scholarly journals Examination of a Sigmoid Shape Composition for BMI Fluctuation and Fat Percentage

2021 ◽  
Vol 9 (3) ◽  
pp. 60
Author(s):  
Katsunori Fujii ◽  
Nozomi Tanaka ◽  
Yuki Takeyama ◽  
Tohru Ishigaki
Keyword(s):  
Fat Percentage ◽  
Sigmoid Shape

Whey as an indicator for standardizing cow’s milk fat percentage for cheese production

2020 ◽  
pp. 33-39
Author(s):  
Prof. Asoc. Dr. Shurki MAXHUNI ◽  
Prof.Asiss.Dr.Nerimane BAJRAKTARI
Keyword(s):  
Milk Fat ◽  
Economic Indicator ◽  
Peculiar Feature ◽  
Cow’S Milk ◽  
Fat Percentage ◽  
Cow's Milk ◽  
Physical Chemical ◽  
Heated Milk ◽  
Sweet Whey ◽  
Acid Whey

The dairy industry seems to have convinced the food industry that whey is a miracle product. The list of supposed benefits it gives to food is as long as your arm. Some of the benefits may be real. Whey is the liquid remaining after milk has been curdled and strained. It is a by-product of the manufacture of cheese or casein and has several commercial uses. To produce cheese, rennet or an edible acid is added to heated milk. This makes the milk coagulate or curdle, separating the milk solids (curds) from the liquid whey. Sweet whey is the byproduct of rennet-coagulated cheese and acid whey (also called sour whey) is the byproduct of acid-coagulated cheese. Sweet whey has a pH greater than or equal to 5.6, acid whey has a pH less than or equal to 5.1. Whey is also a great way to add sweetness to a product without having to list sugar as an ingredient as whey contains up to 75% lactose. And it sounds healthy. This study is done to research the examinations for the production of mozzarella cheese from Cow’s milk, after research and analyses of a physical-chemical peculiar feature of whey from coagulum. We have followed the processes from the drying of whey from the coagulum analyzer's physical-chemical peculiar feature. We carried out three experiments. For every experiment, we took three patterns and analyzed the physical-chemical. The calculation was appraised statistically. This paper deals with the research of% of whey fat during the process of milk production from standardized to non-standardized milk. Where% of whey fat should be an economic indicator for standardizing milk for dairy production.

Effect of Breed and Some Non - Genetic Factors on Milk Production and Some Proportions of Its Chemical Components in Two Breeds of Local Sheep

2020 ◽  
Vol 10 (1) ◽  
pp. 227-231
Author(s):  
Rahman Hussein AL-Qasimi ◽  
Shatha Mohammed Abbas ◽  
Allawi L.D. AL-Khauzai
Keyword(s):  
Milk Production ◽  
Genetic Factors ◽  
Chemical Components ◽  
Lactation Period ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Awassi Sheep ◽  
Total Milk ◽  
Milk Components

The study was carried out on 19 ewes of local Awassi sheep and 12ewes local Arabi sheep in the Al-kafeel sheep station Karbala, to determine the effect of breed and some non-genetic factors such as (sex of the lamb, type of birth, age and weight of ewes at birth) on daily and total milk production and lactation period and some of milk components (fat, protein and lactose). The results showed that a significant effect (P <0.05) of the breed on milk production traits where Awassi sheep recorded the highest mean (0.91 kg , 101.63 kg , 104.86 day) compared to the Arabi sheep she was means (0.77 kg , 88.15 kg , 99.15 day) respectively. As well as in proportions of milk components with mean( 5.1 , 4.90 , 5.51) % respectively compared to the Arabi sheep (4.70 . 4.20 . 4.89) ewes with male lambs also exceeded superior ewes with female lambs in daily and total milk production and the lactation period the sex of the lamb did not affect the proportions of milk components the weight of the ewes had a significant effect (P <0.05) in milk production attributes with superior weight of ewes on lower ewes and did not affect the proportions of milk ingredients except for lactose. The type of birth and the age of the ewes did not have a significant effect in all the studied traits except for the superiority (P<0.05) of young ewes on age ewes in the fat percentage of milk.

Subjective Sleep Debt Is Correlated with Body Fat Percentage Independent of Sleep Duration

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1675-P
Author(s):  
XIAO TAN ◽  
CHRISTIAN BENEDICT
Keyword(s):  
Sleep Duration ◽  
Body Fat ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Subjective Sleep ◽  
Sleep Debt

Effects of selection for ultrasound intramuscular fat percentage in Angus bulls on carcass traits of progeny

2002 ◽  
Vol 80 (8) ◽  
pp. 2017 ◽  
Author(s):  
R. L. Sapp ◽  
J. K. Bertrand ◽  
T. D. Pringle ◽  
D. E. Wilson
Keyword(s):  
Carcass Traits ◽  
Intramuscular Fat ◽  
Fat Percentage ◽  
Selection For

Accuracy and sensitivity of different Bayesian methods for genomic prediction using simulation and real data

2020 ◽  
Vol 19 (3) ◽  
Author(s):  
Saheb Foroutaifar
Keyword(s):  
Data Analysis ◽  
Bayesian Methods ◽  
Milk Fat ◽  
Prediction Accuracy ◽  
Real Data ◽  
Fat Percentage ◽  
Real Data Analysis ◽  
Wide Range ◽  
High Heritability ◽  
Qtl Effects

AbstractThe main objectives of this study were to compare the prediction accuracy of different Bayesian methods for traits with a wide range of genetic architecture using simulation and real data and to assess the sensitivity of these methods to the violation of their assumptions. For the simulation study, different scenarios were implemented based on two traits with low or high heritability and different numbers of QTL and the distribution of their effects. For real data analysis, a German Holstein dataset for milk fat percentage, milk yield, and somatic cell score was used. The simulation results showed that, with the exception of the Bayes R, the other methods were sensitive to changes in the number of QTLs and distribution of QTL effects. Having a distribution of QTL effects, similar to what different Bayesian methods assume for estimating marker effects, did not improve their prediction accuracy. The Bayes B method gave higher or equal accuracy rather than the rest. The real data analysis showed that similar to scenarios with a large number of QTLs in the simulation, there was no difference between the accuracies of the different methods for any of the traits.

Comparison of the Effect of Soy protein and Whey protein on Body Composition: A Meta-Analysis of Randomized Clinical Trials

2021 ◽  
pp. 1-27
Author(s):  
Masoome Piri Damaghi ◽  
Atieh Mirzababaei ◽  
Sajjad Moradi ◽  
Elnaz Daneshzad ◽  
Atefeh Tavakoli ◽  
...  
Keyword(s):  
Body Composition ◽  
Whey Protein ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Soy Protein ◽  
Protein Supplementation ◽  
Body Fat Percentage ◽  
Fat Percentage

Abstract Background: Essential amino acids (EAAs) promote the process of regulating muscle synthesis. Thus, whey protein that contains higher amounts of EAA can have a considerable effect on modifying muscle synthesis. However, there is insufficient evidence regarding the effect of soy and whey protein supplementation on body composition. Thus, we sought to perform a meta-analysis of published Randomized Clinical Trials that examined the effect of whey protein supplementation and soy protein supplementation on body composition (lean body mass, fat mass, body mass and body fat percentage) in adults. Methods: We searched PubMed, Scopus, and Google Scholar, up to August 2020, for all relevant published articles assessing soy protein supplementation and whey protein supplementation on body composition parameters. We included all Randomized Clinical Trials that investigated the effect of whey protein supplementation and soy protein supplementation on body composition in adults. Pooled means and standard deviations (SD) were calculated using random-effects models. Subgroup analysis was applied to discern possible sources of heterogeneity. Results: After excluding non-relevant articles, 10 studies, with 596 participants, remained in this study. We found a significant increase in lean body mass after whey protein supplementation weighted mean difference (WMD: 0.91; 95% CI: 0.15, 1.67. P= 0.019). Subgroup analysis, for whey protein, indicated that there was a significant increase in lean body mass in individuals concomitant to exercise (WMD: 1.24; 95% CI: 0.47, 2.00; P= 0.001). There was a significant increase in lean body mass in individuals who received 12 or less weeks of whey protein (WMD: 1.91; 95% CI: 1.18, 2.63; P<0.0001). We observed no significant change between whey protein supplementation and body mass, fat mass, and body fat percentage. We found no significant change between soy protein supplementation and lean body mass, body mass, fat mass, and body fat percentage. Subgroup analysis for soy protein indicated there was a significant increase in lean body mass in individuals who supplemented for 12 or less weeks with soy protein (WMD: 1.48; 95% CI: 1.07, 1.89; P< 0.0001). Conclusion: Whey protein supplementation significantly improved body composition via increases in lean body mass, without influencing fat mass, body mass, and body fat percentage.

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