Pornchaloempong, Pimpen

Loading...
Thumbnail Image
Preferred name
Pornchaloempong, Pimpen
Alternative Name
Pornchaloempong, P.
Main Affiliation
Email
pimpen.po@kmitl.ac.th

Settings

Now showing 1 - 5 of 5
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Preliminary Life Cycle Analysis of Greenhouse Gas Emissions at Transportation Phase of a Beverage Drink for Green Logistics
    (2021-05-12)
    Koiwanit, Jarotwan
    ;
    Riensuwarn, Fonthong
    ;
    Palungpaiboon, Penpicha
    ;
    Pornchaloempong, Pimpen
    As the transportation sector is one of the main emitters of large quantities of pollutions to the atmosphere, industries have been trying to cope with this issue and launch many campaigns or projects to reduce air pollutions. In any industries around the world, an electric vehicle is a part of alternative transportation mode which has recently experienced considerable growth. The paper aims to evaluate energy consumption and greenhouse gas (GHG) emissions of the food sector for the entire life cycle and particularly focusing on green road transportation. The focus of the analysis covers the mango powder drink mix transportation, distribution, and disposal aspects, especially for road transportation. The observed results showed that the electric vehicles have emissions reduction potential and consequently showed low impacts in Global Warming Potential (GWP) impact category. The environmental impact assessment identified that the primary source of energy use and GHG emissions was the transportation process from Hong Keaw plantation to King Mongkut's Institute of Technology Ladkrabang (KMITL) (0.025 kgCO2eq).
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Effect of Environment Temperature and Relative Humidity on Thermal Emissivity: Study Case of Mango Fruit
    (2024-01-01)
    Sirisomboon, Panmanas
    ;
    Sripinyowanich Jongyingcharoen, Jiraporn
    ;
    Junto, Apiwat
    ;
    Phanomsophon, Thitima
    ;
    Dachoupakan Sirisomboon, Cheewanun
    This research was to study the effect of the environment condition during image captured including temperature and relative humidity in the packaging house of the mango exporting factory and in the orchard on the emissivity of mango fruit. The result showed that in the controlled environment of the packaging house in factory, the emissivity was increased (the mango emitted more energy) when the surface temperature was lower and the emissivity of mango is 0.71-0.84 and in the uncontrolled environment of open-air packaging yard in the mango orchard, the different transpiration rates of mango effected mainly by ambient temperature and relative humidity make the morning condition emissivity of 0.44-0.66 and the afternoon condition of 0.72-0.98. There was the effect of the different measured positions on the fruits where the physiology was different and the fluctuated environment in the latter condition made the wide range of emissivity of mangoes. This indicated the shortcoming of thermal imaging of horticultural product if the correct emissivity varied and difficult to set in the thermal camera setting, hence the inaccurate thermogram to be obtained.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Effects of low temperature drying processing on longan fruit
    (2018-08-14)
    Pongsuttiyakorn, Thadchapong
    ;
    Trusphimai, Pachareeporn
    ;
    Sooraksa, Pitikhate
    ;
    Pornchaloempong, Pimpen
    In this study, the single-stage drying in tray dryer at air temperatures of 40, 50, 60, 70 and 80°C is modelled and investigated. The longan fruits, E-dor variety, are peeled and seeded before testing. The drying rate is significantly influenced by the drying techniques and temperatures. Drying rats are initialized adjustment constant rate periods at 60 70 and 80°C. The rate of moisture removal is rapidly changed drastically during the falling rate period. The Midilli model with high R<sup>2</sup> and low χ<sup>2</sup> and RMSE is the most suitable model for predictability of longan drying. Variation rates of quality of the water activity, the shrinkage, and the browning index are also reported.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Processing feasibility and qualities of freeze dried mango powder for SME scale
    (2019-09-09)
    Mawilai, P.
    ;
    Chaloeichitratham, N.
    ;
    Pornchaloempong, P.
    This research studied the processing feasibility and quality of the premium mango powder 'Mahachanok' for SME business. Freeze-dried mango powder as alternative high quality mango powder. The frozen mango puree was thawed at 4°C for 12 hours. The freeze dry processes to freezing and vacuum drying product within a single chamber. The operation cycle included 3 main steps: First step was rapidly frozen with contact plate and air blast freezing at -50°C until core product temperature was -20°C. After that, two steps drying were operated at 40 Pa. The primary drying was operating until core product temperature reached to -10 0 10°C, respectively. The secondary drying temperature was controlled at 40°C. The freeze dried mango powder price reached to 1, 322.76 baht/kg. In addition, physical properties (total soluble solids, pH and color) of rehydrated freeze dried mango sample were similar to mango puree, which had not significantly different (p<0.05). Thus, freeze drying can be developed and applied to process as premium mango powder at the industrial level.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Identification and Removal of Negative Biomass Samples via Scatter Plot Analysis to Improve GWP Predictive Modeling
    (2025-11-13)
    Gyawali, Prakash
    ;
    Shrestha, Bijendra
    ;
    Posom, Jetsada
    ;
    Pornchaloempong, Pimpen
    ;
    Sirisomboon, Panmanas
    Accurate prediction of Global Warming Potential (GWP) from biomass constituents is essential for evaluating the sustainability of bioenergy sources. However, the inclusion of biomass samples with weak or negative correlation to key elemental components such as Carbon (C). Hydrogen (H). Nitrogen (N). and Oxygen (O)'can reduce model accuracy and lead to misleading conclusions. This study utilizes scatter plot regression analysis to evaluate and remove "negative biomass samples."defined as those with consistently low R<sup>2</sup> values across constituent-GWP relationships using HHV = 0.2949C + 0.82 50H developed for wood biomass by Yin. Regression models were generated for each biomass species using elemental concentrations as predictors of GWP. Notably, several non-wood species (e.g.. Zea Mays-Shell. Bagasse. Bamboo) exhibited very low R- values (often <0.05) for model between elemental composition and GWP. where all elemental correlations indicated weak predictive relationships. In contrast, wood-based species such as Alnus demonstrated significantly higher R<sup>2</sup> values, especially with Carbon (R<sup>2</sup> = 0.69). Hydrogen (R<sup>2</sup> = 0.57). and Oxygen (R<sup>2</sup> = 0.68), suggesting a stronger linear influence on GWP. Removing these low-contributing samples improved the clarity and reliability of the predictive model related to HHV and each type of element (C.H.N and O) as evidenced by a sharper regression slope of a graph plotted between predicted GWP and measured GWP of positive species and better fit (increased R<sup>2</sup>) for the remaining samples. These results highlight the value of preliminary scatter plot analysis in identifying biomass species that obscure rather than support predictive modeling. This filtering step ultimately enhances the robustness and inteipretability of constituent-based GWP prediction frameworks, particularly when applying FT-XIR spectroscopy and chemometric modelling.