The bacterial composition of bulk tank milk from 13 farms was examined over a 2-wk period to characterize sudden elevations in the total bacterial count referred to as "spikes." Bulk tank milk samples collected at each pick-up were analyzed for standard plate count, Petrifilm aerobic count, somatic cell count, gram-negative organisms, and streptococci. Twenty standard plate count spikes were observed: 12 associated with streptococci, 4 associated with gram-negative organisms, 2 associated with streptococci and gram-negative organisms, and 2 that were not definitively characterized. Spikes ranged from 14,000 to 600,000 cfu/ml. Streptococcus uberis was isolated as the predominant organism from 11 spikes, and Escherichia coli was isolated from 4 spikes. Statistical analysis of total bacterial counts indicated a high correlation (r = 0.94) between standard plate counts and Petrifilm aerobic count. Regression analysis of standard plate counts and Petrifilm aerobic counts yielded the equation log10 (standard plate count) = 0.73 + 0.85log10 (Petrifilm aerobic count), indicating that the correlation, although strong, is not one to one. In a related pilot study, triplicate bulk tank milk samples were collected and analyzed for total bacterial count and presumptive streptococcus, gram-negative, and staphylococcus counts. Two-way ANOVA of these triplicate data indicated a lack of significant variation among the triplicate samples, suggesting that one sample can reliably gauge the microbial status of the entire bulk tank.

The microbiological and sensory qualities of New York State (NYS) fluid milk products were assessed as part of an ongoing fluid milk quality program. Commercially packaged pasteurized fluid milk samples were collected twice a year over the 10-yr period from 2001 to 2010 from 14 NYS dairy processing facilities and analyzed at the Milk Quality Improvement Program (MQIP) laboratory. Each sample was tested throughout refrigerated storage (6°C) on day initial, 7, 10, and 14 for standard plate count (SPC), coliform count (CC), and sensory quality. Over the 10-yr period, the percentage of samples with bacterial numbers below the Pasteurized Milk Ordinance (PMO) limit of 20,000 cfu/mL at d 14 postprocessing ranged from a low of 21.1% in 2002 to a high of 48.6% in 2010. Percent samples positive for coliforms during that same period ranged from a high of 26.6% in 2002 to a low of 7.5% in 2007. Mean d 14 sensory scores ranged from a low of 6.0 in 2002 to a high of 7.3 in 2007. Samples contaminated with coliforms after pasteurization have significantly higher SPC counts and significantly lower sensory scores on d 14 of shelf-life than those not contaminated with coliforms. Product factors such as fat level were not significantly associated with SPC, CC, or sensory quality of the product, whereas the factor processing plant significantly affected overall product quality. This study demonstrates that overall fluid milk quality in NYS, as determined by microbiological and sensory analyses, has improved over the last decade, and identifies some challenges that remain.

Fluid milk consumption per capita in the United States has been steadily declining since the 1940s. Many factors have contributed to this decline, including the increasing consumption of carbonated beverages and bottled water. To meet the challenge of stemming the decline in consumption of fluid milk, the dairy industry must take a systematic approach to identifying and correcting for factors that negatively affect consumers' perception of fluid milk quality. To that end, samples of fluid milk were evaluated to identify factors, with a particular focus on light-emitting diode (LED) light exposure, which negatively affect the perceived sensory quality of milk, and to quantify their relative effect on the consumer's experience. Fluid milk samples were sourced from 3 processing facilities with varying microbial postprocessing contamination patterns based on historical testing. The effect of fat content, light exposure, age, and microbiological content were assayed across 23 samples of fluid milk, via consumer, descriptive sensory, and instrumental analyses. Most notably, light exposure resulted in a broad negative reaction from consumers, more so than samples with microbiological contamination exceeding 20,000 cfu/mL on days approaching code. The predominant implication of the study is that a component of paramount importance in ensuring the success of the dairy industry would be to protect fluid milk from all sources of light exposure, from processing plant to consumer.

The sensory quality of fluid milk is of great importance to processors and consumers. Defects in the expected odor, flavor, or body of the product can affect consumer attitudes toward the product and, ultimately, willingness to purchase the product. Although many methods of sensory evaluation have been developed, defect judging is one particular method that has been used for decades in the dairy industry for evaluating fluid milk. Defect judging is a technique whereby panelists are trained to recognize and rate a standard set of fluid milk defects that originate from various sources (e.g., microbial spoilage). This technique is primarily used in processing facilities where identification of sensory defects can alert personnel to potential quality control issues in raw material quality, processing, or good manufacturing practices. In 2014-2016, a preliminary study of defective milk judging screening and training was conducted by the Milk Quality Improvement Program at Cornell University (Ithaca, NY). The study, which included 37 staff and students from the Cornell community, used prescreenings for common odors and basic tastes, followed by uniform training to select, initially train, and retrain defect judges of unflavored high temperature, short time fluid milk. Significant improvements were seen in correct identification of defect attributes following initial training for all defect attributes, with the exception of fruity/fermented. However, following retraining, significant improvements were observed in only 2 defect attributes: cooked and milk carton. These results demonstrate that initial training is important for panelists to correctly identify fluid milk defect attributes, but that subsequent retraining should be tailored toward specific attributes. This study provides a resource for dairy industry stakeholders to use to develop relevant and efficient training methods for fluid milk defect judging panels.