Handbook of Pesticides: Methods of Pesticide Residues Analysis

CRC Press; 1 edition Sept. Be the first to review this item Would you like to tell us about a lower price? About the Author Leo M. Rathore, Algarh Muslim University, India. Share your thoughts with other customers. Write a customer review. Get to Know Us. English Choose a language for shopping. In addition, when the analyzed samples distributed between the four mainly season of each year, i. The selected plant foods will not give a for adverse biological effects to take place providing the residues of pesticides are controlled to be kept to a minimum.

Pesticides residue monitoring programs should then be implemented to assure the minimum allowable residue levels in plant foods, especially with regards to permethrin, endosulfan, dimethoat Rial-Otero et al. The results of the detected amounts of pesticide residues in the selected leafy vegetables, it is therefore clear that patterns of pesticide use are crop dependent: In addition, the most reasonable explanation for the highly detected pesticide residues in rocket, cabbage and radishes may be due to the intensive use of insecticides and the highly deposited amounted of the applied compounds on the broad leafs of such vegetables.

Overall, insecticides found in this study were similar to those found in other studies Cabras and Conte, ; Poulsen and Andersen, ; Dogheim et al. However, the detected amounts of the mentioned insecticides in these important leafy vegetables, make the necessary to continuing the pesticide residue monitoring programs which must be implemented to assure the minimum allowable residue levels in plant foods.

In addition, the obtained results clearly indicate the actual situation of the misuse of insecticides which may affect in turn at long period the consumers health. With the LLC and GCMS multiresidue method, the optimum conditions were met to extract and determined 86 pesticides in more than leafy vegetables samples less time and low detection limit 0. Also, the authors wish to thank the Al-Riyadh development company for kind helps with financial and incorporeal support during this work.

Pesticides and pathogen contamination of vegetables in Ghana s urban markets. Ecological Risk of Pesticides in Freshwater Ecosystems. Pesticide residues in grapes and wine in Italy. Food Additives Contaminants, A new multi-residue method for analysis of pesticide residues in fruit and vegetables using liquid chromatography with tandem mass spectrometric detection. Determination of the reference dose for chlorpyrifos: Proceedings of an expert panel. Pesticides heavy metals levels in Egyptian leafy vegetables and some aromatic medicinal plants.

New techniques for residue analysis of pesticides in foods. Pesticide residues in canned foods, fruits and vegetables: The application of supercritical fluid extraction and chromatographic techniques in the analysis. Exposures of children to organophosphate pesticides and their potential adverse health effects.

Environ Health Perspectives, Association of in utero organophosphate pesticide exposure and fetal growth and length of gestation in an agricultural population. Determination of pyrethroid pesticide residues in vegetables by pressurized capillary electrochromatography. Empirical findings and policy recommendations. Pesticide residues in vegetables and fruits monitored in SaoPaulo city, Brazil, Determination of 23 pesticide residues in leafy vegetables using gas chromatography-ion trap mass spectrometry and analyte protectants. Effects of food processing on pesticide residues in fruits and vegetables: European commission proficiency tests for pesticide residues in fruits and vegetables.

Monitoring of pesticide residues in vegetables marketed in Al-Qassim region, Saudi Arabia. Analysis of pesticide multi-residues in leafy vegetables by ultrasonic solvent extraction and liquid chromatography-tandem mass spectrometry. Results from the monitoring of pesticide residues in fruit and vegetables on the Danish market, Rapid determination of organophosphorous pesticides in leeks by gas chromatography-triple quadrupole mass spectrometry.

Variation in concentrations of the fungicides tebuconazole and dichlofluanid following successive applications to greenhouse-grown lettuces. Multi-residue screening of pesticides in vegetables, fruits and baby food by stir bar sorptive extraction-thermal desorption-capillary gas chromatography-mass spectrometry. Because this is a time-consuming process, most methods are validated less rigorously—perhaps by one cross-check either by investigators in the same laboratory or by one outside laboratory.

For example, the MRM used by the California Department of Food and Agriculture was developed in-house and had not been subjected to outside collaborative validation when put into service. The following discussion of monitoring activities for pesticide residues is based primarily on information that existed for and earlier. The committee realizes that changes in the design and scope of monitoring programs have occurred after but, unfortunately, information on more recent developments was not generally available for inclusion in the committee's discussion.

CSRS has its own programs through land-grant universities. The accomplishments and shortcomings of all programs in sampling and analyzing pesticide residues in foods were reviewed by the Office of Technology Assessment OTA, Much of the following description is based on that report. EPA does not monitor pesticide residues in food. The agency's residue chemistry section within the Office of Pesticide Program's Registration Division reviews registration data compiled by pesticide manufacturers, and its laboratories in Beltsville, Maryland, and Bay St.

Louis, Mississippi, may test the methods with spiked samples. EPA has for some time been studying the feasibility of combining the wide array of data bases in existence to maximize their utility for scientific and regulatory purposes. Together these sources provided data on pesticides in an estimated 49, samples.

In a report prepared for the EPA, Dynamac noted the difficulties encountered in attempts to compare these data bases, especially the differences in information reported and sampling methods. It made three fundamental recommendations intended to improve the utility of the data with minimum cost increases: EPA recognizes the need for uniform record keeping, sampling, and analytical methods in order to determine exposure and assess risk, especially for infants and children.

The utility of the data for estimating exposure and risk varies with the intended purpose of the monitoring programs. At present, EPA is evaluating the feasibility of drawing on the many and varied food intake and dietary exposure data bases to improve assessments of total human exposure. This information-gathering activity is one component of a larger effort to design a national human exposure survey that, among other things, will measure the route, magnitude, duration, and frequency of human exposure to environmental chemicals.

In May , FDA's MRMs included pesticides for which tolerance levels had been set, 74 pesticides with temporary and pending tolerances, 56 pesticides with no EPA tolerance levels those previously canceled or those used only in foreign countries , and metabolites, impurities,. McMahon and Burke, In its monitoring program in , FDA analyzed approximately 15, commodity samples in its 16 laboratories Figure Most samples were collected at random; the remainder were taken from targeted food sources after a violation or suspected violation.

Approximately 7, of the samples are domestic and 8, are imported. To accomplish this, FDA personnel purchase foods from local supermarkets or grocery stores four or five times per year in three cities in each of four different geographic regions of the United States. The cities are changed each year. Each market basket contains food items intended to be representative of the diet of the U.

The foods are prepared for consumption, e. Because of the limitation of the food intake data and residue monitoring methods, coverage is not complete. Human exposure to all pesticides cannot be estimated because some pesticides cannot be detected by the analytical methods used. It is even more difficult to derive estimates of human exposure for population subgroups. FDA's program has been criticized as being too slow in terms of analyses, in need of better sampling and enforcement of imported foods GAO, , and too limited in the numbers and types of pesticides detected GAO, a,b,c.

Despite these criticisms and the age of the data, this program proved to be an important source of information for the committee's purposes. If the TDS were improved, risk from exposure to dietary residues could be better assessed. Increased funding for TDS would almost certainly be required to improve it. Later in this chapter, the committee addresses how the sampling program might be restructured to provide the data necessary to estimate the exposures of infants and children.

FSIS in its National Residue Program annually analyzes approximately 50, samples for about residues of pesticides, animal drugs, and environmental contaminants in meat, poultry, and raw egg products. About one-third of the samples are analyzed for pesticides. Most samples are collected at random by FSIS inspectors located at slaughterhouses. Thirty-eight states monitor pesticide residues in food but vary widely in the number of samples they process and the purposes of their programs. Figure shows the range of sampling activity for 10 states in California has the largest and oldest program, which is designed to monitor the major raw commodities produced in, or imported into, the state.

Its purpose is to enforce tolerance levels for residues on both domestic and imported commodities. This program is administered by the California.

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FIGURE The number of food samples analyzed for pesticide residues in monitoring programs conducted by 10 states in Department of Food and Agriculture, which in analyzed 13, samples of fresh fruits, nuts, and vegetables State of California, Although routine postharvest monitoring is the largest component of the California program, efforts also include considerable preharvest monitoring for early detection and deterrence , focused monitoring to determine levels of specific chemicals of primary health concern , and foods to be processed samples destined for processing and taken up to the point of actual processing.

Florida's Department of Agriculture and Consumer Services began monitoring raw agricultural commodities for pesticide residues in That program is targeted to potential problem areas in contrast to the random sampling conducted in California. Many states have much more extensive pesticide analysis programs than is apparent in Figure , since they incorporate nonfood pesticide monitoring such as programs for farm worker health and safety and for groundwater contamination.

FeedCon provides information on contaminants in animal feeds;. FoodContam provides similar information for human foods. Participation in these programs is voluntary. At present, 21 states participate in FoodContam. There is an effort to enlist all states and agencies as data sources Minyard et al. The food processing industry has a special interest in pesticide residues in produce. If processed and packaged foods are found to contain illegal residues or residues with the potential to cause adverse health effects, entire lots may need to be recalled from distribution centers and even from grocer's shelves.

Tolerance levels must be established for any residue that concentrates during food processing e. The behavior of residues during processing is evaluated based on processing studies required of the pesticide manufacturer before registration. Nevertheless, continual surveillance is needed to detect any unanticipated behavior, such as the formation of a previously unrecognized metabolite Elkins, Approximately of these companies are involved in processing common foodstuffs. Since the food processing industry has used the NFPA Protective Screen Program—detailed recommendations for preventing illegal and unnecessary residues, published annually in the Almanac of the Canning, Freezing and Preserving Industry see, e.

The recommendations involve washing, blanching, and processing steps, and emphasize proper use of chemicals at the farm source. Many food manufacturers and trade associations maintain analytical programs and data bank resources to accomplish the same purpose wherever possible and generally use the same multiresidue procedures as FDA. In EPA enlisted the help of NFPA and other groups to determine the availability and quality of data on pesticide residues in foods.

Data were collected from 16 companies, including 3 major baby food companies, on more than 86, samples. Elkins, NFPA, personal commun. More than half of the samples 47, were classified as fruit. Vegetables 14, , tomatoes 8, , and meat 8, were the next highest categories.

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Potatoes were given a separate category. The balance of the samples 6, were combined under miscellaneous; these were mostly flour samples in which the pesticide of interest was ethylene dibromide EDB. In the fruit category, 8, of the samples were fresh or juice concentrates that were analyzed for Alar from to the present.

Of these, 8, were negative for Alar. From to the present, NFPA has been building a new pesticide residue data base that currently contains almost 74, samples, The balance is processed. Data from NFPA members usually pertain to crops on which the pesticide is known to have been used, but other data are random.

The data have been obtained from the food industry, from NFPA, and from other sources. The pesticide residues reported so far include aldicarb on bananas, potatoes, and oranges; benomyl on apples and tomatoes; guthion on tomatoes and peaches; methamidophos in tomatoes; malathion on wheat; and diazenon on apples and tomatoes. The concentrations reported were at or near the LOQ. Private, for-profit certification programs serve as third parties to verify the retailer's claims regarding residues on their produce.

Some of the programs also certify growers who comply with a full disclosure statement of chemical usage and allow sample testing of their produce at random. Some large farming operations and commodity groups are beginning to do their own monitoring to ensure acceptability of their produce. Commercial analytical laboratories have flourished in recent years, especially in analyses for pesticides and other toxicants in foods, water, soil, and waste sites. There has been no similar certification for food residue analyses by either the FDA or any other agency.

However, some states such as California are now instituting laboratory certification programs that involve inspection, performance standards, and adherence to GLPs. As a result of these certification programs, the data generated by these laboratories are becoming more consistent than in the past and promise greater reliability and more standardized operating procedures in the future. All analytical laboratories government, academic, and private performing work of a regulatory nature must comply with GLPs as set forth in the Federal Register. In practice, this requires written protocols for.

A QA officer must oversee the analyst and analysis. Records must be kept so that an outsider can reconstruct the analysis, including calculation of final results. Because the GLPs and the quality assurance and control procedures are relatively recent developments, the quality and completeness of recent data may differ considerably from those produced from analyses done 3 or more years ago Garner and Barge, In the past, for example, a zero was entered into the NFPA data base when no residue was detected, and the zero was entered into the NFPA data base when no residue was detected, and the zero was averaged with the positive values.

Today, the term None Detected replaces the zero and the method's detection limit is stated. Furthermore, NFPA data were sometimes obtained by nonstandard methods e. At present, however, NFPA is requiring that each contributor of data complete a residue report form for each reported pesticide-food combination.

Among the information required are the analytical method used, detection limits, quantitation limits, and recovery information. Thus, NFPA's findings have added considerably to the data base on exposure to residues in food because the samples were "as-served," finished products, and the ongoing effort promises to be even more useful because of the new requirements. MRMs used by individual agencies or laboratories may be modified, usually are not peer reviewed, and usually are not externally validated. Although this does not necessarily make them less reliable or of lesser quality than standard methods, the lack of external quality assurance.

Improvements can be seen as a growing number of analytical laboratories adopt GLP.

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Compliance data may have the best quality because they require more stringent methodological control. In general, the lack of quality control procedures limits assessments of data quality. Confidence intervals cannot be assigned to monitoring results because of the general lack of sample replication, and degrees of uncertainty cannot be clearly defined. All residue determinations are subject to error caused by limitations in the training or skill of the analyst, in laboratory glassware and other equipment, in the reference standards used as the basis for quantitation, and in the instruments chromatographs and spectrometers used in the final determination.

Error is also partially attributable to difficulty in identifying a relatively low response above a high and variable background noise from nonpesticide materials in the sample. In most cases, this is quite acceptable for laboratory validation of a new method. Such errors can be dealt with by running a larger number of replicate samples—a costly solution that is not often used.

Another source of error or uncertainty is the large, difficult-to-gauge variability due to sampling. This variability may be small in well-designed field experiments in which a chemical is applied by a calibrated sprayer to a uniform stand of grapes, or it may be unknown but almost certainly large when samples are taken from large shipping bins of grapes from several fields treated with different chemicals and applied by a variety of spray equipment.

It is difficult to estimate the sampling error in random sampling of a field or lot, especially because of differences in the training of personnel and sampling protocols. This is in addition to the inherent variability of residues due to uneven field applications of pesticides to the commodity of interest. Thus, a residue analysis that yields a 1-ppm level should be assigned a range of 0.

This error tends to swamp. This can be seen in Table , which shows the consequences of averaging fictitious residue data when nondetects are assumed to be at the LOQ, zero, or one-half the LOQ. The limitations of the residue data derive also from the lack of consistency among methods used for sampling, analyzing, and processing residue data.

The lack of commonality among the analytical methods used by agencies to monitor food for residues, in the number of chemicals included in the studies, especially metabolites and degradation products, or in the limits of detection of the methods impedes comparability of data and limits the utility of the data for exposure assessment. Thus the basic validity of the sample, including the extent to which it represents the population sampled, is frequently difficult to assess.

This contributes to the uncertainty in the final residue report. Federal, state, and industry groups differ considerably in their processing and reporting of data on residue levels. Residues that exceed established EPA tolerance levels are subject to confirmation and are included in the residue reports. Residues below the tolerance levels are usually reported but are not always confirmed. When a given method includes chemicals that are not present above the LOD, these absences are not always specified in the final residue report.

In calculating averages, some laboratories use only positive data above the LOD , some include the LOD for nondetectables, and others enter a zero for nondetectables. The rigor with which positives and nondetectables are recorded, and positives are confirmed, varies from laboratory to laboratory. Thus it is difficult to judge the quality associated with individual residue results or averages.

These are some of the reasons why it is not always possible to assess a given data set or to include its data in calculating average dietary exposures of the U. Data are collected for different reasons and from clearly different populations. Random sampling of consumption data reflects overall estimates of dietary and pesticide intake. Surveillance or compliance samples are directed to problem areas suspected of violating tolerance levels and therefore involve intense appraisal of products to which the compounds have been applied. The biases that exist in terms of the number frequency and types of samples collected are apparent.

Negative observations are more frequent in a truly random sampling program. On the other hand, surveillance, targeted, or compliance sampling may provide primarily positive values. Residues are expected in these types of sampling because they are designed primarily to intercept violations of FIFRA and related federal and state codes. Identification, separation, and calculation of the discrete observation categories are essential, because data are drawn from clearly different populations.

Yet many residue report compilations do not discriminate between the categories, or reasons, for sampling. The results of many residue data sets are clearly skewed due to inadequate sampling plans or a heavy emphasis on pesticides or products that have high potential for violation or health risk. Sampling may be biased to seek positive results when application of the pesticides is known. Sampling intensity tends to decrease when the potential for a measurable residue does not exist, for example, when the pesticide is not used. This impedes assessment of residue exposure of children or infants, whose primary food items may not be sampled frequently enough to provide a broad data base of residue information.

A lack of detectable residues may be an important signal that the compound is not used because of a lack of approval, local practice, or lack of a need to control pests. Several factors may lead to uneven, or no, use of a pesticide, even when it has been granted regulatory clearance. Prominent among these are climatic conditions, agricultural practices, and economic exclusion. Because pesticide costs account for a relatively large portion of the total cost of growing crops, unneeded pesticides or excessive quantities of pesticides are rarely used and expensive products are replaced by less costly compounds when available.

Furthermore, pesticide usage may be governed by recommendations issuing from a state. Agricultural practices can also be influenced by regulatory matters, consumer attitude e. Approvals may have been terminated for a specific use of a compound. Integrated pest management programs also favor some chemicals over others, or result in the increasing substitution of nonchemical control measures for chemical compounds.

When applied according to recommendation and practice, some pesticides are used to maintain soil conditions and are not absorbed by the plants. For example, when applied to soil according to specifications, aldicarb maintains soil activity and is not absorbed systemically by all produce.

Some pesticides dissipate so rapidly that residues are usually not detectable at harvest. Knowledge of the relationship between residue level and the amount actually consumed is incomplete. This stems from a generally inadequate understanding of residue behavior during the storage, processing, and preparation of foods as influenced by biological constituents, pH, temperature, moisture levels, and heat treatment.

Data on residue behavior provided by registrants are not adequate. Extrapolation of the limited data to population subgroups may be subject to major sources of error. Because more water is consumed per kilogram of body weight than any other item in the diet see Chapter 5 , it is an important medium to consider in assessing total dietary exposure.

For the pesticides examined in the Nonoccupational Pesticide Exposure Study Immirman and Schaum, , "exposure [to pesticides] from drinking water appeared to be minimal. Moreover, no single survey of pesticides in food commodities has included both surface and groundwater sources of drinking water. As a consequence, it is not yet possible to estimate with any degree of certainty all the variations that must be considered in assessing dietary exposure to pesticide residues in water used in the processing and preparation of foods.

The data that have been produced are discussed in the following paragraphs. This source of water has been the subject of several studies. Hallberg reported that residues of 39 pesticides and their degradation products have been detected in the groundwater of 34 states and Canadian provinces. The sources of these data ranged from controlled field studies to ongoing programs to monitor public water systems. The pesticides most frequently reported were mobile or volatile compounds used in soil treatments, such as aldicarb and its products, which were detected in 24 states from California to Maine.

Also prominent were herbicides widely used in the humid regions of the corn belt. These included alachlor, atrazine and its products, cyanazine, dicamba, dinoseb, metolachlor, metribuzin, simazine, trifluralin, and 2,4-D. The most frequently detected pesticides were the triazine herbicides atrazine, cyanazine, and simazine. Most of the herbicides found in groundwater in these studies are still widely applied USDA, b ; however, many of the fumigants and nematicides are no longer in use.

According to a study conducted for the EPA by Williams et al. In a compilation of data from groundwater monitoring studies conducted by pesticide registrants, universities, and government agencies, Williams and colleagues confirmed detections of 46 pesticides in the groundwater of 26 states resulting from normal agricultural use and 32 pesticides in 12 states attributed to point sources or pesticides misuses. Most frequently reported were atrazine normal use, 13 states; point source, 7 states and alachlor normal use, 12 states; point source, 7 states. The median and maximum concentrations reported as a result of normal use were 0.

Its purpose was to estimate the proportion of private rural domestic wells that contained detectable residues of alachlor and other herbicides atrazine, cyanazine, metolachlor, and simazine. The investigators used a three-stage, stratified, unequal probability selection procedure to obtain samples of 1, wells from the estimated 6 million private, rural, domestic. These wells serve 6. The wells located in areas of highest alachlor use and in areas of groundwater vulnerability had a higher probability of selection.

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Most counties were located in the midwest, northeast, and southeast, where pesticides containing alachlor are used primarily to control annual grasses and certain broadleaf weeds in corn, soybeans, and peanuts. The results indicated that , people in the sampled area are consuming water from wells with detectable concentrations of the compound. They also suggest that an estimated 36, people are exposed to minimum concentrations of 0.

The investigators found that Not only was atrazine detected in the highest percentage of the wells, it also exceeded the proposed MCL level by the highest percentage 0. Metolachlor and cyanazine were not found in levels higher than the MCL Holden et al. In the EPA completed a 5-year National Survey of Pesticides in Drinking Water Wells, the first survey undertaken to estimate the frequency and occurrence with which pesticides and their degradation products as well as nitrate were detected in drinking water wells EPA, The investigators sampled 1, drinking water wells for pesticides and products as a statistical representation of the more than Their findings indicate that The pesticides most frequently detected were the degradation products of the herbicide 2,3,5,6-tetrachloro-1, 4-benzenedicarboxylic acid dimethyl ester DCPA , which were found in 6.

Next highest was atrazine 1. Simazine, prometon, and DBCP were also found in both sources of groundwater, but with considerably lower frequency.

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Atrazine concentrations were 0. The EPA survey was designed to examine the relationships among contamination, groundwater vulnerability, and intensity of agriculture. Although the survey was stratified by patterns of pesticide use and groundwater vulnerability, the number of positive samples was generally too low to be considered representative of groundwater contamination or that could be used effectively by the committee in the estimation of exposure through groundwater. Surface water contributes The data on this source of the nation's water supply are even sparser than those for groundwater.

In addition to his study of groundwater, Hallberg compiled data on pesticide detections in raw and finished drinking water drawn from surface water supplies in Illinois, Iowa, Kansas, and Ohio. Less frequently detected were the herbicides butylate, dicamba, linuron, metribuzine, simazine, and trifluralin and the insecticides carbofuran and chlorpyrifos.

Seasonal variations in pesticide concentrations in surface water are striking Figure Baker and Richards reported that time-weighted concentrations of atrazine, alachlor, and metolachlor peaked during the late spring and early summer months in the Maumee River, the Sandusky River, and Honey Creek—all in Ohio. Atrazine, alachlor, and metolachlor concentrations exceeded maximum contaminant levels and health advisory levels during that period but were well below them during the rest of the year Figure Similar seasonal patterns were noted in statewide observations of atrazine concentrations in Illinois Good, In the Sandusky River, for example, a time-weighted mean atrazine concentration of 7.

In general, the highest mean concentrations for all pesticides in all rivers were highest in and , dropping in to levels lower than those recorded at the beginning of the observation period in The authors attributed these differences to variations in the timing, intensity, and amount of rainfall. During May and June the planting period , median concentrations of atrazine, alachlor, cyanazine, and metolachlor were 10 times higher than levels reported in March and April before planting and in October and November after harvest.

The occurrence of herbicides primarily molinate and thiobencarb in California's Sacramento River has been monitored extensively.

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Peak concentrations, which occur during May and June, have declined over the past decade because of the initiation of water management programs designed to minimize herbicide runoff from rice fields Department of Fish and Game, State of California, As demonstrated in Chapter 5 , water is an important component of the diets of infants and children. Water consumed by itself, water added to infant formula, and water used in the preparation of foods may represent a significant source of pesticide exposure by ingestion.

However, because of the limited information on pesticide residues in water and the lack of monitoring data on water intake by infants and children, quantitative risk estimates cannot be made at this time. The committee noted, however, that water residues tend to run in the low or sub-ppb levels when present, so that the contribution of waterborne residues to ingested food prepared by using water will generally be expected to be low, except in specific locations where water contamination is far above the U.

Infant formula is one of the most important processed foods fed to babies not breastfed because it is usually their sole source of nutrition during the first few months of life. Although pesticide application to some components of processed foods is likely to have occurred at some point e.

These invariably negative analytical findings are attributable to ingredient selection and processing procedures that reduce the potential for pesticide residues to appear in the finished product. In preparing ingredients for use in infant formula, manufacturers use numerous separation and purification procedures and heat treatments that reduce pesticide residues in raw agricultural commodities Swern, ; Pancoast and Junk, ; Considine and Considine, a,b; Snyder and Kwon, Chemical and physical processes of refinement and purification include washing, solvent extraction, filtration including carbon filtration , acidification, basic extractions, clarification centrifugation , crystallization, deodorization, evaporation, spray drying, and heat treatments such as ultra-high temperature UHT.

Because of processing and the relatively low levels of the individual ingredients in finished products e. Water is the principal ingredient by weight and volume of all liquid infant formulas. Ingredient water used in the processing of most infant formula is passed through activated carbon filtration columns. Analysis of influent and effluent for trihalomethanes THMs has shown the columns to be highly efficient at removing THMs from the water.

THMs are among the most difficult compounds to remove from water by activated carbon filtration McGuire and Suffer, Water treated in this manner is therefore considered by the manufacturers to be free of pesticide residues. Infant formulas are broadly classified into two categories: The manufacturing systems for producing the protein and carbohydrate ingredients used in the two formula types are quite different. The principal ingredients of infant formula based on cow's milk include cow's milk solids after milk fat is removed , lactose derived from cow's milk , and a combination of fats to provide an optimal lipid source for infants.

In some cases, whey proteins derived from cow's milk are also a part of the formulation. The composition of a typical infant formula based on cow's milk is shown in Figure The effects of processing e. The production of lactose and whey protein concentrate is illustrated in Figure Figure illustrates the production of condensed skim milk and nonfat dry milk from raw cow's milk.

Temperature extremes and highly effective purification processes, such as crystallization, can be expected to reduce any pesticide residues Buchel, ; Hartley and Kidd, ; Hayes, The likely effect of processing potential pesticide residues in raw cow's milk and the contribution of ingredients derived from cow's milk is illustrated in the following example. Assume that chlorpyrifos is present at its tolerance level of 0. Processing of milk to lactose could be expected to reduce that residue to 0.

Gelardi, Infant Formula Council, personal commun. Similarly, processing is likely to reduce the residue in raw milk to 0. A concentration factor of 2. Because infant formula contains 5. This calculation is based on the preceding worst case assumptions and the percentages of lactose and condensed skim milk in a typical cow's milk-based infant formula, as noted in Figure Thus, although condensed skim milk and lactose are major ingredients in infant formulas based on cow's milk, they are not expected to contribute greatly to potential pesticide residues. The primary sources of lipids used in these formulas are soy oil and coconut oil.

As with lactose and condensed skim milk, the contribution of these oil ingredients to pesticide residue levels in the finished product can be theoretically predicted. For example, the EPA tolerance concentration for malathion on soybeans is 8 ppm. Processing is expected to reduce the residue level in soybean oil to 4 ppm. And since infant formula based on cow's milk contains about 1. The composition of a typical soy-based infant formula is shown in Figure The principal ingredients include soy protein isolate and soy oil the predominant ingredients derived from soybeans as well as corn syrup solids, sucrose, and coconut oil.

Soy protein isolate is a specific protein fraction derived from soybeans. Following isolation, purification and modification are required to provide a protein source that will be nutritionally beneficial to infants. The soy protein isolation process involves several physical and chemical operations that effectively decrease any pesticide concentrations Figure