Overview of the Potential Impacts of Climate Change on the Microbial Safety of the Dairy Industry.

Climate change is expected to affect many different sectors across the food supply chain. The current review paper presents an overview of the effects of climate change on the microbial safety of the dairy supply chain and suggest potential mitigation strategies to limit the impact. Raw milk, the common raw material of dairy products, is vulnerable to climate change, influenced by changes in average temperature and amount of precipitation. This would induce changes in the microbial profile and heat stress in lactating cows, increasing susceptibility to microbial infection and higher levels of microbial contamination. Moreover, climate change affects the entire dairy supply chain and necessitates adaptation of all the current food safety management programs. In particular, the review of current prerequisite programs might be needed as well as revisiting the current microbial specifications of the receiving dairy products and the introduction of new pretreatments with stringent processing regimes. The effects on microbial changes during distribution and consumer handling also would need to be quantified through the use of predictive models. The development of Quantitative Microbial Risk Assessment (QMRA) models, considering the whole farm-to-fork chain to evaluate risk mitigation strategies, will be a key step to prioritize actions towards a climate change-resilient dairy industry.

Decimal reduction energies of UV-C-irradiated spoilage yeasts in coconut liquid endosperm.

The ultraviolet-C (UV-C) decimal reduction energy (DUV-C) values of 17 spoilage yeasts and their composited inoculum were determined in coconut liquid endosperm (pH 5.26, 5.8 °Brix, 0.04% malic acid, 0.17% w/v insoluble solids). Growth kinetic parameters of all the test yeast strains were first established to standardize the growth stage of the cells prior to inactivation studies. Approximately 4.0 to 5.0 log CFU/mL cells in the mid-stationary growth phase (30.3 to 39.9 h, 25 °C) were suspended in 4 mL turbulent flowing juice and subjected to UV-C irradiation at a surface irradiance range of 3.42 to 4.99 mW/cm2. Survivor populations after exposure to predetermined UV-C energy were enumerated, and were used to derive the DUV-C values using the linear regression and Baranyi and Roberts (1994) model fitting. Results show that the yeast strains exhibited either log-linear or biphasic inactivation behavior with inactivation lag. The most UV-C resistant spoilage yeast was found to be Cryptococcus albidus (LJY1) with DUV-C values of 122.72 and 214.89 mJ/cm2 determined from linear regression and model-fitting, respectively. The least UV-C resistant was Torulaspora delbrueckii (LYJ5) with a DUV-C of 17.34 (linear regression) and 17.35 mJ/cm2 (model-fitting). The DUV-C values determined from the model fitting were generally greater than those calculated from linear regression, although only those determined for C. albidus were significantly different. To the investigators' knowledge, this is the first report of the UV-C inactivation kinetic parameters of Kluyveromyces marxianus, Trichosporon cutaneum, Pichia anomala, and Meyerozyma guilliermondii and C. albidus in coconut liquid endosperm. The results of this study can be used in the establishment and validation of UV-C process schedules for coconut liquid endosperm and other similar commodities.

Ultraviolet-C resistance of selected spoilage yeasts in orange juice.

This study determined the ultraviolet-C (UV-C) dose necessary to reduce 90% population (DUV-C) of 17 spoilage yeasts and their composited inoculum in orange juice (pH 3.71, 11.60 °Brix, 0.55% citric acid, 2.46% w/v insoluble solids). Growth parameters of all test yeasts were first established to standardize the growth stage of the cells prior to harvesting and eventual UV-C challenge studies. Approximately 4-5 log CFU/ml cells in the mid-stationary growth phase (30.3 t0 39.9 h, 25 °C) were suspended in 4 ml turbulent flowing juice and subjected to UV-C irradiation at an incident surface irradiance of 3.64-4.97 mW/cm2. The inactivation rates of each yeast and their composited inoculum were determined using 2 methods namely, the linear regression and Baranyi and Roberts (1994) model-fitting. Results showed that the yeasts exhibited either log-linear or biphasic inactivation behavior with downward concavity or inactivation lag. Regardless of the method of determination, Cryptococcus albidus (LJY1) exhibited the significantly greatest (p < 0.05) UV-C resistance with DUV-C values of 1924.31 and 2174.63 mJ/cm2. On the other hand, Candida parapsilosis was determined to be least resistant with a DUV-C values of 245.83 and 357.88 mJ/cm2. Majority of the DUV-C values determined from the model-fitting were greater than those calculated from linear regression. However, only those determined for the composited inoculum were significantly different. The results of this study address knowledge gaps pertinent to the UV-C resistance of less studied spoilage yeast, and help in better understanding the utility of this non-thermal food processing technology.