Effect of Salicylic Acid, Calcium Chloride and Calcium Lactate Applications on Quality Attributes of Minimally-Processed 'Wonderful' Pomegranate Arils

'Wonderful' pomegranate arils were treated with 0.5% and 1% of calcium chloride, 0.5% and 1% of calcium lactate, and salicylic acid (1 and 2 mM), then treated and untreated (control) arils packaged in clean (sterilized) plastic containers. Fresh produce was then stored at stored at 5±1°C. Assessment of arils quality was carried out at 3-day intervals by evaluating the following quality parameters: appearance, decay, off odor, flavor, total soluble solids, acidity, anthocyanin and vitamin C content, firmness, colour development (L* value and hue angle), and microbial load. Pomegranate arils treated with salicylic acid, calcium chloride, and calcium lactate maintained a general good quality and appearance up to 12 days of storage at at 5±1°C, with no visible decay and off odor development. The total microbial population was lower in arils treated with salicylic acid, in comparison to treatments with calcium chloride, calcium lactate and control arils. All treatments scored above the limit of marketability, maintaining good quality of fresh-cut produce during storage. However, the use of salicylic acid and calcium chloride helped to keep a better overall quality of arils at the end of the 12-day storage at at 5±1°C

Resource Allocation in Activity Networks under Stochastic Conditions. A Geometric Programming-Sample Path Optimization Approach

We depart from the conventional ‘resource constrained project scheduling problem’, better known under the acronym RCPSP, by adding the element of randomness to the activities. In particular, we assume that each activity in the project has a work content that is exponentially distributed. The duration of an activity is then modeled as a function of the random work content and the allocated resources; the exact functional relationship can be arbitrarily defined. The stochastic optimization problem is approached by a method that is a ‘marriage’ between geometric programming (GP) and sample path optimization (SPO) that is flexible and can be implemented in a modular fashion.