that goats with CT genotype had higher milk yield; goats with CC genotype had higher fat content and lactose content; goats with TT genotype had higher protein and urea content and also SCC. According to LPL gene analysis, goats with CC genotype had higher milk yield while goats with GG genotype had higher fat and protein content. The highest milk yield was estimated in Saanen and Alpine crossbreed goats while the highest milk fat and protein content was estimated in Anglo Nubian goats.

Sales Forecast for Garment Companies with Cluster Analysis and Modified Neural Networks

2011 ◽  
Vol 127 ◽  
pp. 490-495
Author(s):  
Li Yu ◽  
Yun Chen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Cluster Analysis ◽  
Sales Forecast ◽  
The Neural Network ◽  
Linkage Cluster ◽  
Relationship Of ◽  
Marketing Resource Allocation ◽  
The Relationship

For the companies of the garment industry, managers often dedicate their efforts to forecast the sales accurately while making decisions for marketing resource allocation and scheduling. Based on the historical database, this paper constructs a method to investigate the relationship of the relating factors and sales values. The proposed method combines the cluster analysis and modified neural networks to fulfill the sales forecast task. Firstly, the average linkage cluster algorithm is applied to cluster similar sales values. Secondly, a modified neural network is used to investigate the mapping relationship between those influencing factors and the sales clusters. The method employs a self-adjust mechanism to determine the structure of the neural network. The effectiveness of the proposed method is illustrated with a case study of a garment company in Shanghai.

Personality Types in Data from California Psychological Inventory as Defined by Cluster Analysis

1981 ◽  
Vol 48 (1) ◽  
pp. 115-118 ◽  
Author(s):  
Maurice Lorr ◽  
Gary K. Burger
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Personality Types ◽  
California Psychological Inventory ◽  
Standard Score ◽  
Average Linkage ◽  
Cluster Analytic ◽  
Linkage Cluster ◽  
Psychological Inventory

The study compared the three personality types delineated by Burger and Cross by obverse factor analysis with those disclosed by an average linkage cluster analytic technique. The data were from three subsamples of 85 men who completed the California Psychological Inventory for Burger and Cross. The standard score profiles within each sample were intercorrelated and then cluster analyzed. Four profile types were replicated across the three subsamples. Two of the types, labeled antisocial and well-adjusted, corresponded fairly closely to the Burger-Cross types. There were differences in the number of types generated, in the proportion of individuals classified, and in the profile shapes.

scholarly journals Einfluss systematischer Umwelteffekte auf die Milchleistungsmerkmale bei Bunten Deutschen Edelziegen

2004 ◽  
Vol 47 (3) ◽  
pp. 275-285
Author(s):  
D. Bömkes ◽  
H. Hamann ◽  
O. Distl
Keyword(s):  
Somatic Cell ◽  
Protein Content ◽  
Milk Yield ◽  
Significant Influence ◽  
Milk Fat ◽  
Fixed Effects ◽  
Fat Content ◽  
Protein Yield ◽  
Production Traits ◽  
Milk Traits

Abstract. Title of the paper: Influence of systematic environmental effects on milk performance traits in German Improved Fawn The objectives of this study were to analyse the influence of fixed effects on milk traits of German Improved Fawn. The analysis was based on 27,778 test day records of 1,848 German Improved Fawn with 3,574 lactation records. The milk records were sampled between 1988 and 2002 from 229 flocks in Lower Saxony, Saxony and Baden-Wuerttemberg. The average daily milk yield was 2.87 ± 1.20 kg with a fat content of 3.08 ± 0.54% and a protein content of 3.38 ± 0.95%. Somatic cell count (SCC) was transformed into somatic cell score (SCS). Mean SCS was 5.49 ± 1.93. The average lactation length was 234.1 ± 76.4 days. The analysis of variance showed a significant influence of lactation number, stage of lactation, year of lambing and month of lambing on all analysed milk production traits. Milk yield was highest in the fourth lactation number and fat as well as protein content in the 7th to 13th lactation number. Litter size had a significant influence on milk and fat yield and on fat and protein content. The region significantly influenced protein yield and fat and protein content of German Improved Fawn but had no effect on milk and protein yield and SCS. Animals from Baden-Wuerttemberg reached the highest milk protein content but the lowest milk fat content.

scholarly journals Variability and heritability of milk traits of Holstein-Frisian bull dams and their progeny

Genetika ◽  
2018 ◽  
Vol 50 (1) ◽  
pp. 243-251
Author(s):  
Marina Lazarevic ◽  
Dragan Stanojevic ◽  
Vladan Bogdanovic ◽  
Vlada Pantelic ◽  
Nevena Maksimovic ◽  
...  
Keyword(s):  
Protein Content ◽  
Milk Yield ◽  
Milk Fat ◽  
Fat Content ◽  
Protein Yield ◽  
Milk Traits ◽  
Holstein Friesian ◽  
Fat Yield ◽  
Calving Season ◽  
The Impact

The research was performed on Holstein-Friesian and Black and White bull dams reared on five farms of Agricultural Corporation of Belgrade - PKB. The study included 575 lactations of cows selected as bull dams and their progeny calved in the period from 2007 - 2014 and represent progeny of 24 bulls. The following dairy traits were analysed in a standard lactation (305 days): milk yield (kg) - MY, milk fat content (%) - % MF, milk fat yield (kg) - MFY, protein content (%) - % PC and protein yield (kg) - PY. Holstein-Friesian bull dams and their progeny, in standard lactation, produced on average 9239.84 ? 1607.64 kg of milk, with a milk fat content of 3.44 ? 0.20 and protein content of 3.21 ? 0.12. The impact of bull - sire, year of birth, lactation order, farm, year and calving season was present at different levels of statistical significance on yield traits, while the genetic group had no influence on any of the milk traits. Bull - sire, year of birth, lactation order and calving season did not influence the variability of milk fat and protein content. Heritability of observed milk traits was medium to low. The content of milk fat and protein had the lowest values of heritability, 0.014, and 0.024, respectively. The heritability of milk yield, milk fat yield and protein yield was 0.293, 0.319 and 0.273, respectively.

Non-Fasting Factor VII Coagulant Activity (FVII:C) Increased by High-Fat Diet

1994 ◽  
Vol 71 (06) ◽  
pp. 755-758 ◽  
Author(s):  
E M Bladbjerg ◽  
P Marckmann ◽  
B Sandström ◽  
J Jespersen
Keyword(s):  
High Fat Diet ◽  
Fat Content ◽  
Factor Vii ◽  
Amidolytic Activity ◽  
High Fat ◽  
Low Fat Diet ◽  
Increased Risk ◽  
Coagulant Activity ◽  
High Fat Diets ◽  
Fat Diets

SummaryPreliminary observations have suggested that non-fasting factor VII coagulant activity (FVII:C) may be related to the dietary fat content. To confirm this, we performed a randomised cross-over study. Seventeen young volunteers were served 2 controlled isoenergetic diets differing in fat content (20% or 50% of energy). The 2 diets were served on 2 consecutive days. Blood samples were collected at 8.00 h, 16.30 h and 19.30 h, and analysed for triglycerides, FVII coagulant activity using human (FVII:C) or bovine thromboplastin (FVII:Bt), and FVII amidolytic activity (FVIPAm). The ratio FVII:Bt/FVII:Am (a measure of FVII activation) increased from fasting levels on both diets, but most markedly on the high-fat diet. In contrast, FVII: Am (a measure of FVII protein) tended to decrease from fasting levels on both diets. FVII:C rose from fasting levels on the high-fat diet, but not on the low-fat diet. The findings suggest that high-fat diets increase non-fasting FVII:C, and consequently may be associated with increased risk of thrombosis.

Sign in / Sign up

Export Citation Format

Share Document