Control commodities

As with any residue method, a method used in an LSMBS method should include analysis of control commodities to demonstrate adequate selectivity and analysis of fortified control samples to demonstrate recovery. These aspects present a particular challenge in every food-based market basket survey, because, unlike field residue studies, control samples of known provenance are not available. 

A market basket survey, however, is unique in that untreated control commodities, as the term is normally used in residue studies, cannot be obtained. In a market basket survey, food commodities are collected at the consumer level and not from controlled field tests. By design, the cultural and treatment details for the collected commodities are expected to differ from sample to sample. This factor enables the collected commodities to represent the spectrum of conditions under which crops are supplied for human consumption. 

A second problem was that some lots of control commodities contained one or more extractable interferences, i.e., co-extractives that interfered with one or more of the analytes for the particular commodity and could not be removed during cleanup. This problem was addressed by either using controls from different sources for specific analytes or by blending controls to obtain a matrix with a sufficiently low level of interference to allow accurate determination of recovery. 

The primary use for methyl bromide is in the extermination of insect and rodent pests. Methyl bromide is used in space and stmctural fumigation except in California. The material is suitable for the fumigation of food commodities such as dried fmits, grain, flour, and nuts, and the faciHties in which these foods are processed or stored, as weU as for tobacco and many kinds of nursery stock. The usual dosage is 2—4 kg/28 m for 12—24 h. In soil fumigation methyl bromide controls weed seeds, nematodes, wireworms, and soil fungi. The usual dosage is 0.5—1 kg/9 m for 24 h at 16°C and above (82). 

Most of the resin systems used in commodity composites are slight modifications of the standard commercial mol ding grade material. Usually certain selected properties, such as purity or molecular weight range or distribution, are enhanced or carehiUy selected. In addition, special additives, such as flow controllers, thermal stabilizers, or antioxidants, are often added by the resin manufacturer prior to shipment. Many of the conventional or commodity-type resins used in thermoplastic composites are Hsted in Table 1 and the preparation of each of these is described. AH resins and blends described in the hterature are not Hsted, and the synthesis described is not the only procedure available, but is usually the most common commercial process. 

Polyolefins. The most common polyolefin used to prepare composites is polypropylene [9003-07-0] a commodity polymer that has been in commercial production for almost 40 years following its controlled polymerisation by Natta in 1954 (5). Natta used a Ziegler catalyst (6) consisting of titanium tetrachloride and an aluminum alkyl to produce isotactic polypropylene directly from propylene ... 

The immediate objective of an advanced control effort is to reduce the variance in an important controlled variable. However, this effort must be coupled with a commitment to adjust the target for this controlled variable so that the process is operated closer to the constraint. In large throughput (commodity) processes, very small shifts in operating targets can lead to large economic returns. 

Supplier partnerships or alliances have been used to control the cost of procurement. They are based on methods developed in Japan, initially in the automobile industry. These methods have been extended into the process industry and for the purchase of such items as compressor trains. Generally as originally conceived, they were intended mainly for commodity items. By using some innovative approaches, the concept of partnerships or alliances has been extended into the purchase of custom equipment. 

The solution to this problem has been to isolate the lactide and to polymerize this directly using a tin(ii) 2-(ethyl)hexanoate catalyst at temperatures between 140 and 160 °C. By controlling the amounts of water and lactic acid in the polymerization reactor the molecular weight of the polymer can be controlled. Since lactic acid exists as d and L-optical isomers, three lactides are produced, d, l and meso (Scheme 6.11). The properties of the final polymer do not depend simply on the molecular weight but vary significantly with the optical ratios of the lactides used. In order to get specific polymers for medical use the crude lactide mix is extensively recrystallized, to remove the meso isomer leaving the required D, L mix. This recrystallization process results in considerable waste, with only a small fraction of the lactide produced being used in the final polymerization step. Hence PLA has been too costly to use as a commodity polymer. 

The bulk chemical commodity producing companies (e.g., refineries, petrochemicals) have been practicing this philosophy for some time, using dynamic models to contain operational variability through feedback controllers, and employing static models to determine the optimal levels of operating conditions (Lasdon and Baker, 1986 Garcia and Prett, 1986). 

In petrochemical and bulk commodity chemical manufacture, real-time process control has been a fact of life for many years. There is considerable understanding of processes and control of process parameters is usually maintained within tight specifications to ensure statistical process control to within six sigma, or the occurrence of one defect in a million. This has been enabled through the use of real-time analytical capability that works with programmable logic circuits to make small changes to various process inputs and physical parameters as required. 

Occasionally the complete sample set of an individual commodity was not analyzed within a validation study. This is not a problem if the same study provides data on additional commodities belonging to the same matrix group. Consequently, the missing data, e.g., a second concentration level, are replaced, provided that control sample results are presented for all crops. 

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