Method of Improving Cheese Quality

A method is provided for improving the quality of cheese produced from a curd and whey mixture. The method comprises the steps of monitoring the curd and whey mixture during syneresis processing to collect color data, comparing the color data to a predetermined standard and terminating syneresis when the color meets the predetermined standard or, alternatively, analyzing the color data obtained to generate kinetic parameters that can be used to predict the end point of syneresis to improve control of curd moisture content

Distinguishing Bovine Fecal Matter on Spinach Leaves Using Field Spectroscopy

Detection of fecal contaminants on leafy greens in the field will allow for decreasing cross-contamination of produce during and post-harvest. Fecal contamination of leafy greens has been associated with Escherichia coli (E. coli) O157:H7 outbreaks and foodborne illnesses. In this study, passive field spectroscopy measuring reflectance and fluorescence created by the sun’s light, coupled with numerical normalization techniques, are used to distinguish fecal contaminants on spinach leaves from soil on spinach leaves and uncontaminated spinach leaf portions. A Savitzky-Golay first derivative transformation and a waveband ratio of 710:688 nm as normalizing techniques were assessed. A soft independent modelling of class analogies (SIMCA) procedure with a 216 sample training set successfully predicted all 54 test set sample types using the spectral region of 600–800 nm. The ratio of 710:688 nm along with set thresholds separated all 270 samples by type. Application of these techniques in-field to avoid harvesting of fecal contaminated leafy greens may lead to a reduction in foodborne illnesses as well as reduced produce waste

Supplemental Table 1 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 1 provides demographic and tobacco use characteristics of exclusive and polytobacco users.</p

Supplemental Table 6 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 6 provides Wave 1 and Wave 4 TNE-2 cut-points for any tobacco use.</p

Supplemental Table 2 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 2 provides demographic and tobacco use characteristics of any tobacco users.</p

Supplemental Table 5 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 5 provides Wave 1 and Wave 4 cotinine cut-points for any tobacco use.</p

Supplemental Table 4 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 4 provides prevalence rates of any tobacco use using TNE-2 cut-points.</p

Supplemental Table 3 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Table 3 provides prevalence rates of any tobacco use using cotinine cut-points.</p

Supplemental Figure 1 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study

Supplemental Figure 1 shows the analytic sample flow chart.</p