Produce is responsible for 46% of all foodborne illnesses in the USA. Salmonella enterica causes 19,000 hospitalizations each year, and has been associated with produce. Presently, chlorine based sanitizers are most often used, however organic matter reduces its antimicrobial activity. Bacteriophage treatments are an all-natural, alternative method for pathogen inactivation. The objective of this study was to determine the efficacy of a five-strain bacteriophage treatment against a S. enterica cocktail in simulated wash waters at different temperatures. Bacteriophage and S. enterica were enumerated in simulated wash water solutions. One set of experiments studied bacteriophage and S. enterica growth in TSB+vegetable solutions. Bacteriophage behavior was not statistically different (p < 0.05) in spinach, romaine, or iceberg lettuce across different concentrations of organic matter. S. enterica reduction was approximately 2 log over 135 minutes for vegetable solutions and for the TSB control. S. enterica reduction was only 0.5 log in water solutions. The next set of experiments studied bacteriophage and S. enterica growth in vegetable solutions. Spinach wash water and tryptone soy broth solutions (TSB) at 20 °C and 37 °C. S. enterica was not reduced in spinach solution studies at 20 °C and 37 °C or at broth solutions at 20 °C. However, S. enterica was effectively reduced 4 log in broth solutions at 37 °C up to 7.5 hours, but grew to high levels after 24 hours. These results indicate that bacteriophage could not effectively control bacteria levels in produce wash water, and may need to be optimized.

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.

The Food Safety Modernization Act (FSMA) has a regulation stating that there can be no detectable generic Escherichia coli in agricultural water. The objective of this study was to optimize the use of peracetic acid (PAA) as a mitigating strategy in postharvest processing. This project began by investigating the impact of storage temperatures on stability of a commercially available PAA sanitizer. Regression analysis showed a quadratic relationship in the concentration of PAA over 12 weeks when storing the product at 4, 20 and 37°C. Stability of the product was also investigated in the presence of organic load over time at 60ppm PAA. PAA significantly decreased at an organic load level of 750COD. From this, the impact of various ratios of hydrogen peroxide (H2O2) and PAA were investigated further to see the efficacy against E. coli O157:H7 over three hours with reinoculation of bacteria after 3 hours. A higher level of PAA in the solution had a greater inactivation efficacy against E. coli O157:H7. The impact of concentration, organic load, temperature and pH on the efficacy against E. coli O157:H7 and stability of PAA over four hours was then investigated. All of the conditions tested showed a significant decrease in H2O2 and PAA concentrations over time, except at concentration of 80ppm, with varying rates of depletion under each condition tested. This study will help to create guidance on optimizing the use of PAA. With this knowledge growers can understand how changes in their post-harvest processing water can affect sanitizer performance.

No description available.

The presence of postharvest sanitizers has shown to be an effective approach to reducing microbial cross contamination in agricultural washing operations. However, choosing an appropriate sanitizer can be challenging due to produce commodity, processing conditions and interference with organic load. Current research shows a wide variety of methods to mimic the organic load of vegetable processing conditions, with paddle mixing and blender as the most commonly used. Controlling and understanding the physiochemical properties of wash water is key in maintaining sanitizer efficacy. The effects of simulated wash water preparation method on the physiochemical properties were tested at 0 and 50 COD(mg/L) and no significant difference was observed. However, at high levels of organic load results showed a significant difference between turbidity values at 1,500 COD. Free residual chlorine titration methods were compared, using DPD-titrimetric and Iodometric method. Results showed a significant difference between titration methods in organic load heavy environments. Commercially available chlorine based sanitizers, Pure Bright™ Germicidal Bleach and Clorox® Germicidal Bleach, were compared to a concentrated solution of sodium hypochlorite. Pure Bright™ Germicidal Bleach showed to perform the best by reducing 7 log CFU/ml of E. coli O157:H7 after 30 seconds in no organic load environments, whereas Clorox Germicidal bleach was able to reduce 7 log CFU/ml of E. coli O157:H7 after 30 minutes. These studies aim to provide best management practices for small in medium growers in the implementation of antimicrobial solutions for the maintenance of water quality in postharvest washing solutions.

The Agricultural Product Standards Act, 1990 (Act 119 of 1990) of South Africa provides for the standardisation of quality norms for agricultural produce (DAFF, 2018). The purpose of this research was to investigate the quality and compliance of fresh produce sold in the Tshwane metropolis with the Agricultural Product Standards Act of South Africa. A cross-sectional study survey was conducted in six regions of Tshwane metropolis, in which 200 fresh produce vendors were randomly selected from various vending sites to analyse their level of knowledge regarding the Act. Furthermore, different fruits and vegetables were sampled from different vending sites and inspected for compliance with the Act.The vast majority (89%) of respondents did not know of the existence of the Act. Quite a small proportion of fruit (51.5 %) and vegetable (56 %) retailers indicated that their agricultural fruit products have been monitored. A large proportion of fruits (from 86% to 99.8%) and vegetables (from 85.4% to 97.5%) met all the various quality requirements. In general a fair proportion of fruits (58%) and vegetables (65%) complied highly with the Act in terms of quality. There was a significant positive correlation between monitoring by officials and the level of compliance. The Department of Agriculture Forestry and Fisheries should make sure that farmers and street vendors of agricultural produce register their businesses and are trained on the interpretation of the provisions of the Agricultural Product Standards Act. This will allow them to be tracked and traced for proper development concerning matters related to the Act. / Life and Consumer Sciences / M.A. (Consumer Science)