Non-linear prediction model for egg production of quails the tropics with methionine supplementation

This study aimed to predict the egg production of quails receiving methionine supplementation. Two hundred and four quails were divided into two treatment diets, and six replicates with 17 quails each. The treatment diets were control (P0) and 0.12% methionine supplementation (P1). Egg production data were collected for eleven weeks, and a T-test was performed. Next, the data was plotted to get the actual egg production curve. We used a logistic regression model to predict the egg production pattern and calculated the model’s fitness with the coefficient of determination (R2). The results showed that methionine supplementation increased egg production by 9.43% (p<0.01). Based on the actual production curve, the increase in initial production to peak production of P1 was slower than P0, but P1 had a higher egg production than P0. The logistic model predicts that peak production of P1 was higher than P0 (62.74% vs. 56.79%), although the production rate of P1 was lower than P0 (0.21 vs. 0.36). In addition, the accuracy of both P0 and P1 models was 0.88 and 0.92, respectively. Thus, the logistic model can predict quail egg production in the tropics due to diet modification with high accuracy.

Fitness of logistics model for predicting quails egg production reared in a tropical environment with dietary betaine supplementation

Betaine is a methyl group donor and organic osmolyte, optimizing quail’s performance, particularly in a tropical environment. This study determined the fitness of the logistic model to predict the quail egg production with dietary betaine supplementation. Two hundred and four quails were divided into two dietary treatments, and six replicates with 17 quails each. The treatment diets were control (CTR) and 0.12% betaine supplementation (BET). Egg production data were collected for eleven weeks, and a T-test was performed. Next, the data is plotted to get the actual egg production curve. The fit of the logistic model is calculated according to the coefficient of determination (R2). Quail that received betaine supplementation produced more eggs than control (P<0.05). The actual egg production curve shows the effect of betaine supplementation seen after the fourth week. The logistic model predicts CTR to reach peak production faster than BET but to have lower peak production than BET (56.63% vs. 63.56%). Prediction of egg production both CTR and BET showed high accuracy with a relatively high R2 (0.88; CTR and 0.87; BET). Thus, the logistic model accurately predicted quails egg production reared in a tropical environment with betaine supplementation.

KORELASI PRODUKSI SUSU DENGAN BCS SAPI FRIESIAN HOLSTEIN LAKTASI PERTAMA DI BBPTU-HPT BATURRADEN

The purpose of this study was to determine the relationship between milk production of PFH dairy cows with BCS at the first lactation at BBPTU HPT Baturraden. The study was conducted from March 20 to April 20 2018, with research material consisting of 250 production data records and 250 BCS data records that were corrected in lactation months 1 to 10 originating from BBPTU HPT Baturraden. Data analysis shows that milk production has a close relationship with lactation month, the results are shown by the equation y = -0.1223x2 + 0.6068x + 13.493 with R2 of 0.97. These results are reflected in the milk production curve which shows in the first month to the third month that there is an increase in milk production, with peak production being reached in the third month. Average peak milk production is 14.74 liters / head / day and average milk production Daily 12.12 liters / head / day. The results of the BCS analysis show that BCS has a close relationship with the lactation month, the results are shown by the equation y = 2.9133 + 0.0132x2 + 0.0365x shown with R2 of 0.95. The results on the BCS graph show that BCS is increasing as the lactation period progresses, the largest average BCS is obtained 3.79 in the 10th month. The relationship between milk production and BCS based on the analysis shows the equation y = -3,9224x2 + 18,894x - 7,6087, indicated by an R2 of 0.98.

Defense and Immune Response to Severe Acute Respiratory Syndrome Coronavirus 2 in COVID-19 Patients: A Narrative Review

In the present review, we aim to determine the defense methods, assessment the profile of acute antibodies response in COVID-19 patients, and to provide accurate date for the usage of antibody test in clinical practice. After exposure to COVID-19, the immune system is responded in different ways and particles in different concentrations according on period of infection graduation. While the main response of immune system includes IgM, IgG and IgA antibodies, and, the most serological diagnosis tests and researches were found that “≥4- fold increase in the IgG titer” is suitable for a majority of COVID-19 patients and after three months is disappeared. IgM and IgG antibodies are the best defense methods. Serologic test method is helpful for the diagnosis of SARSCoV- 2 infection in suspects and close contacts. Antibodies determination in SARS Cov-2 is essential for COVID-19 assessment, treatment and vaccine development. In conclusion, we noticed in most of cases the production of IgM is started after 72 hrs. Of symptoms appears and peak up the production curve in 20-22 days then is disappeared in day 56 of infection. While, the production of IgG is started after 8 days of infection and peak up the production curve in 17-19 day then disappeared in day 80 of infection, but IgA production is started in 5th day of infection.

ANALISIS UJI PRODUKSI DENGAN ORIFICE PLATE PADA SUMUR J-97 LAPANGAN PANAS BUMI “KYU”

<em>In a study entitled "Analysis of Production Tests with Orifice Plate on the J-97 Well KYU Geothermal Field" will discuss the production test. Geothermal production tests are conducted to determine the potential of the production capacity of a well at different wellhead pressures so that the value of the mass flow rate and the well production curve is obtained. J-97 well is one-phase steam well, so the production test method used is to use the orifice plate. The pressure data read by the orifice plate is then converted to a mass flow rate. Calculating the mass flow rate can use the British Standard 1042 method. In the production test to obtain the final result in the form of a production curve, the gas deliverability equation can be used. The method used in the S-87 well is Flow After Flow Test (Back pressure Test). The final result of the curve shows a decrease in the production line calculated using the British Standard 1042 method..</em>