The effect of postnatal depression on mother-infant interaction, infant response to the still-face perturbation, and performance on an instrumental learning task

A representative community sample of primiparous depressed women and a nondepressed control group were assessed while in interaction with their infants at 2 months postpartum. At 3 months, infants were assessed on the Still-face perturbation of face to face interaction, and a subsample completed an Instrumental Learning paradigm. Compared to nondepressed women, depressed mothers' interactions were both less contingent and less affectively attuned to infant behavior. Postnatal depression did not adversely affect the infant's performance in either the Still-face perturbation or the Instrumental Learning assessment. Maternal responsiveness in interactions at 2 months predicted the infant's performance in the Instrumental Learning assessment but not in the Still-face perturbation. The implications of these findings for theories of infant cognitive and emotional development are discussed.

Prediction of processed cheese instrumental texture and meltability by mid-infrared spectroscopy coupled with chemometric tools

The objective of this study was to determine the potential of mid-infrared spectroscopy coupled with multidimensional statistical analysis for the prediction of processed cheese instrumental texture and meltability attributes. Processed cheeses (n = 32) of varying composition were manufactured in a pilot plant. Following two and four weeks storage at 4 degrees C samples were analysed using texture profile analysis, two meltability tests (computer vision, Olson and Price) and mid-infrared spectroscopy (4000-640 cm(-1)). Partial least squares regression was used to develop predictive models for all measured attributes. Five attributes were successfully modelled with varying degrees of accuracy. The computer vision meltability model allowed for discrimination between high and low melt values (R-2 = 0.64). The hardness and springiness models gave approximate quantitative results (R-2 = 0.77) and the cohesiveness (R-2 = 0.81) and Olson and Price meltability (R-2 = 0.88) models gave good prediction results. (c) 2006 Elsevier Ltd. All rights reserved..

Sensory and instrumental analyses of volatiles generated during the extrusion cooking of oat flours

Three batches of oats were extruded under four combinations of process temperature (150 or 180 °C) and process moisture (14.5 and 18%). Two of the extrudates were evaluated by a sensory panel, and three were analyzed by GC-MS. Maillard reaction products, such as pyrazines, pyrroles, furans, and sulfur-containing compounds, were found in the most severely processed extrudates (high-temperature, low-moisture). These extrudates were also described by the assessors as having toasted cereal attributes. Lipid degradation products, such as alkanals, 2-alkenals, and 2,4-alkadienals, were found at much higher levels in the extrudates of the oat flour that had been debranned. It contained lower protein and fiber levels than the others and showed increased lipase activity. Extrudates from these samples also had significantly lower levels of Maillard reaction products that correlated, in the sensory analysis, with terms such as stale oil and oatmeal. Linoleic acid was added to a fourth oat flour to simulate the result of increased lipase activity, and GC-MS analysis showed both an increase in lipid degradation products and a decrease in Maillard reaction products.

Sensory and instrumental analysis of medium and long shelf-life Charentais cantaloupe melons (Cucumis melo L.) harvested at different maturities

The flavour profiles of two genotypes of Charentais cantaloupe melons (medium shelf-life and long shelf-life), harvested at two distinct maturities (immature and mature fruit), were investigated. Dynamic headspace extraction (DHE), solid-phase extraction (SPE), gas chromatography–mass spectrometry (GC-MS) and gas chromatography–olfactometry/mass spectrometry (GC-O/MS) were used to determine volatile and semi-volatile compounds. Qualitative descriptive analysis (QDA) was used to assess the organoleptic impact of the different melons and the sensory data were correlated with the chemical analysis. There were significant, consistent and substantial differences between the mature and immature fruit for the medium shelf-life genotype, the less mature giving a green, cucumber character and lacking the sweet, fruity character of the mature fruit. However, maturity at harvest had a much smaller impact on the long shelf-life melons and fewer differences were detected. These long shelf-life melons tasted sweet, but lacked fruity flavours, instead exhibiting a musty, earthy character.

A generalised Bayesian instrumental variable approach under student t-distributed errors with application

Bayesian analysis is given of an instrumental variable model that allows for heteroscedasticity in both the structural equation and the instrument equation. Specifically, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). Heteroscedasticity is treated by modelling the variance for each error using a hierarchical prior that is Gamma distributed. The computation is carried out by using a Markov chain Monte Carlo sampling algorithm with an augmented draw for the heteroscedastic case. An example using real data illustrates the approach and shows that ignoring heteroscedasticity in the instrument equation when it exists may lead to biased estimates.