ON THE FORECASTING OF ECONOMICALLY OPTIMAL APPROXIMATIONS TO LOAD DURATION CURVES

This paper develops a methodology for forecasting economically optimal approximations to the load duration curve. A dynamic programming algorithm serves as the basis of the optimal approximation, yielding discrete approximations over a known horizon. These approximations are related to a set of economic and weather variables and are, in turn, forecast. This forecast in conjunction with a forecast of the shape of a continuous load duration curve yields the requisite results. The approach is implemented and the results are acceptable.     

AROMA COMPOUNDS AS MARKERS OF WINE QUALITY IN THE CASE OF MALVAZIJA ISTARSKA YOUNG WINE

ABSTRACT

In order to investigate the relationship between sensory and gas chromatographic analysis data, and to establish if particular aroma compounds could be used as Malvazija istarska young wine quality markers, 30 samples of Malvazija istarska young wine were subjected to sensory evaluation and gas chromatographic analysis of aroma compounds. Linear regression and principal component analysis were applied in order to establish the relations between sensory evaluation scores and aroma compound concentrations in corresponding wines. The most important contributors to the characterization and differentiation of wines evaluated with higher sensory evaluation scores were isoamyl acetate, ethyl hexanoate, ethyl octanoate, ethyl decanoate, hexanoic acid, octanoic acid and decanoic acid. On the other hand, wines evaluated with lower sensory evaluation scores were characterized and differentiated by higher amounts of isoamyl alcohol and isobutanol. Mentioned esters and acids were also found to be the most important variables for the classification of these wines according to quality using stepwise linear discriminant analysis (SLDA). The evaluation of the SLDA model was performed by cross‐validation, obtaining an average percentage of correct classification of 100.0%, and of correct prediction of 89.3%. The results of this investigation suggest that above‐mentioned esters, acids and alcohols could be used as markers of Malvazija istarska young wine quality.

PRACTICAL APPLICATIONS

Wine aroma is one of the most important parameters responsible for its quality, and hence for consumer acceptance. Sensory evaluation is the most common technique for controlling the organoleptic quality of wine, but it is not always feasible, since it requires specific conditions, and a group of trained expert tasters that can only assess a relatively small number of wine samples for a day. Moreover, the subjectivity of panelists can affect the evaluation in a great measure. The approach proposed in this work suggests the use of a nonsubjective instrumental technique such as gas chromatography for the analysis of volatile aroma compounds as a complementary tool for wine quality control able to predict, confirm or to correct the results of Malvazija istarska young wine sensory evaluation. Although this model is yet far from being practically implemented, information obtained could be used as a starting ground. Moreover, it was assumed that the approach proposed in this work is likely to be applied successfully on the differentiation and classification of other types of wine according to quality.     

CLASSIFICATION OF AVOCADO BY FIRMNESS AND MATURITY

Table-ripe soft avocado cannot be shipped or stored for more than a few days. Thus, it is common practice to store and ship firm, tree-ripe avocado, while the consumer may soften the fruit as required. A human sorter cannot distinguish between a freshly picked firm avocado and a somewhat softer semiripe fruit, yet the accelerated evolution of ethylene by even several ripe fruits, may prematurely ripen a whole shipment. A sensor system, for nondestructive sensing of avocado firmness is presented, based on vibrationally exciting one side of the fruit, while measuring the transmitted vibration energy on its other side. Special signal processing hardware and software was developed for computing several alternative firmness indexes, highly correlated to the standard piercing force, destructive, test method. Optimal classification algorithms were developed, whereby the fruit may be classified into two or three firmness grades. In both cases, the actual contamination of the firm fruit class by soft fruits was only 3.3%, while the overall classification accuracy was about 90%.     

OPTIMAL OPERATION OF MULTIQUALITY WATER SUPPLY SYSTEMS-III: THE Q-C-H MODEL

A new technique for optimal operation of multiquality water supply systems is proposed. The technique, which is known as a Q-C-H (flow-quality-head) model, combines previously developed Sow-quality (Q-C) and flow-head (Q-H) models for optimal operation of water supply systems. The decision variables in the model are the operation of treatment plants, pumps and valves. The model minimizes the cost of water at sources, treatment, energy, and loss of agricultural yield when water quality is low. The model uses an iterative modified projected gradient method combined with the Complex method. As in the Q-C and Q-H models, the solution method is based on decomposition, dis-aggregation/aggregation approach, involving internal and external optimization. The decision variables of the external model are the flows in the loops of the network and the removal ratios at the treatment plants. The operation of the pumps and valves are the decision variables of the internal model. The method is demonstrated by application to an example problem.     

The matrix partial realization problem: an algebraic approach

This paper introduces a new approach to the multivariable partial realization problem. It formulates the problem in algebraic terminology, which sheds new light on the nature of the problem and our existing knowledge of it. The structure of the state space is analysed in terms of polynomial models. The main idea is analysis of the algebraic structure of the kernels of truncated Hankel maps. The elements of such kernels are directly related to the partial realization problem, in the sense that the columns of the denominator matrix of a partial realization are elements of such kernels. The numerator matrix is determined by an appropriate denominator matrix     

PEAK LOAD FORECASTING USING AN ADAPTIVE MODEL

In this paper two adaptive forecasting models are suggested. One model is based on a specification relating the forecast of a variable For some future period to a weighted average of a Free forecast of that variable and the current level of the variable. The second model makes a similar assumption with regard to its specification but relates the model's parameters to a set of economic and seasonal variables. This relationship allows one to forecast these parameters. The forecast parameters are in turn used to provide a forecast of the variable of interest.

When the two models are compared for a specific set of data, neither proves to be superior to the other though both are superior to a naive time series model. The choice of one model over the other ultimately rests on subjective factors.     

THERMAL DEATH PARAMETERS of ORANGE JUICE and EFFECT of MINIMAL HEAT TREATMENT and CARBON DIOXIDE ON SHELF-LIFE

Freshly squeezed, refrigerated orange juice has a relatively short shelf-life, which could be extended by minimal processing. D and z values of orange juice microflora were obtained using the capillary method, as well as a plate heat exchanger. the effect of low levels of CO₂ on the shelf-life of the juice was also evaluated. the D₆₀ value of typical orange juice flora was about 5 s and the z was 4–5C. A combination of minimal heat treatment (15 s at 60C) and 6 mM CO₂ extended the storage life of orange juice to 35 days at 4C.
Carbon dioxide flushed into a 10% headspace of 350 ml jars resulted in 6 mM dissolved CO₂ in the juice at 4C. This level of CO₂ extended the shelf-life of unpasteurized juice to 25 days at 4C and 10 days at 10C, as compared to 17 and 5 days without CO₂, respectively. No significant difference in organoleptic evaluations was found between minimally heat treated juices with or without CO₂ and fresh untreated juices without CO₂ during the first week of storage.     

OPTIMAL OPERATION OF MULTI-QUALITY WATER SUPPLY SYSTEMS-II: THE Q-H MODEL

This paper describes the second in a series of three models for optimal operation of multi-quality water supply systems. This second model, which is termed the Q-H (flow-head) model, seeks to determine the optimal operation of pumps and valves, and does not consider water quality aspects. However, the model belongs to the group of three models Tor multi-quality systems because it is one of the two building blocks (the other is the flow-quality Q-C) of a full-llow-quality-head (Q-C-H) model. This Q-H model is based on continuous representations of the head-flow and power-flow functions of the pumping stations, which in turn results in a continuous non-convex optimization model. For a given flow distribution in the network, Q₀, the Q₀-H model is solved for the optimal operation of pumps and valves. The flow distribution is then modified by changing the circular flows, using a projected gradient method combined with the Complex Method which employs the results of the Q₀-H solution, such that the locally optimal solution at the next point has a better value of the objective function. The process is continued until one of the termination criteria is satisfied. The circular flows thus serve as decision variables in an external problem, while in the internal problem the decisions are the operation of pumps and valves. The method is demonstrated by application to a sample problem.     

OPTIMAL STEP FUNCTION APPROXIMATIONS TO UTILITY LOAD DURATION CURVES

Utility load duration curves are often approximated by step functions, especially in the context of energy modeling and utility scheduling. This paper presents a method of constructing an optimal n-step approximation to a load duration curve.     

Heat Inactivation Kinetics of Trypsin Inhibitors During High Temperature-Short Time Processing of Soymilk

Heat treatment of soymilk was studied in the conventional batch boiling process and under High Temperature-Short Time (HTST) conditions. Reduction in total trypsin inhibitor was assayed enzymatically, and individual inhibitors, the Kunitz and the Bowman-Birk inhibitor, were assayed by ELISA technique. Standard first-order reaction kinetics and thermodynamics were applicable for inactivation, and results indicated that the mechanism was not protein unfolding, because entropy changes were zero or negative. The two inhibitors were inactivated at the same rate around 137°C. Therefore, a simple first-order kinetic model which gave a good, slightly conservative estimate of residual anti-trypsin activity under HTST conditions could be established.