Quality of Sour Cream Packaged in Cups with Different Light Barrier Properties Measured by Fluorescence Spectroscopy and Sensory Analysis

ABSTRACT:  In this study, photooxidation of sour cream packaged in cups with different light barrier properties was investigated. The sour cream was light exposed for 36 h with a standard fluorescent light tube, simulating storage conditions in many Norwegian grocery stores. Three different cups were evaluated: a white cup, a cup with medium light barrier (LB), and a cup with high LB. The quality of the sour cream was evaluated by sensory analysis and front face fluorescence spectroscopy. The sour cream stored in white cups became very rancid during the light exposure, with a rancid flavor score of 7.8 on a scale from 1 to 9, where 9 is the highest intensity. Cups with high LB gave best protection against the light. The sensory assessors could not distinguish between sour cream stored in cups with high LB and sour cream stored in the dark. The rancid flavor intensity for the cups with medium LB was significantly different ( P  < 0.05) from both the white cup and the cup with high LB. The sensory flavor intensities indicated that with 36 h of light exposure, only a cup with high LB will protect the sour cream sufficiently. The fluorescence measurements corresponded well with the sensory analysis as the photosensitizers were somewhat degraded for sour cream stored in cups with medium LB and most degraded in the white cups. For the cups with high LB, the fluorescence peaks that originated from the photosensitizers were all intact.
PRACTICAL APPLICATION: Dairy products such as sour cream will develop off-odor and taste faults ("sunlight taste") in a few hours if exposed to sufficient fluorescent lightning in the grocery stores. A light barrier can be incorporated in the packaging material to protect the dairy products from the light. Our experiment showed that the incorporation of a black pigment into 1 of the 3 plastic layers in the cup for packaging of sour cream protected the sour cream from degradation when exposed to light.     

Adjustment to a dyadic stressor: A longitudinal study of coping and depressive symptoms in infertile couples over an insemination attempt.

In a study designed to examine how intimate partners' coping processes with regard to infertility predicted depressive symptoms across the course of a treatment cycle, 43 couples completed assessments in the week prior to and the week after receiving a negative pregnancy result from an alternate insemination attempt by the partner. Depressive symptoms in both partners increased significantly after the pregnancy result receipt. As hypothesized, avoidant coping predicted increased distress over time, and approach-oriented coping (e.g., problem-focused coping, emotional processing, and expression) predicted decreased distress. Coping strategies engaged in by both individuals and partners predicted depressive symptoms, and for women, interactions also emerged between their own and their partners' coping. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Transfer in artificial grammar learning: The role of repetition information.

In this article, the authors report 2 experiments that investigated the sources of information used in transfer and nontransfer tasks in artificial grammar learning. Multiple regression analyses indicated that 2 types of information about repeating elements were crucial for performance in both tasks: information about the repetition of adjacent elements and information about repetition of elements in the whole item. Similarity of test items to specific training items and chunk information influenced participants' judgments only in nontransfer tasks. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Satellite-derived irradiance statistics for Africa

Hourly images registered by the Meteosat satellite are used to derive the global irradiance at ground level. Keeping almost the full spatial information of the original images, maps of irradiance characteristics for Africa are derived with a resolution of approx. 10 × 10 km². Monthly irradiance conditions are characterized by means and standard deviations of daily sums and the irradiance of specific daytime hours. The data also allow for the extraction of irradiance time series for specific sites. In addition, the analysis of the spatial structure of the satellite-derived irradiance fields is used to identify regions in which the radiation characteristics call for special attention.     

Sub-micrometer particulate air pollution and cardiovascular mortality in Beijing, China

Background

While the link between particulate matter and cardiovascular mortality is well established, it is not fully investigated and understood which properties of the aerosol might be responsible for the health effects, especially in polluted mega-city areas.

Objectives

Our goal was to explore the association between daily cardiovascular mortality and different particle metrics in the sub-micrometer range in Beijing, China.

Methods

We obtained daily counts of cause-specific cardiovascular deaths in the Beijing urban area for the period March 2004 to August 2005. Concurrently, continuous measurements of particle number size distributions were performed. Particle number concentrations (NC) between 0.003 μm and 0.8 μm were converted to particle mass and surface area concentrations assuming spherical particles. Semi-parametric Poisson regression models adjusting for trend, seasonality, day of the week, and meteorology were used to estimate immediate, delayed and cumulative particle effects. Additionally, effect modification by air mass origin was investigated.

Results

We observed associations between daily cardiovascular mortality and particle NC for a 2-days delay. Moreover, nearly all particle metrics showed 2-days delayed associations with ischemic heart disease mortality. The strongest association was found for particle NC in the size range 0.03-0.1 μm (7.1% increase in daily mortality with a 95%-confidence interval of 2.9%-11.5%, per an increase of 6250 particles/cm³). Results for surface and mass concentrations with a lag of two days indicated effect modification by air mass origin, whereas effects of particle NC were not modified.

Conclusions

Results show an elevated risk of cardiovascular mortality in Beijing from short-term exposure to particulate air pollution in the sub-micrometer range. Results also indicate that locally produced smaller particles and regionally transported particles may exhibit different effects in Beijing.     

Analysis of an energy efficient building design through data mining approach

Incorporating energy efficiency and sustainable green design features into new/existing buildings has become a top priority in recent years for building owners, designers, contractors, and facility managers. This paper intends to address why delivery of an energy efficient building is not just the result of applying one or more isolated technologies. Rather, it can best be obtained using an integrated whole building process throughout the entire project development process, which leads building designers to generate a large amount of data during energy simulations. The authors observed that even a simple energy modeling run generated pages of data with many different variables. The volumes of energy modeling data clearly overwhelm traditional data analysis methods such as spreadsheets and ad-hoc queries with so many factors to be considered. An integrated or whole building design process involves studies of the energy-related impacts and interactions of all building components, including the building location, envelope (walls, windows, doors, and roof), heating, ventilation and air conditioning (HVAC) system, lighting, controls, and equipment, which shows why it is so difficult to find the correlation between different systems. The objective of this research is to develop an energy efficient building design process using data mining technology which can help project teams discover important patterns to improve the building design. This paper utilizes the data mining technology to extract interrelationships and patterns of interest from a large dataset. Case study revealed that data mining based energy modeling help project teams discover useful patterns to improve the energy efficiency of building design during the design phase. The method developed during this research could be used to guide designers and engineers through the process of completing an early design energy analysis based on energy simulation models.