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Wyszukujesz frazę "sweet corn" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Ecological Footprint Analysis of Canned Sweet Corn
Autorzy:
Usubharatana, P.
Phungrassami, H.
Powiązania:
https://bibliotekanauki.pl/articles/123689.pdf
Data publikacji:
2016
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
ecological footprint
life cycle assessment (LCA)
sweet corn
food industry
Opis:
There has been a notable increase in both consumer knowledge and awareness regarding the ecological benefits of green products and services. Manufacturers now pay more attention to green, environmentally friendly production processes. Two significant tools that can facilitate such a goal are life cycle assessment (LCA) and ecological footprint (EF). This study aimed to analyse and determine the damage to the environment, focusing on the canned fruit and vegetable processing. Canned sweet corn (340 g) was selected for the case study. All inputs and outputs associated with the product system boundary were collected through field surveys. The acquired inventory was then analysed and evaluated using both LCA and EF methodology. The results were converted into an area of biologically productive land and presented as global hectares (gha). The ecological footprint of one can of sweet corn was calculated as 6.51E-04 gha. The three factors with the highest impact on ecological footprint value were the corn kernels used in the process, the packaging and steam, equivalent to 2.93E-04 gha, 1.19E-04 gha and 1.17E-04 gha respectively. To promote the sustainable development, the company should develop new technology or utilize better management techniques to reduce the ecological footprint of canned food production.
Źródło:
Journal of Ecological Engineering; 2016, 17, 3; 22-29
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sweet Corn Yield Simulation Using Normalized Difference Vegetation Index and Leaf Area Index
Autorzy:
Lykhovyd, Pavlo
Powiązania:
https://bibliotekanauki.pl/articles/124254.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
direct measurement
mathematical model
regression analysis
remote sensing
sweet corn
yield prediction
Opis:
The authors determined the accuracy and reliability of yielding models by using the values of two differently obtained indices – the leaf area index (LAI) obtained through direct surface measurements, and the normalized difference vegetation index (NDVI) obtained through spatial remote sensing of crops. The study based on the drip-irrigated sweet corn yielded the data obtained in the field experiment held in the semi-arid climate on darkchestnut soil in the South of Ukraine. The suitability of the LAI and NDVI for the simulation of sweet corn yields was estimated by the regression analysis of the yielding data by correlation (R) and determination (R2) coefficients. Additionally, mathematical models for the crop yields estimation based on the regression analysis were developed. It was determined that LAI is a more suitable index for the crop yield prediction: the R2 value was 0.92 and 0.94 against 0.85 for the NDVI-based models.I It was determined that it is better to use the LAI values obtained at the stage of flowering, when R2 averaged to 0.94, and the NDVI-based models does not depend on the crop stage (the R2 was 0.85 both for the flowering and ripening stages of the plant development). The combined NDVI-LAI model showed that there is no necessity in the complication of the LAI-based model through introduction of the remotely sensed index because of insignificant improvement in the performance (R2 was 0.94 and 0.92).
Źródło:
Journal of Ecological Engineering; 2020, 21, 3; 228-236
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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