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Analysis of several acceptance sampling procedures is performed and improvement of the procedures is sug- gested in this thesis. The issue of an efficient calculation of exact (P1, P2) single sampling plans for sampling by variables and exact LTPD and AOQL single sampling plans for sampling by variables when the rejected lots are inspected is addressed. The calculation of the plans is done using exact formula for operating characteristic of acceptance sampling plan and the new plans have better characteristics compared to the plans computed in a usual way using just approximately valid formula for operating characteristic. The tables of plans calculated according to procedures suggested in this thesis are provided for a couple of input parameters combinations. Tools designed for working with acceptance sampling plans, tools for analysis and calculation of acceptance sampling plans is one of the outputs of this thesis. R language and environment for statistical computations was chosen for implementation. The tools are satisfactorily efficient and may be easily used even for acceptance sampling plans tables computation. Newly defined functions in R are supplied including their source code and basic documentation so that acceptance sampling plans can be computed as demanded in case that the particular input parameters set is out of the scope covered in the tables of plans provided here.

Doctor of Philosophy / Department of Entomology / Thomas W. Phillips / The phase-out of methyl bromide production, the most effective fumigant for the control of the ham mite, Tyrophagus putrescentiae (Schrank) (Acari: Acaridae), on dry-cured ham has necessitated the search for other management methods. The foundation of a successful management program is an effective monitoring program that provides information on pest presence and abundance over time and space to help in making management decisions. By using the standard trap made from disposable Petri dishes and a dog food-based bait, mite activity was monitored weekly in five dry-cured ham aging rooms from three commercial processing facilities from June 2012 to September 2013. Results indicated that mite numbers in traps in facilities typically had a pattern of sharp decline after fumigation, followed by a steady increase until the next fumigation. Average trap captures varied due to trap location, indicating that traps could be used to identify locations where mite infestation of hams may be more likely to occur. Experiments were also conducted in 6 m x 3 m climate-controlled rooms to determine the effects of some physical factors on trap capture. Factors such as trap design, trap location, trap distance, duration of trapping, and light conditions had significant effects on mite capture. Mites also responded differently to light emitting diodes of different wavelengths, either as a component of the standard trap or as a stand-alone stimulus to orientation. To determine the relationship between trap capture and mite density, experiments were carried out in the climate-controlled rooms. Mite density was varied but trap number remained constant for all mite densities. There was strong positive correlation between trap capture and mite density. In simulated ham aging rooms, the distribution of mites on hams was determined and different sampling techniques such as vacuum sampling, trapping, rack sampling, ham sampling and absolute mite counts from whole hams were compared and correlated. Results showed weak or moderate correlations between sampling techniques in pairwise comparisons. Two sampling plans were developed to determine the number of samples required to estimate mite density on ham with respect to fixed precision levels or to an action threshold for making pest management decisions. Findings reported here can help in the optimization of trapping and sampling of ham mite populations to help in the development of efficient, cost-effective tools for pest management decisions incorporated with alternatives to methyl bromide.

Les industriels du secteur agro-alimentaire sont responsables de la qualité des produits mis sur le marché. Un moyen de vérifier cette qualité consiste à déterminer la distribution de la contamination. Dans cette thèse, nous avons utilisé des données portant sur L. monocytogenes durant le procédé de fabrication de lardons et du saumon fumé. Nous avons ensuite élaboré des modèles hiérarchiques pour décrire la concentration en prenant ou non en compte diverses variabilités, nous avons estimé les paramètres par inférence bayésienne, puis comparé leur capacité à simuler des données proches des observations. Nous avons également comparé l'estimation de paramètres par inférence fréquentiste sur deux modèles en utilisant les données brutes issues des analyses microbiologiques et ces mêmes données converties en concentration. Par ailleurs, nous avons amélioré un modèle décrivant le devenir de L. monocytogenes au cours de la fabrication des lardons. Le plan d'échantillonnage permettant d'estimer la qualité des produits, nous avons appliqué la théorie de la décision aux couples L. monocytogenes/lardons et L. monocytogenes/saumon fumé en sortie usine pour déterminer la taille optimale de l'échantillon à prélever par lot de manière à minimiser les coûts moyens supportés par le fabricant. Enfin, nous avons comparé plusieurs plans d'échantillonnage de mesure de la température d'un plat en sauce fabriqué dans une cuisine centrale et placé dans une cellule de refroidissement rapide. L'objectif était de sélectionner le meilleur plan d'échantillonnage en fonction du risque admissible pour le gestionnaire quant à la croissance de C. perfringens. / Food business operators are responsible for the quality of the products they sell. A way to assess the safety of food is to determine the contamination distribution. During my PhD thesis, we used data about L. monocytogenes during the process of diced bacon and of cold smoked salmon. Then, we constructed several hierarchical models to describe contamination taking or not into account several kinds of variability such as between batches variability. We compared the capacity of each model to simulate data close to the observed ones. We also compared the parameters assessment by frequentist inference using raw data (the results of the microbiological analyses) and concentration-like data. In addition to the models describing the contamination at one step of the process, we improved an existing model describing the fate of L. monocytogenes throughout the diced bacon process. A tool to assess the quality of a product is the sampling plan. We applied the Bayesian theory of decision to the pairs L. monocytogenes/diced bacon and L. monocytogenes/cold smoked salmon at the end of the process to determine the optimal size of a sample analysed per batch so that the average cost for the manufacturer is as los as possible. We also compared several sampling plans of temperature measurement of a meal cooked in an institutional food service facility and put in a blast-chiller just after cooking. The aim was to select the best sampling plan regarding the risk of C. perfringens growth that the manager is ready to take.