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Tekijä: | Ali, Javeria |
Työn nimi: | Exploratory data analysis of microbial communities in food production environment |
Julkaisutyyppi: | Diplomityö |
Julkaisuvuosi: | 2014 |
Sivut: | vii + 47 Kieli: eng |
Koulu/Laitos/Osasto: | Perustieteiden korkeakoulu |
Oppiaine: | Information and Computer Science (T-61) |
Valvoja: | Rousu, Juho ; Aurell, Erik |
Ohjaaja: | Hultman, Jenni |
Elektroninen julkaisu: | http://urn.fi/URN:NBN:fi:aalto-201410042707 |
OEVS: | Sähköinen arkistokappale on luettavissa Aalto Thesis Databasen kautta.
Ohje Digitaalisten opinnäytteiden lukeminen Aalto-yliopiston Harald Herlin -oppimiskeskuksen suljetussa verkossaOppimiskeskuksen suljetussa verkossa voi lukea sellaisia digitaalisia ja digitoituja opinnäytteitä, joille ei ole saatu julkaisulupaa avoimessa verkossa. Oppimiskeskuksen yhteystiedot ja aukioloajat: https://learningcentre.aalto.fi/fi/harald-herlin-oppimiskeskus/ Opinnäytteitä voi lukea Oppimiskeskuksen asiakaskoneilla, joita löytyy kaikista kerroksista.
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Sijainti: | P1 Ark Aalto 1738 | Arkisto |
Avainsanat: | data analysis food environment microbial community spoilage bacteria |
Tiivistelmä (eng): | Food operators require products to be free and safe from microbial contamination. The characteristics and activities of microbial communities in food material, at the time of processing, influences shelf life, quality, and spoilage rate. Present processing and storage conditions enable growth of bacterial species adapted to survive extreme conditions, making them a concern in the food industry as they result in food unfit or hazardous for human consumption. In this thesis, 16S rRNA gene amplicon data was used to investigate the microbial community structure and composition sampled from a Finnish sausage processing factory. To roughly analyze the distribution of dominating bacterial species in each processing stage, the 16S rRNA gene count data was filtered to retain OTUs having a non-zero, to greater than 50, read counts in more than 50% of the samples, where differences in composition were tested for significance. A more thorough analysis included agglomerative hierarchical clustering using Ward's minimum variance method, to explore OTU grouping based on their read count composition, across various food processing environments and within factory locations. Both approaches identified spoilage bacteria of the genus Leuconostocs, Pseudomonas, Brochothrix, Yersinia, Carnobacterium, Lactobacillus, Lactococcus, Streptococcus and Clostridium dominating samples. Lactic acid bacteria such as Leuconostocs were found abundant in packaged product and emulsion samples whereas Brochothrix, Pseudomonas and Carnobacterium were abundant in nutrient rich mediums such as meat. The results of the analysis coincide with findings in literature. Factory equipment surfaces were abundant in spoilage species such as Brochothrix, Clostridium, and Yersinia, which are reported in literature to grow on meat and skin. Metal equipment surfaces had a higher incidence of spoilage bacteria compared to plastic surfaces. The current analysis also showed that the effect of extensive and daily cleaning leads to the higher growth of certain spoilage bacteria, instead of reducing their number. The presence of spoilage bacteria on factory surfaces suggests the formation of biofilms that are difficult to remove. |
ED: | 2014-10-05 |
INSSI tietueen numero: 49768
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