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Enregistrement W4404145534 · doi:10.3390/microorganisms12112251

Microbiological Analysis of Wild Lowbush Blueberries Harvested in Nova Scotia, Canada for the Fresh Produce Market

2024· article· en· W4404145534 sur OpenAlex

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Notice bibliographique

RevueMicroorganisms · 2024
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueInsect Utilization and Effects
Établissements canadiensAgriculture and Agri-Food Canada
Organismes subventionnairesAgriculture and Agri-Food CanadaDepartment of Agriculture, Nova ScotiaWild Blueberry Producers Association of Nova Scotia
Mots-clésNova scotiaNova (rocket)BiologyGeographyEngineeringAeronauticsArchaeology

Résumé

récupéré en direct d'OpenAlex

Canada is a leading producer of wild lowbush blueberries, most of which are mechanically harvested, washed, individually quick frozen (IQF), and bulk packaged. Still, some berries are harvested by more gentle methods and sold as fresh-packed products. These berries do not undergo a wash step, nor are subjected to antimicrobial treatments. The purpose of this study was to conduct a microbiological survey of berries harvested in the province of Nova Scotia to assess their potential for harborage of bacterial foodborne pathogens. A combination of standardized plate count methods and 3M-Petrifilm protocols were used to enumerate total aerobic mesophilic bacteria (APC), yeasts and molds (YMC), coliforms, and generic E. coli, the latter being an indicator of fecal contamination. Overall, APC and YMC levels were 1.2 and 0.5 log greater, respectively, for berries collected early in the harvest season versus those acquired late season and varied significantly (p < 0.05) between farm (location) and harvest practices used. Berries harvested by our team using sanitized hand rakes (SH) had consistently lower APC and YMC levels than those harvested by farm crews. Yet, when gentle harvesting (GH) methods (hand-raking, walk-behind or modified mechanical harvesters) were employed on farms, lower numbers were generally observed compared to berries harvested by traditional tractor-mounted mechanized harvesters (MH). The presence of coliforms (and their levels) was also impacted by the harvest method, with detection rates of ~29%, 73%, and 92% in SH, GH, and MH samples, respectively. Mean counts were < 2.5 log10 CFU/g for both SH and GH berries, but significantly higher (p < 0.05) on MH berries (3.6 log10 CFU/g). Although ~56% of all berry samples collected (n = 350) contained coliforms, only 12 were positive for E. coli, 9 of which were MH samples. Only the latter had numbers > 2 log10 CFU/g, but none tested positive for Shiga toxin-producing serotype O157 (STEC O157) or Salmonella spp. when using internationally recognized selective enrichment and plating methods. ATP luminescence was used to assess the general hygiene of processing lines, whereby “hot spots” for microbial activity were identified, even after cleaning., Standard selective enrichment and plating methods were used for the detection of Listeria monocytogenes on 61 swab samples taken from berry totes or conveyor belts at different times during processing; 4 swabs tested positive for L. monocytogenes. However, the pathogen could not be detected by direct plating on selective agar without prior enrichment; this indicated its numbers were low. The results from this work demonstrated that alternative gentle harvest methods can reduce microbial numbers on wild blueberries. Although the frequency of fecal contamination in berry samples appeared to be low and targeted human pathogens were not detected; this represents a single study conducted over one harvest season. Therefore, it would be prudent for processors to seek effective antimicrobial technologies prior to packaging, while consumers should use caution and thoroughly wash produce before consumption. Where sporadic detection of L. monocytogenes was observed on environmental samples from the processing line, processors must ensure that effective sanitation programs are implemented to avoid potential food safety risks.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,752
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,209
Écart entre enseignants0,197 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle