scholarly journals DETECTION OF THE PRESENCE OF MICROORGANISMS DURING PRODUCTION OF PLASTERBOARD

2021 ◽  
Vol 30 ◽  
pp. 93-97
Author(s):  
Hana Sekavová ◽  
Zdeněk Prošek ◽  
Pavla Ryparová
Keyword(s):  
Production Process ◽  
Bacterial Contamination ◽  
Suitable Modification

This article is focused on detection microorganisms appearing during production of gypsum plasterboards. The research is carried out within the project TAČR ZÉTA TJ02000235 Sádrokarton se zvýšenou odolností proti bilogické degradaci (Gypsum plasterboard with increased biodegradation resistance). This article shows first part of this issue what was detection of the most critical place of production, where is the highest risk of bacterial contamination and it open the area to find suitable modification of production process or recipes of gypsum plasterboards.

scholarly journals Production process development of Nipa bowl from Nipa palm (Nypa fruticans Wurmb.) waste by using solar dryer cabinet for sustainability of Palian river basin community

2019 ◽  
Vol 15 (4) ◽  
pp. 593-596
Author(s):  
Noppadon Podkumnerd ◽  
Supranee Wunsri ◽  
Sujint Khairin
Keyword(s):  
Production Process ◽  
River Basin ◽  
Bacterial Contamination ◽  
Process Development ◽  
Drying Methods ◽  
Drying Process ◽  
Nypa Fruticans ◽  
Solar Dryer ◽  
Nipa Palm ◽  
Palm Leaf

The objective of this research was to develop the process for the production of Nipa bowls from Nipa palm (Nypa fruticans Wurmb.) waste by using solar energy. Two types of solar dryer were investigated, (1) solar dryer cabinet (SDC) and (2) solar dryer cabinet coupled with heater (SDCH) and were compared to the traditional sun dryer (SD) method. The results demonstrated that the use of SDCH could reduce the humidity of the Nipa leaves to 15.23 ± 0.78% within 2 hours. This result was statistically significant at 95% confident compared to those results obtained from SDC (49.91 ± 0.78%) and SD (38.66 ± 0.21%). The dried leaves obtained from the three drying methods were tested for bacterial contamination. For SD, the maximum bacteria contamination was 95,000 ± 40,414 cfu/piece which was higher than SDC (480 ± 173 cfu/piece) and SDCH (463 ± 112 cfu/piece) methods. The SDC and SDCH techniques were implemented at Palian river basin community (Ban Na Yod Tong Nipa Palm Leaf Handicraft) in Wang Won Sub-District, Kantang District,Trang Province, Thailand. These techniques could enhance the drying process of Nipa leaves and thus increase the production of Nipa bowls 3.5 times reducing Nipa waste up to 1.83 tons. The villagers could produce approximately 183,000 bowls/year generating an income of more than 55,800 USD for 60 families.

scholarly journals Bacterial DNA Diversity among Clear and Cloudy Sakes, and Sake-kasu

2020 ◽  
Vol 13 (1) ◽  
pp. 74-82
Author(s):  
Momoka Terasaki ◽  
Hiromi Nishida
Keyword(s):  
Production Process ◽  
Dna Sequences ◽  
Bacterial Contamination ◽  
Yeast Cells ◽  
Bacterial Cells ◽  
Bacterial Dna ◽  
Rdna Sequences ◽  
Dna Diversity ◽  
16S Rdna Sequences ◽  
The Difference

Background: The traditional Japanese alcoholic drink, sake, is classified into two types: those that contain sediment produced during the production process (cloudy sakes) and those that do not contain such sediment (clear sakes). Leftover pressed sediment from the sake production process, sake-kasu (sake cake or sake lees), is commercially available and is highly nutritious for humans. Objective: The purpose of this study was to determine the difference among component bacterial DNA sequences of clear and cloudy sakes, and sake-kasu. Methods: We compared the 16S rDNA sequences from 44 samples of clear sake, 3 samples of cloudy sake, and 11 samples of sake-kasu. Results: The DNA sequences were divided into three major clusters; however, sequences in sake-kasu were located in just one cluster forming two lineages. The microbial diversity in sake-kasu was lower than that in clear and cloudy sakes, which may be because some of the contaminating bacterial cells do not lyse during the production process and remain intact, along with yeast cells, in sake-kasu. Conclusion: Bacterial DNA frequently detected in sake samples was from environmental bacterial contamination that occurs early in the sake production process. Contaminating bacteria are usually killed by the ethanol produced as the sake yeast grows; after which, if bacteria lyse, the bacterial DNA is released into the sake solution. However, if the bacterial cells do not lyse, they will precipitate toward the sediment. Thus, there is bacterial DNA diversity in clear and cloudy sake, but less diversity in sake-kasu.

Optimization of the production process of special purpose pasta with the addition of carrots and pectin

2019 ◽  
Vol 28 (9) ◽  
pp. 50-53
Author(s):  
N.N. Martynov ◽  
◽  
G.A. Sidorenko ◽  
G.B. Zinyukhin ◽  
E.Sh. Maneeva ◽  
...  
Keyword(s):  
Production Process

IMPLEMENTASI JOB ORDER COSTING METHOD DALAM PERHITUNGAN HARGA POKOK PRODUKSI MAP

2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita
Keyword(s):  
Production Process ◽  
Quantitative Data ◽  
Production Cost ◽  
Qualitative Data ◽  
Cost Data ◽  
Method Calculation ◽  
Cost Of Production ◽  
The Right ◽  
The Cost

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method

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