Thesis--Cornell University. / Bibliography: p. 179-187.

Thesis (Ph. D.)--Catholic University of America, 1922. / Vita. Facsimile edition, 1975. Bibliography: p. 150-154.

Thesis (M.A.)--University of North Carolina Wilmington, 2009. / Title from PDF title page (January 11, 2010) Includes bibliographical references (p. 83-88)

Thesis (M.S.)--University of Wisconsin, 1967. / Extension Repository Collection. Typescript (carbon copy). Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 84-85).

Thesis (Ph. D.)--University of Florida, 1993. / Vita. Includes bibliographical references (leaves 159-164).

Published also as a Thesis (Ph. D.) Princeton University. / Xerox microfiche facsimile.

Thesis (M.S.)--Wisconsin State University at La Crosse.

No description available.

Thesis (MSc Food Science)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: South Africa is a water scarce country and farmers are forced to irrigate crops with river water. Contamination of South African rivers has been reported and the carry-over of bacteria from river water to produce has been confirmed. Foodborne outbreaks linked to fresh produce are increasing world-wide. A total of 151 fresh produce samples (lettuce, tomatoes, beans, peas, coriander, basil, mint, rocket, thyme, spinach, cabbage, parsley and sprouts) were sourced from small-scale and commercial farms, farmers’ markets and retail outlets. Total coliforms (TC) and E. coli loads on the produce were determined with Colilert-18. Isolates were phenotypically characterised and identified with the API system and the E. coli identification confirmed with uidA PCR. Sixty-three E. coli isolates were identified. Three were not identified as E. coli with the API system but were positive for the uidA gene. The TC loads for the produce from the farms, farmers’ markets and retail outlets were all in the range of log 3 to log 8.38 MPN.100 mL-1. Escherichia coli was found to be most prevalent on produce samples from farmers’ markets with the highest E. coli load (log 7.38 MPN.100 mL-1) on cabbage sampled from a commercial farm. Escherichia coli were present on 8% of the produce samples. The maximum TC and E. coli loads found on the fresh produce were log 8.38 and log 7.38 MPN.100 mL-1, respectively. The lowest risk in terms of TC and E. coli presence and load was observed on fresh produce from retail outlets and the highest risk was on fresh produce from farmers’ markets. Phenotypic dendrograms and a PCA plot were statistically constructed to determine similarity groupings of the isolates and three main E. coli clusters were formed. These three clusters could not be directly linked to a specific produce type or source type. A larger variation E. coli phenotypes was observed present on fresh produce within the three clusters. All E. coli isolates were also subjected to triplex and multiplex PCR analysis to identify their phylogenetic groups and the presence of INPEC and ExPEC strains. Fourteen isolates belonged to genotypic group A0, 11 to A1, 20 to B1, 7 to B23 and 11 to D2. Thus a large variation E. coli genotypes are present but it cannot be linked to a specific source type or produce type. Multiplex PCR testing for INPEC revealed that none of the E. coli isolates were carriers of the INPEC genes. The isolates were also tested for the presence of ExPEC gene sequences: papA, papC, sfa/foc, iutA, kpsMT II and afa/dra. None of the isolates were classified as ExPEC (which required the presence of two or more genes) but three of the isolates did test positive for the presence of the kpsMT II gene. The latter could indicate that potentially pathogenic E. coli can be evolving in the environment and increase the risk of pathogenic E. coli occurring on fresh produce. In conclusion, the presence of E. coli (commensal or pathogenic) on fresh produce is unacceptable according the South African Department of Health. According to this study the identification of E. coli types could not be correlated with the presence of E. coli on the different produce types and thus the presence of E. coli on fresh produce is unpredictable. It is recommended that extensive safety precautions should be in place throughout every step in the production chain from harvest to the consumer’s kitchen to reduce the probability of contamination of fresh produce. / AFRIKAANSE OPSOMMING: Suid-Afrika is ‘n waterskaars land en boere word gedwing om rivier water te gebruik vir gewas besproeiing. Kontaminasie van Suid-Afrikaanse riviere is al telkemale aangemeld en die oordrag van bakterieë vanaf rivierwater na vars produkte is al voorheen bevestig. Voedselverwante uitbrake wat gekoppel is aan vars produkte is besig om wêreldwyd toe te neem. ‘n Totaal van 151 vars produk monsters (blaarslaai, tamaties, boontjies, ertjies, koljander, basilie, kruisement, roket, tiemie, spinasie, kool, pietersielie en spruite) was verkry van klein-skaalse en kommersiële plase, plaasmarkte en kettingwinkels. Totale kolivorme (TK) en E. coli tellings op die vars produkte is bepaal deur middel van Colilert-18. Isolate word fenotipies gekarakteriseer en geïdentifiseer met die API sisteem en die E. coli identifikasie is bevestig met uidA PKR. Drie-en-sestig E. coli isolate is geïdentifiseer. Drie is nie met met die API sisteem as E. coli geklassifiseer nie, maar was wel positief vir die uidA geen. Die TK tellings vir die vars produkte van die plase, plaasmarkte en kettingwinkels was almal in die reeks van log 3 tot log 8.38 MPN.100 mL-1. Escherichia coli teenwoordigheid was die meeste op groente monsters van plaasmarkte, maar die hoogste E. coli telling (log 7.83 MPN.100 mL-1) was op ‘n kool monster van ‘n kommersiële plaas. Escherichia coli was teenwoordig op 8% van die vars produk monsters. Die maksimum TK en E. coli wat teenwoordig was op die vars produkte was log 8.38 en log 7.38 MPN.100 mL-1 onderskeidelik. Die laagste risiko in terme van TK en E. coli teenwoordigheid en tellings is waargeneem op vars produkte van kettingwinkels en die hoogste risiko is op vars produkte van plaasmarkte. Fenotipiese dendrogramme en ‘n PKA plot is statisties gekonstrueer om ooreenstemende groepe van isolate te identifiseer en drie hoof groepe is gevorm. Daar kon geen direkte verband gevind word tussen hierdie drie groepe en ‘n spesifieke produk-tipe of ‘n spesifieke bron-tipe nie. ‘n Groter variasie in E. coli fenotipes teenwoordig op die vars produkte is waargeneem binne die drie groepe. Alle E. coli isolate was onderworpe aan tripleks en multipleks PKR analise om die filogenetiese groep van elke isolaat te bepaal en of enige INPEC of ExPEC stamme teenwoordig is. Veertien isolate behoort aan genotipiese groep A0, 11 aan A1, 20 aan B1, 7 aan B23 en 11 aan D2. Dus is ‘n groot variasie E. coli genotipes teenwoordig maar dit kan nie gekoppel word aan ‘n spesifieke produk-tipe of bron-tipe nie. Multipleks PKR analise vir INPEC het gewys dat geeneen van die E. coli isolate enige INPEC gene dra nie. Die isolate is ook getoets vir die teenwoordigheid van ExPEC geen volgordes: papA, papC, sfa/foc, iutA, kpsMT II en afa/dra. Geeneen van die isolate is geklassifiseer as ExPEC (wat die teenwoordigheid van twee of meer gene vereis) nie, maar drie van die isolate het wel positief getoets vir die teenwoordigheid van die kpsMT II geen. Laasgenoemde kan ‘n aanduiding wees dat potensiële patogeniese E. coli in die omgewing kan ontwikkel en dus dan die risiko van die teenwoordigheid van patogeniese E. coli op vars produkte sal verhoog. Ter afsluiting, die teenwoordigheid van E. coli (nie-patogenies en patogenies) op vars produkte is onaanvaarbaar volgens die Suid-Afrikaanse Departement van Gesondheid. Volgens hierdie studie kan die identifisering van E. coli tipes nie gekorreleer word met die teenwoordigheid van E. coli op verskillende produk-tipes nie en dus is die teenwoordigheid van E. coli op vars produkte onvoorspelbaar. Dit word aanbeveel dat ekstensiewe voorsorgmaatreëls in plek moet wees in elke stap dwarsdeur die produksie ketting, vanaf oestyd tot in die verbruiker se kombuis, om die moontlikheid van vars produk kontaminasie te verminder.

abstract: This thesis develops a low-investment marketing strategy that allows low-to-mid level farmers extend their commercialization reach by strategically sending containers of fresh produce items to secondary markets that present temporary arbitrage opportunities. The methodology aims at identifying time windows of opportunity in which the price differential between two markets create an arbitrage opportunity for a transaction; a transaction involves buying a fresh produce item at a base market, and then shipping and selling it at secondary market price. A decision-making tool is developed that gauges the individual arbitrage opportunities and determines the specific price differential (or threshold level) that is most beneficial to the farmer under particular market conditions. For this purpose, two approaches are developed; a pragmatic approach that uses historic price information of the products in order to find the optimal price differential that maximizes earnings, and a theoretical one, which optimizes an expected profit model of the shipments to identify this optimal threshold. This thesis also develops risk management strategies that further reduce profit variability during a particular two-market transaction. In this case, financial engineering concepts are used to determine a shipment configuration strategy that minimizes the overall variability of the profits. For this, a Markowitz model is developed to determine the weight assignation of each component for a particular shipment. Based on the results of the analysis, it is deemed possible to formulate a shipment policy that not only increases the farmer's commercialization reach, but also produces profitable operations. In general, the observed rates of return under a pragmatic and theoretical approach hovered between 0.072 and 0.616 within important two-market structures. Secondly, it is demonstrated that the level of return and risk can be manipulated by varying the strictness of the shipping policy to meet the overall objectives of the decision-maker. Finally, it was found that one can minimize the risk of a particular two-market transaction by strategically grouping the product shipments. / Dissertation/Thesis / M.S. Industrial Engineering 2011