Dried-Fruit Storage: An Analysis of Package Headspace Atmosphere Changes.
The quality of packaged dried foods depends on storage conditions and is determined largely by the initial gas composition inside and the transference through the container. The aim of this work was to analyze the O₂ and CO₂ concentrations within the internal atmosphere of the packaging. In this study, dried apricots and raisins were packaged in glass jars and polypropylene trays thermosealed with different polymers, and stored at 5, 15, 25, and 35 °C. Some trays were flushed with nitrogen just before sealing. In addition, the work relates to other previous papers to investigate the effect of these gases and packages on the stored products, and compares the influence of permeable and impermeable containers on food quality parameters. When packages were flushed with nitrogen before sealing, the O₂ level in the headspace increased until the outside O₂ concentration was reached. The CO₂ concentration increased over time, regardless of the initial atmosphere. Nitrogen had a great influence on the concentration of O₂, but not on that of CO₂. Finally, this paper shows that the films and initial gas used in this study had no significant effect on the quality of the stored dried fruit.
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis Hypogaea) Oils.
The intake of adulterated and unhealthy oils and trans-fats in the human diet has had negative health repercussions, including cardiovascular disease, causing millions of deaths annually. Sadly, a significant percentage of all consumable products including edible oils are neither screened nor monitored for quality control for various reasons. The prospective intake of adulterated oils and the associated health impacts on consumers is a significant public health safety concern, necessitating the need for quality assurance checks of edible oils. This study reports a simple, fast, sensitive, accurate, and low-cost chemometric approach to the purity analysis of highly refined peanut oils (HRPO) that were adulterated either with vegetable oil (VO), canola oil (CO), or almond oil (AO) for food quality assurance purposes. The Fourier transform infrared spectra of the pure oils and adulterated HRPO samples were measured and subjected to a partial-least-square (PLS) regression analysis. The obtained PLS regression figures-of-merit were incredible, with remarkable linearity (R² = 0.994191 or better). The results of the score plots of the PLS regressions illustrate pattern recognition of the adulterated HRPO samples. Importantly, the PLS regressions accurately determined percent compositions of adulterated HRPOs, with an overall root-mean-square-relative-percent-error of 5.53% and a limit-of-detection as low as 0.02% (wt/wt). The developed PLS regressions continued to predict the compositions of newly prepared adulterated HRPOs over a period of two months, with incredible accuracy without the need for re-calibration. The accuracy, sensitivity, and robustness of the protocol make it desirable and potentially adoptable by health departments and local enforcement agencies for fast screening and quality assurance of consumable products.