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brazilian monitoring for pesticide residues in food 2001-2010بقایای سموم در مواد غذای.

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مدیر و نویسنده و ترجمه و تحلیل از سید محمود جعفری

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(با تغییر اقلیم و اب با ارزش و  کمبود اب    water  در بسیاری از مناطق جهان وسموم گران قیمت ) نعمت خدا  ودست اورد بشر  وبا تکنولوزی نوین…محصولات غذای سالم تولید کنیم.) با انتخاب بهترین سموم وسمپاشهای مدرن با کیفیت ونازل های پیش رفته واقتصادی واستاندارد دنیا. باید اشنا شویم ومورد استفاده بهینه قرار گرفته شود. سموم غیر استاندارد وکنترل نشده مساوی با مرگ ناگهانی وتدریجی.
ما امده ایم به شما کمک کنیم  حتی یک دانه میوه  یک دانه گندم سالم.
حتی   ….   پیش گیری  ….    از مرگ   ….  یک موجود ….  زنده
به دست خود گیاهی می نشانم         به پایش قره ابی می چکانم…وسم وکودی استفاده می نمایم  که مردم وطنم وجهان از ان کمترین اسیب بینند؟

 

.غذای الوده به سموم کشاورزی یعنی کشتن مردم    .بی صدا . و بی مدرک.

, –   Brazilian monitoring programs for pesticide residues in food – Results from 2001 to 2010 Andreia N.O. Jardim,  Eloisa D. Caldas,

دانشجویان   کارشناسان و اساتید  وپزشکان

جوان و علاقمندان مطالب علمی و کابردی با امارهای دقیق ارزنده تهیه کنید  برای هشدارها ی: صدها بیماری  شناخته وناشناخته از برای انسان ودام وابزیان از جمله سرطان های معلوم ونا معلوم که علم پزشکی دنیا در ان بی جواب مانده است مربوط به ندام کاری انسانها.در ایند بیشتر خواهم گفت .این تحقیق در کشور برزیل انجام شده است.

و  ….باید گفت مجموع    ۱۳۵۵۶    نمونه از    ۲۲    نوع از  میوه ها و غلات از جمله برنج و لوبیا

  و خانواده سبزیجات     مورد تجزیه در کشور    ( برزیل  برزیل    برزیل   )  قرار گرفت   .برای پیدا کردن بقایای سموم  در محصول.   که انسانها نوش جان می کنند هر روز   .در سال ۲۰۰۱تا۲۰۱۰ باقی مانده سموم (در ۴۳ در صد )از نمونه ها پیدا شدو (۱۳ در صد) از انها نامعقول بود وباشرح فوق فقط( کمتر)( از ۳ در صد )از نمونه ها باقی مانده سموم (بالای حد  مجازMRL بود.        MAXIMIMUM. RESIDUE .LIMITS و حال توجه کنید.که در بین نمونه ها   سیب درختی    وفلفل سبز وقرمز درشت دلمه    و  میوه   پاپایا   که میوه  کرمسیری است     و توت فرنگی   . بیشترین    بقا یای سموم در انها یعنی بالای( ۸۰ در صد )سم  (دی تی کار با میت    DITHIOCARBAMATES ) و (ار گا نوفسفر     ORGANOPHOSPHORUS) در انها از راست به جپ (۴۲ در صذد )(۳۱ در صد)
مشخص شد.

ودر( ۲ سم دیگر)  بنام ( کار بندازیم  CARBENDAZIM ) و   (کلورپیر یفوس   CHLORPYRIFOS ) به نوبت از راست به چپ (۲۷ در صد)   و(۱۶ در صد )معنی دار وقابل قبول ومشکل ساز بود.
وحال نگاه کنید ببینید که چرا بعضی از کشورهادر نوع سم وکابرد سم و ومقادیر کود های شیمیای  در محصولات . قانون ومقرات در کشور وخرید محصولات از کشورهای دیگر حساب وکتاب ومقررات دارند و سخت گیر هستند وبعضی این علم واطلاع ندارند وبعضی بی تفاوت  میباشندواین چنین باید گفت که بیماریهای انسان وحیوانات اینقدر زیاد و ناشناخته شده است که همه پزشکان  معمولا وقتی سر در نمی اورند یا می اورندیک نظریه دارند وهمه میگویند سرطان بودکه اکثرا هم درست می گویند  وشاید هم اشتناه کنند.

لیکن :خیلی وقت ها نمی دانند چه نوع سرطانی  یا بیماری ما در اینده در باره انها سخن خواهیم گفت در همین سایت منتظر باشید .واین میوه های است که در بالا وضعیت ذغیره سم ودر صد سم یک بار دیگرمرور کنیم .نکته ای قابل ذکر است که اکثر    تجار وشرکتها :و کشاورزان ایرانی  وجهان سوم به دلایل مختلف که بعدا خواهیم گفت  از انتخاب سم ومیزان سم وزمان سم پاشی وبرداشت محصول  بعضا بی اطلاع و رعایت نکات فنی واستاندارد را  ساده گرفته ورعایت نمی نمایند اگر قبول ندارید ایمیل بزنید تا با هم کنکاش کنیم در مزرعه ها .
هشدار تجار که علم ریز کودهای شیمای وسموم کشاورزی ندارند نباید در این گونه تجارت ها سهم داشته باشند زیرااز نظر شرعی وقانونی  باید بسخگوی مردم وخدا باشند در این دنیا ودر اخرت…خداوند در کتابهای اسمانی می فرمایند ما پروندهای شما را دست خوتان خواهیم داد وان زمان است که خود اقرار می کنیید که چه کرده اید در این دنیا.

 

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Open Access Abstract

 

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A total of 13,556 samples of 22 fruit and vegetable crops, rice, and beans were analyzed within two Brazilian pesticide residue monitoring programs between 2001 and 2010. Pesticideresidues were found in 48.3% of the samples, and 13.2% presented some irregularity, mostly non-authorized active ingredient use. Less than 3% of the samples had residue levels above the MRL. Apple, papaya, sweet pepper and strawberry were the crops with the higher percentages of positive samples (about 80%). Dithiocarbamates and organophosphorus compounds were found in 41.6% and 30.8% of the samples, respectively. Carbendazim and chlorpyrifos were the pesticides most found (۲۶٫۷ and 16.1% of positive samples, respectively). Almost half of the samples analyzed had multiple residues (up to 10 residues), with multiple residues most common in samples of apple, sweet pepper and tomato. About 8% of positive samples contained up to four residues of the same chemical class, mainly organophosphorus compounds (18.6%, mostly in apple) and triazoles (16.1%, mostly in papaya and grape). In general, the scenario of pesticide residues in foods investigated within the Brazilian governmental monitoring programs in the last decade is similar to what has been found in other countries. However, the use of non-authorized active ingredients is a common practice among the farmers in the country, a problem that the government authorities have been trying to solve. A preliminary cumulative acute exposure assessment for organophosphates and carbamates in apple has shown that the intake by individuals ≥۱۰ years old accounts for 100% of the acephate ARfD, indicating a need to further investigate the exposure through the consumptions of other crops and group of pesticides, mainly for children. Highlights

► ۱۳,۵۵۶ samples were analyzed for pesticides, 48.3% were positive and 13.2% irregular. ► Less than 3% of the samples had residue levels above the MRL. ► About 80% of apple, papaya, sweet pepper and strawberry samples were positive. ► Dithiocarbamates and organophosphorus pesticides were found in over 1/3 of samples. ► About 8% of positive samples contained up to four residues of the same chemical class.   Keywords Pesticide residues;  Food;  Brazil 1. Introduction
Pesticide use is the most widely adopted pest management strategy to guarantee food supplies worldwide. In Brazil, one of the world’s major food producers, over 90% of farmers rely on pesticide use (IBGE, 2006), and the country has ranked first in pesticide use worldwide in recent years, with over 673 million tons applied in 2008 (ANDEF, 2009).

The basis for pesticide regulation in Brazil was set by Federal Law No. 7802, enacted in 1989, and later by Acts 4074/2002 and 5981/2006 (ANVISA, 2011a). These legal standards regulate all aspects related to pesticides, including registration, use, production, storage, transport and disposal. The pesticide registration process involves the Ministry of Health, through the National Sanitary Surveillance Agency (ANVISA), which is responsible for evaluating the impact of pesticide use on human health, and for the establishment of maximum residue levels (MRL);

 

the Ministry of the Environment, which evaluates the impact on non-human species; and the Ministry of Agriculture, Livestock and Food Supplies (MAPA), responsible for evaluating pesticide pest control efficacy and approving the product label. Brazilian MRLs are established based on supervised pesticide residue trials conducted throughout the country, and reflect the good agricultural practices used nationally, specified in the approved product labels. As of June 2011, 343 active ingredients had MRLs established for a variety of food commodities in the country (ANVISA, 2011b).

The Confusing World of Pesticides: A Primer

Two monitoring programs for pesticide residues in food of vegetal origin are currently in place in Brazil, aimed at evaluating compliance with national MRLs: the Program on Pesticide Residue Analysis in Food (PARA), coordinated by ANVISA, and the National Residue and Contaminant Control Program (PNCRC), coordinated by the MAPA. The first results of the PARA program were published by Oliva, Gemal, Nóbrega, and Araújo (2003), and reported the residue findings from 350 samples of tomato and strawberry collected in four Brazilian states from July to December, 2001. Caldas Tressou et al., 2006 and Caldas Boon et al., 2006summarized the PARA results for the 2001–۲۰۰۴ period for organophosphorus, carbamates and dithiocarbamate pesticides in nine food commodities evaluated. Additionally, Mauricio, Lins and Alvarenga (2009) described the strategies implemented by the MAPA in 2006 to increase the analytical standards of the official laboratories under the PNCRC, including the updating of instrumentation facilities and the increase in capacity-building.

 

The summary of the results obtained by the PARA program are periodically posted at the Agency website (ANVISA, 2011c), and those from the PNCRC were published in the official government gazette (Brasil, 2009a and ۲۰۱۰, p 3). These summaries are only available in Portuguese.
The objective of this paper is to present and discuss the results obtained by the PARA and the PNCRC pesticide residue monitoring programs for the period between 2001 and 2010. 2. Material and methods 2.1. The monitoring programs
From 2001 to 2007, the scope of the PARA program was to analyze 92 active ingredients (a.i.) in 9 food crops – apple, banana, carrot, lettuce, orange, papaya, potato, strawberry and tomato (ANVISA, 2011c). This scope was expanded in 2008 (to 167 a.i., with the inclusion of pineapple, rice, onion, bean, mango, sweet pepper, cabbage and grape), and in 2009 (to 234 a.i., with the inclusion of sugar beet, collard green and cucumber). The samples analyzed under the PARA were collected at local supermarkets and food distributors by the state sanitary surveillance agencies, and covered 24 of the 26 Brazilian states, and the Federal District.

 

The samples were sent fresh for analysis and arrived at the laboratory within 24 h after collection.
The PNCRC program of products of vegetal origin initiated its activities in 2006, analyzing samples of apple and papaya for export, and samples of these crops from local markets in subsequent years. Its legal basis was established in 2009 (Brasil, 2009b), when pineapple, banana, grapes, lemon,

melon, mango, strawberry, tomato, lettuce, and potato were included in the program. Potato data are not included in this paper due to problems in data reporting. Under the PNCRC, samples are collected by federal agriculture inspectors at packing houses in seven Brazilian states (Espírito Santo, Bahia, Pernambuco, Rio Grande do Norte, Santa Catarina, Rio Grande do Sul and Paraíba) and/or at the largest national distributor of fresh food, located in the city of São Paulo (CEAGESP – Companhia de Entrepostos e Armazéns Gerais de São Paulo). Apple, mango, papaya and grape samples were collected from both the packing houses and CEAGESP, and the other crops only from the latter. 2.2. Analytical methods
Five laboratories analyzed the samples collected within the PARA program, of which four are state laboratories. They were inspected and authorized by ANVISA to ensure compliance with ISO/IEC 17025 requirements; two laboratories are accredited by the competent Brazilian agency (INMETRO). Dithiocarbamates were determined as CS2 either by spectrophotometry (LOQ of 0.08–۰٫۴ mg/kg) or by gas chromatography (GC/FPD) (LOQ of 0.05–۰٫۳ mg/kg). The multiresidue Mini Luke extraction method (The Netherlands, 1996) was used for the other pesticide classes, using GC/FPD, GC/ECD, CG/NPD, GC/MS/MS or LC/MS/MS. LOQs vary among laboratories, matrix and compound, being 0.01 mg/kg in most cases. The highest (0.4 mg/kg) was reported for carbendazim in apple and sweet pepper and cypermethrin in sweet pepper, and the lowest (0.005 mg/kg) for carbendazim in pineapple, sugar beet, collard green, papaya, mango, cucumber, cabbage and grape, and tetraconazole in pineapple, sugar beet, mango, grape and cucumber.
Two ISO/IEC 17025 accredited laboratories analyzed the samples collected within the PNCRC program. Dithiocarbamates were determined as CS2 by GC/FPD (LOQ of 0.01–۰٫۰۷ mg/kg). Other pesticides were analyzed by multiresidue Mini Luke method using GC/ECD, GC/MS or LC/MS/MS. LOQ was 0.01 mg/kg in most cases, and the highest LOQ was 0.41 mg/kg for bifenthrin, captan, esfenvarelate and fenpropathrin in melon, strawberry and grape.

۳٫ Results
A total of 13,556 samples were analyzed for pesticide residues between 2001 and 2010 (Table ۱), of which 12,072 were from the PARA program (July 2001 to December 2009), and 1484 from the PNCRC (January 2006 to July 2010). Some samples collected between 2001–۲۰۰۲ and 2009–۲۰۱۰ did not contain the sampling data, so they were grouped. Laboratories that analyzed the samples in both programs used similar analytical methods with LOQs in the same range.   Table ۱٫
Samples analyzed by the Brazilian monitoring programs from 2001 to 2010, as percent of positive and irregular samples. YearSamples analyzedPositive samples, %aIrregular samples Total%bNA, %c,d>MRL, %cBoth, %c,e 2001/2002 1278 41.5 207 16.2 51.2 38.2 10.6 2003 1369 28.6 168 12.3 83.9 7.1 8.9 2004 1208 47.1 130 10.8 64.6 31.5 3.8 2005 1195 37.4 62 5.2 67.2 32.8 – ۲۰۰۶ ۱۰۴۹ ۵۷٫۳ ۱۱۸ ۱۱٫۲ ۷۴٫۶ ۱۶٫۹ ۸٫۵ ۲۰۰۷ ۱۳۷۳ ۵۷٫۰ ۱۷۵ ۱۲٫۷ ۷۶٫۶ ۱۶٫۶ ۶٫۹ ۲۰۰۸ ۲۱۹۴ ۵۱٫۴ ۲۵۰ ۱۱٫۴ ۸۳٫۱ ۱۲٫۴ ۴٫۴ ۲۰۰۹/۲۰۱۰ ۳۸۹۰ ۵۳٫۹ ۶۸۰ ۱۷٫۵ ۷۱٫۸ ۱۹٫۸ ۸٫۴ Total 13556 48.3 1790 13.2 72.1 20.6 7.4 a
Presence of at least one pesticide residue at levels > LOQ. b
Related to the total of samples analyzed each year. c
Related to the total of irregular samples each year. d
Non-authorized active ingredient. e
Presence of both non-authorized active ingredient and residues above the MRL. Table options
Prior to 2006, less than 50% of the samples analyzed contained pesticide residues (all samples from the PARA program), but from 2006 to 2010, the majority of the samples were positive for at least one pesticide (≥LOQ) (Table ۱). A total of 1790 samples (13.2%) were irregular (presence of a non-authorized a.i., or residue levels higher than the Brazilian MRL); irregular samples represented 27.3% of the positive samples. The periods of 2001/2002 and 2009/2010 had the higher percentages of irregular samples, representing 16.2 and 17.5% of the samples analyzed for each period, respectively, and 2005 the lowest (5.2%). When compared with the positive samples, higher percentages of irregularities were found in 2001/2002 (32%) and 2003 (43%).

 

 


The majority of the irregularities found for the period under study were related to the use of non-authorized a.i. (72.1%) (Table ۱), mainly methamidophos (256 samples), chlorpyrifos (207 samples) and dithiocarbamates (138 samples). For 2001/2002, 2004 and 2005, over one third of the samples had at least one residue above the MRL. The pesticides most frequently found above the MRL for the whole period were dithiocarbamates (121 samples), carbendazim (99 samples) and iprodione (39 samples). Approximately 7% of the samples presented non-authorized a.i., and also residues above the MRL.
Table ۲ shows the number and the percentage of positive and irregular samples for each crop analyzed under the programs. Apple and papaya were the crops with the highest number of samples analyzed, having also the higher percentages of positive samples (about 80%), with similar percentages found also for strawberry, grape and sweet pepper. Lemon and melon were analyzed only under the PNCR program (2009/2010) (31 and 21 samples, respectively). Sweet pepper was the crop with the highest percentage of irregularity (70.7% of the samples analyzed), mainly due to non-authorized organophosphorus compound use (163 samples;Table ۲), mostly methamidophos (103 samples). Strawberry represented 39.6% of irregular samples, from which 73.3$ with non-authorized a.i., mostly captan, procloraz and endosulfan. Over 60% of non-authorized use in lettuce was due to dithiocarbamates (withdrawn from the label in 2005). Only 4% of potato samples analyzed were irregular, mostly due to residues above the MRL (87.8%), a profile of irregularities clearly different from the other crops. Strawberry, grape and sweet pepper presented the highest percentages of irregular samples presenting both non-authorized use and residues above the MRL (>10%). Irregularities found in cabbage, sugar beet, onion, lemon and melon samples were due only to non-authorized use (Table ۲). In cabbage, this was mostly due to the presence of procymidone (20 samples).   Table ۲٫
Food commodities analyzed by the Brazilian monitoring programs from 2001 to 2010, as percent of positive and irregular samples. CropSamples analyzedPositive samples, %aIrregular samples Total%bNA, %c,d>MRLc, %Both, %c,e Apple 1750 79.9 107 6.1 82.2 16.8 0.9 Papaya 1545 82.3 173 11.2 46.2 47.4 6.4 Potatof 1222 25.9 49 4.0 12.2 87.8 – Orangef 1219 28.5 38 3.1 86.8 13.2 – Tomato 1154 59.8 158 13.7 63.9 27.2 8.9 Carrotf 1021 15.5 83 8.1 48.2 51.8 – Lettuce 1007 33.9 210 20.9 97.1 1.0 1.9 Strawberry 992 76.3 393 39.6 73.3 13.5 13.2 Banana 911 11.3 25 2.7 52.0 44.0 4.0 Beansf 301 55.1 6 2.0 50.0 50.0 – Ricef 298 18.5 15 5.0 93.3 6.7 6.7 Grape 286 82.2 98 34.3 62.2 21.4 16.3 Mango 284 30.6 9 3.2 66.7 33.3 – Pineapple 270 41.9 55 20.4 49.1 41.8 9.1 Cabbagef 268 18.3 43 16.0 100 – – S. pepperf 266 82.0 188 70.7 86.7 2.7 10.6 Onionf 263 1.1 3 1.1 100 – – Sugar beetf 172 32.0 37 21.5 100 – – Cucumberf 146 53.4 43 29.5 88.4 7.0 4.7 Collardf green 129 58.1 52 40.3 71.2 19.2 9.6 Lemong 31 74.2 3 9.7 100 – – Melong 21 28.6 2 9.5 100 – – Total 13556 48.3 1790 13.2 72.1 20.6 7.4 a
Presence of at least one pesticide residue at levels ≥LOQ. b
Related to the total of samples analyzed each year. c
Related to the total of irregular samples each year. d
Non-authorized active ingredient. e
Presence of both non-authorized active ingredient and residues above the MRL. f
Only PARA program. g
Only PNCRC program. Table options
Data from the PNCRC program shown in Table ۱ and Table ۲ only concern the period of 2006–۲۰۱۰٫ Table ۳shows the results of the PARA and the PNCRC for the crops analyzed in both programs during this period. In general, the PARA results showed a lower frequency of positive samples and a frequency of irregular samples over two times higher than the PNCRC program (17.9 and 8.0%, respectively). The number of samples analyzed in both programs was comparable only for apple and papaya, which showed similar frequencies of positive samples during the period. However, the frequency of irregular papaya samples collected by the PARA program was over 3 times higher than that from the PNCRC program (14.4 and 3.8% of the samples analyzed, respectively). In both programs, the majority of the irregular apple samples contained non-authorized a.i. (66.7 and 71.8%), while most of the irregular papaya samples contained residues above the MRL (55.8 and 59.2%) (data not shown). The number of samples analyzed by the PNCRC program for the other crops shown in Table ۳ was much smaller than those from the PARA program (less than 10%, in general), and comparisons between the two data sets may be misleading. Table ۳٫

Results obtained by the PARA and PNCRC monitoring programs from 2006 to 2010. CropPARA 2006-2009PNCRC 2006–jul 2010 Samples analyzedPositive samples, %aIrregular samples, %bSamples analyzedPositive samples, %aIrregular samples, %b Apple 560 84.1 2.7 690 87.8 5.7 Tomato 520 67.5 14.4 26 76.9 3.8 Strawberry 515 84.9 35.1 42 64.3 19.0 Lettuce 501 31.1 29.3 32 53.1 25.0 Banana 406 10.1 2.2 29 51.7 0.0 Papaya 396 89.4 19.4 540 92.0 9.1 Grape 266 84.2 36.8 20 55.0 0.0 Pineapple 240 43.3 20.4 30 30.0 20.0 Mango 261 27.6 2.3 23 65.2 13.0 Total 3665 60.3 17.9 1432 85.0 8.0 a
Presence of at least one pesticide residue at levels > LOQ; Non-authorized active ingredient. b
Presence of non-authorized active ingredient and/or residues above the MRL. Table options
Of the samples analyzed by the PNCRC, 934 samples (62.9%) were collected at packing houses (mostly commodities for export), and 550 samples at CEAGESP (for domestic consumption, including 8 samples of imported apples). The percentage of positive samples collected at CEAGESP (75.3%) was lower than that collected at packing houses (89%). However, only 2.9% of the packing house samples were irregular (2% non-authorized use), while 10.6% of the CEAGESP samples were in this situation (6.3% non-authorized) (data not shown).
Fig. ۱ shows the percentage of residues that exceeded the national MRLs, considering all the positive samples. In about 25% of the cases, residues were up to 50% higher than the MRL, and in the majority of cases (65%), reached up to 2.5 times the MRL(15% exceedance of the MRL). The three highest residues above the MRL were triazophos in tomato (2075% MRL of 0.04 mg/kg), propiconazole in rice (3340% of MRL of 0.1 mg/kg), and chlorpyrifos in potato (3400% MRL of 0.01 mg/kg).   Fig. ۱٫
Percentage by which the MRLs is exceeded in the samples analyzed of the Brazilian monitoring programs from 2001 to 2010. Dithiocarbamates had its LMR established as CS2 only as of 2003. Figure options
Most of the residues (51.3%) found in the positive samples analyzed were in the range of 0.01 to Fig. ۲ shows the residue levels found in the samples of the 10 crops with the highest percentage of positive residues (higher than 50% of the samples analyzed). The majority of the positive samples of cucumber and beans had residue levels Fig. ۲٫
Levels of pesticides found in the 11 highest positive crops samples analyzed by the Brazilian monitoring programs from 2001 to 2010. Figure options

Fig. ۳ shows the crops presenting multiple residues (up to 7 different a.i.), which represent 47.8% of the positive samples. Sweet pepper was the crop with highest number of samples with multiple residues (73.9% of positive sweet pepper samples), followed by strawberry (71.6%) and grape (70.2%). With exception of grape, all the crop samples shown in Fig. ۳ had mainly two residues. Eight grape samples had 8 residues, one had 9 residues and 2 had 10 different residues; one strawberry sample also had 8 different residues (data not shown). Fig. ۳٫
Crops with multiple pesticide residues in the samples analyzed by the Brazilian monitoring programs from 2001 to 2010, s % of positive samples. Figure options
Table ۴ shows the five main pesticides classes found in each commodity, and Fig. ۴ the main compounds found in all samples analyzed. Dithiocarbamates were the pesticides most frequently detected (41.6%, 2723 samples), mainly in lettuce, apple and tomato samples (Table ۴). Carbendazim, a benzimidazole fungicide, was the single compound most frequently detected (26.7% of the samples) (Fig. ۴).   Table ۴٫
Classes of pesticides most found in the Brazilian monitoring programs from 2001 to 2010, as % of positive samples. CropDTOPTRIPYCB Lettuce 71.3 18.5 3.5 7.6 2.3 Apple 67.7 51.7 4.0 0.7 6.7 Tomato 56.4 39.9 8.7 13.2 1.0 Collard green 46.7 21.3 5.3 40.0 0 Banana 45.6 6.8 3.9 3.9 10.7 Papaya 45.5 3.7 19.3 2.4 0 Carrot 36.1 23.4 24.1 0 0 Grape 29.8 11.1 44.7 23.4 0.4 Cucumber 29.5 16.7 6.4 17.9 2.6 Sweet pepper 26.1 67.4 5.0 40.4 5.0 Strawberry 25.2 15.1 5.9 18.4 1.1 Orange 14.4 56.5 0 5.2 0.9 Pineapple 11.5 3.5 6.2 19.5 0 Sugar beet 10.9 14.5 41.8 12.7 0 Rice 3.6 43.6 47.3 3.6 3.6 Potato 2.8 92.4 0 0 1.6 Beans 2.4 2.4 6.6 0.6 0 Mango 2.3 2.3 4.6 3.4 0 Cabbage 0 20.4 14.3 2.0 6.1 Lemon 0 17.4 8.7 8.7 4.3 Melon 0 16.7 0 16.7 0 Onion 0 100 0 0 0 Total 41.6 30.8 10.2 8.3 2.4

DT = dithiocarbamate; OP = organophosphorus; TRI = triazoles; PY = pyrethroids; CB = carbamates.
Table options   Fig. ۴٫
The 15 pesticides most frequently detected in the samples analyzed by the Brazilian monitoring programs from 2001 to 2010. Figure options
All crops had at least one sample with one organophosphorus insecticide, a class of compounds found in 2017 samples, about one third of all positive samples (Table ۴). Over 90% of the positive potato samples contained at least one organophosphorus compound, and the three positive onion samples analyzed contained only organophosphorus compounds (non-authorized use in all cases). The four organophosphorus compounds most frequently found in the samples analyzed were chlorpyrifos, methamidophos, acephate and dimethoate (Fig. ۴), representing 15.4% of the residues.
Triazoles were present mostly in sugar beet, grape and rice (over 40% of the positive samples; Table ۴), with tebuconazole and difenoconazole the most frequent compounds found within this class (Fig. ۴). Pyrethroids, mainly fenpropathrin (Fig. ۴), were found in about 40% of positive collard green and sweet pepper samples (Table ۴). Compounds from the carbamate class were found in 2.4% of the samples analyzed, being present in 10.7% of the banana samples (Table ۴). Carbaryl was the carbamate most found (115 samples; 1.8% of positive samples), mainly in apples (89 samples).
Table ۵ shows the crops with samples containing up to four residues of the same chemical classes. Multiple residues of organophosphorus compounds were found in 18.6% of the samples positive for these compounds, followed by triazoles (16.1%). Apple was the crop with the highest number of samples in this situation (154; 11% of the positive apple samples), followed by sweet pepper and tomato, with 91 and 89 samples, respectively. Papaya and grape were the main crops with samples with multiple residues from the triazole class (37 and 40 samples, respectively). Fifty four samples had residues of organophosphorus compounds plus carbamates, compounds known to be inhibitors of the enzyme acetylcholinesterase (AChE), mostly apple. No samples of potato, banana, mango, onion, cucumber, lemon and melon contained multiple residues of the same class. Table ۵٫

INM microbes

Crop losses due to pest & disease are problematic around the world. More than 30-50% of the yield is lost due to pests. Chemical pesticides have been able to control many of the pests over the past decades. However, issues of toxic residues in food/water/environment are threatening human & animal health. Chemical pesticides are also rendered inefficient due to resistance built-up in pests. This has necessitated search for bio-control agents, bio-pesticides and bio-metabolites.
Bio-pesticides are formulations of entomopathogenic (killing insects), fungicidal (killing fungi) and nematophagous (killing nematodes) microbes. Bio-pesticides control the pests by causing diseases. They are safe, residue free with zero pre-harvest intervals. Bio-pesticides are used as soil and foliar sprays. For best results bio-pesticides are incorporated into normal package of practices during farming. Main reason is create sufficient population density of bio-pesticide microbes which help reduce unnecessary sprays. For best results start early and check for compatibility with chemicals.

Samples with multiple residues from the same class found in the Brazilian monitoring programs from 2001 to 2010. Pesticide classNumber of samplesaNumber of multiple residues, crop (number of samples) 234 OP 375 (18.6%) Apple (131); tomato (59); sweet pepper (58); orange (28); strawberry (16); potato (10); papaya (6); lettuce (4); cabbage (4); carrot (4); pineapple (2); collard green (2); grape (1); bean (1) Apple (17); sweet pepper (15); tomato (7); orange (3); carrot (1) Sweet pepper (5); tomato (1) TRI 107 (16.1%) Papaya (36); grape (34); pineapple (6); strawberry (6); tomato (6); apple (4); rice (3); sugar beet (2); carrot (2); Sugar beet (1); grape (5); papaya (1) Grape (1) PY 48 (8.8%) pineapple (14); tomato (14); sweet pepper (13); strawberry (3); collard green; (2); apple (1) Collard green (1) 0 CB 4 (2.6%) Tomato (2); lettuce (1); apple (1) 0 0 OP + CBb,c 54 Apple (29); strawberry (2); sweet pepper (2); tomato (2); lettuce (1); rice (1); cucumber (1); cabbage (1) Apple (9); sweet pepper (4); strawberry (1) Sweet pepper (1)

OP = organophosphorus compounds; TRI = triazoles; PY = pyrethroids; CB = Carbamates.
a
% related to the number of positive samples within the class. b
The positive samples for OP and CB contained only one CB residue. c
One sweet pepper sample presented 4 OP residues and 1 CB. Table options   ۴٫ Discussion
The Brazilian monitoring program data evaluated in this study show that 48.3% of the 13,556 samples analyzed from 2001 to 2010 were positive for at least one pesticide residue. Apple, papaya, grape and sweet pepper were the crops with the highest percentage of positive samples (around 80%). Irregularities found in 13.2% of the samples were mostly due to the presence of non-authorized a.i., and 2.7% of the samples analyzed had residue levels above the Brazilian MRL. Samples collected at farm packing houses within the PNCRC program were more likely to contain residues than those from food distributors, as expected, due to the degradation of residues that occurs between harvesting and sales. Packing house samples also had fewer irregularities, probably because most of the crops in these facilities are destined for export, and are likely to be subject to restricted pesticide use.
The high prevalence of non-authorized pesticide use in Brazil found in this study is in part due to the profile of the country’s agricultural population and to the minimal phytosanitary support given to certain crops. Most Brazilian food growers have low levels of education (over 40% are illiterate) and receive limited technical support (IBGE, 2006, p. 1–۷۷۷), do not read the pesticide labels or do not understand their content, and are economically vulnerable (Recena and Caldas, 2008, Recena et al., 2006 and Waichman et al., 2007). In many cases, their decisions regarding which pesticides to use rely strongly on their previous experience, on costs, and on product availability on the farm (Recena & Caldas, 2008). For instance, over 100 a.i. are registered for use on tomato (8.7% of samples with non-authorized a.i.), including ten organophosphorus compounds and four dithiocarbamates (MAPA, 2011), which are the pesticides most found in the samples with irregularities. On the other hand, between 20 and 30 pesticides are registered for sweet pepper, collard green and lettuce (61, 28.7 and 20% of the samples analyzed with non-authorized a.i., respectively). It is likely that a farmer will use a pesticide registered for tomato in other crops also grown on the property, regardless of its registration status. In order to minimize non-authorized pesticide use on minor crops, the Brazilian Government has accepted, as of January 2010, the extension of the MRL to all crops within a group based on supervised residues analyses conducted only on representative crops for that group (INC ANVISA/IBAMA/MAPA 01/2010). For example, a MRL set for tomato could be extended to sweet pepper.
The results found in this study are within the range of those found for pesticide monitoring programs conducted elsewhere. The 2008 European Union (EU) program (78 active ingredients in 11,610 samples of nine crops from 29 countries) showed 35.9% of positive samples, and 2.2% of the samples exceeding the MRL (EFSA, 2010). In the Netherlands, 5.9% of the 4344 samples analyzed, mostly fruit and vegetables, had residues above the MRL (VWA, 2008). In Belgium, 65.7% of the 1413 fruit and vegetable samples were positive, and 6.1% had residues above the MRL (AFSCA, 2008). In Poland, 2.2% of the 5340 samples analyzed in 2004–۲۰۰۷ had residues exceeding the MRL (Góralczyk et al., 2009). Results from the 2000–۲۰۰۸ Italian program showed 3.2% of the 6947 samples with residues above the MRL (Zicari, Soardo, Cerrato, & Rivetti, 2011). Pesticide analysis of 724 fruit and vegetables samples imported from South America to Denmark, Estonia, Finland, Norway and Sweden showed over 70% of positive samples, and 8.4% with residues above the MRL (Hjorth et al., 2011). About one third of these samples were from crops imported from Brazil, 9.2% of them having residues above the MRL. In the 2008 USFDA Program, 42.2% of the 3656 fruit and vegetable samples were positive and 3.5% were irregular, mostly for the presence of non-authorized a.i. in imported commodities (USFDA, 2008). In Australia, 98.9% of the 974 samples of five horticulture crops analyzed in 2009/2010 were in compliance with the relevant standards (DAFF, 2011).
Dithiocarbamates (MRLs from 0.1 to 3 mg/kg CS2) was the pesticide class most found in the Brazilian monitoring programs (41.6% of positive samples). This incidence is much higher than that found in Canada (32.3%; Ripley, Lissemore, Leishman, Denommé, & Ritter, 2000) and the EU (7.6%; EFSA, 2010). Currently, five dithiocarbamate compounds are registered in the country. Mancozeb is the most used (about 3000 tons a.i. in 2009; Rebelo et al., 2010, 84 pp.), registered for 33 food crops (ANVISA, 2011b), being probably the main source of CS2 detected in the samples. Metiram, the second most used (about 1000 tons in 2009, Rebelo et al., 2010, 84 pp.), and propineb are registered for 12 and 8 food crops, respectively. Metam sodium and tiram are used only in soil and/or seed treatment, modes of application that, in most cases, do not lead to residues in food.
About 30% of the positive samples contained organophosphorus compounds, a higher percentage in comparison with the 2003-2005 Dutch program on 11,873 fruit and vegetable samples (15%, Boon, van der Voet, van Raaij, & van Klaveren, 2008). Chlorpyrifos was the second single compound most frequently detected in the Brazilian programs (7.8% of the samples), and the main organophosphorus compound detected. Chlorpyrifos was also the main organophosphorus compound detected in the 2004–۲۰۰۷ Danish monitoring (7.4% the samples; Jensen, Petersen, & Christensen, 2009), and was found in 8.6% of the samples in Europe (EFSA, 2010), 16.9% of samples of food imported to Europe (Hjorth et al., 2011), and in 42.7% of the 1150 peach samples analyzed in 2002–۲۰۰۷ in Greece (Danis, Karagiozoglou, Tsakiris, Alegakis, & Tsatsakis, 2011). Organophosphorous compounds are among the most acute toxic pesticides on the market worldwide, and their registration is being phased out or has been canceled in many countries, including Brazil. The use of methamidophos, the second most found organophosphorus compound in this study and the most used in the country in 2009 (5000 tons a.i.; Rebelo et al., 2010, 84 pp.), was prohibited in the country in July 2012 (RDC 1/2011; ANVISA, 2011a).
Among the triazole pesticides, tebuconazole and difeconazole were the main compounds found in the Brazilian monitoring programs. In Belgium, difenoconazole was the fifth pesticide most frequently found (Claeys et al., 2011), and tebuconazole and/or myclobutanil were the main triazoles detected in the European program (EFSA, 2010), in Canada (Ripley et al., 2000) and in Greek peaches (Danis et al., 2011). Fenpropatrin was the main pyrethroid compound found in the Brazilian monitoring program (3.4% of positive samples). In Egypt (Dogheim, El-Marsafy, Salama, Gadalla, & Nabil, 2002), Denmark (Poulsen & Andersen, 2003), and Canada (Ripley et al., 2000), cypermethrin was the main pyrethroid found in the food samples analyzed. Although detected in less than 3% of the positive samples in Brazil, cypermethrin was the second a.i. most used in the country in 2009 (over 50.000 tons), following glyphosate (Rebelo et al., 2010, 84 pp.).
Almost half of the positive samples (47.8%) had multiple residues, with grape being the crop with the highest number of residues in a single sample (of up to 10). Grape samples were also found to have over seven different pesticide residues in Egypt (Dogheim et al., 2002), Europe (Hjorth et al., 2011), and Canada (Ripley et al., 2000). In the EU Program, a single table grape sample had 26 pesticides (EFSA, 2010). Over 8% of the positive samples had at least two residues from the same chemical class, mainly from the organophosphorus and triazole classes. About 19% of the samples containing organophosphorus compounds had at least two residues of this class, a lower percentage than what was found in the Netherlands (22.2%) (Boon et al., 2008). Multiple residues are expected in some crops since the application must alternate among pesticide classes to prevent pest resistance. However, the presence of multiple residues may also suggest that principles of good agriculture practice are not being respected (EFSA, 2010).
The use of pesticides is necessary for pest management and the presence of their residues in food is unavoidable. However, these compounds are toxic to humans at certain levels and their presence in the diet may be a health concern to humans (Bjørling-Poulsen et al., 2008, Breckenridge et al., 2009, CODEX (Codex Alimentarius), 2009, Mendes et al., 2005, Menegola et al., 2006 and USEPA, 2001). In addition to providing data to assess whether the product is being applied to the crop according to the instructions on the approved labels (compliance with MRL), pesticide residue monitoring program data can also be used to assess the human health risk from exposure to pesticide through the diet (Claeys et al., 2011, Caldas and Souza, 2004, Jensen et al., 2009 and Katz and Winter, 2009). Furthermore, the cumulative exposure to multiple residues with the same mechanism of action (organophosphate and carbamates, AChE inhibitors, and triazoles, sterol 14-demethylase inhibitors) can lead to unsafe intake of these compounds in the diet (Caldas Boon et al., 2006, Caldas Tressou et al., 2006, EFSA, 2010 and USEPA, 2001).
We conducted a preliminary cumulative acute exposure assessment for the AChE inhibitors in apple, the commodity with the highest number of samples analyzed by the monitoring programs, one of the crops with the highest frequencies of positive samples and the one with the highest number of samples with multiple organophosphate and organophosphate plus carbamates residues. In this estimation, we calculated the equivalent residue levels in a sample, expressed as the index compound (acephate), by multiplying the level of the AChE inhibitor compound detected by its relative potency factor (RPF) calculated by Caldas, Boon, and Tressou (2006) and Boon et al. (2008, for fenthion only). The cumulative acute exposure was estimated using the FAO/WHO Joint Meeting on Pesticide Residues methodology to estimate the short-term intake of pesticides at the international level (FAO, 2003). The highest equivalent residue found in apple in the monitoring programs during the period of 2005–۲۰۱۰ was used as the HR (0.387 mg/kg, as acephate). The large portion (600 g; 97.5 P of apple consumer days, mean body weight of 70 kg) was estimated from a dietary survey for individuals 10 years or older conducted by IBGE in 2008/2009 (34003 respondents on two non-consecutive days, 4426 apple consumer days; data not published). The calculated cumulative acute intake of AChE inhibitors by individuals ≥۱۰ years was 50 μg/kg bw, representing 100% of the acephate ARfD (50 μg/kg bw; FAO, 2002). This result indicates the need for expanding the assessment to other crops and pesticide classes, and to assess the exposure by children. Dietary risk assessments have been conducted previously in our laboratory on cumulative acute exposure to AChE inhibitors, and on chronic exposure to dithiocarbamates (Caldas Boon et al., 2006, Caldas and Souza, 2004 and Caldas Tressou et al., 2006). The latest data (2005–۲۰۱۰) from the Brazilian monitoring programs will be used to update the previous assessments, and also to estimate the cumulative exposure to the triazole fungicides, which were found as multiple residues in 16.1% of the samples containing these compounds. Acknowledgments
The authors would like to acknowledge the Toxicology Division of the Brazilian Health Inspectorate (ANVISA) and the Coordination for Control of Residues and Contaminants of the Ministry of Agriculture, Livestock and Food Supplies (MAPA) for providing the raw residue data on the PARA and PNCRC programs, respectively. This work was financially supported by the National Council for Scientific and Technological Development (CNPq) (Call CNPq/MAPA/SDA N° ۰۶۴/۲۰۰۸, Grant ۵۷۸۵۳۹/۲۰۰۸-۰). We thank the CNPq for supporting A. N. O. Jardim with a Ph.D. scholarship.
ANNEX. Compounds analyzed by the Brazilian monitoring programs from 2001 to 2010
۲,۴-D Acid Abamectin Acephate Acetamiprid Acibenzolar-S-methyl Alachlor Aldicarb Aldrin2 Allethrin Ametryn Aminocarb Asulam Atrazine Azaconazole1 Azinphos-ethyl2 Azinphos-methyl1 Azoxystrobin Benalaxyl Bendiocarb1 Beta-cyfluthrin Beta-cypermethrin Bifenthrin Bioallethrin Bitertanol Boscalid Bromacil Bromopropylate Bromuconazole Bupirimate1 Buprofenzin Cadusafos Captan Carbaryl Carbendazim Carbofenotion2 Carbofuran Carbosulfan Carboxin Chlordane1 Chlorfenapyr Chlorfenvinphos2 Chlorpyrifos-methyl Chlorthiophos ۱ Clethodim Clofentezine Clomazone Clothianidin Coumafos1 Cyanazine Cyanofenphos1 Cyazofamide Cyfluthrin Cymoxanil Cypermethrin Cyproconazole Cyprodinil Cyromazine Dazomet DDT total2 Deltamethrin Demeton-S-methyl Diafenthiuron Diallate1 Diazinon Dichlofluanid Dichlorvos Dicofol Dicrotophos1 Dieldrin1 Difenoconazole Diflubenzurom Dimethoate (dimethoate +omethoate) Dimethomorph Diniconazole1 Disulfoton Dithiocarbamate Diurom Dodemorph1 Endosulfan Endrin2 Epoxiconazole Esfenvalerate Etefon Ethiofencarb2 Ethion Ethoprophos Etofenprox Etrimfos2 Famoxadone Fenamiphos Fenarimol Fenazaquin1 Fenbuconazole1 Fenhexamid1 Fenitrothion Fenoxycarb1 Fenpropathrin Fenpropimorph Fenpyroximate Fenthion Fenvalerate Fipronil Flazasulfuron Fluasifop-p-buthyl Flufenoxuron Fluquinconazole Flusilazole1 Flutriafol Folpet Fonofos1 Forchlorfenuron1 Fosthiazate Furathiocarb Halosulfuron HCH(alfa+beta+delta) Heptachlor Heptachlor – epoxide1 Heptenophos1 Hexachlorobenzene (HCB) Hexaconazole Hexazinone Hexythiazox Imazalil Imibenconazole Imidacloprid Indoxacarb Iprodione Iprovalicarb Kresoxim methyl Lambda-cyhalothrin Malaoxon Malatione Metalaxyl Metamitron Metconazole Methamidophos Methidathion Methiocarb Methomyl Methoxychlor2 Methoxyfenozide Metolachlor Metribuzin Mevinphos Mirex Monocrotophos2 Monuron Myclobutanil Neburon Nitenpyram Nuarimol Oxadixyl2 Oxamyl2 Oxyfluorfen Paclobutrazol Paraoxon-methyl Parathion -ethyl Parathion-methyl PBO (piperonyl – butoxide) Penconazole1 Pencycuron Pendimethalin Permethrin Permethrin Phenothrin Phenthoate Phorate Phosalone Phosmet Phosphamidon2 Picloram Picoxystrobin Pirifenox2 Pirimicarb Pirimiphos-ethyl1 Pirimiphos-methyl Prochloraz Procymidone Profenofos Prometryn Propamocarb Propargite Propiconazole Propoxur Prothiofos Pyraclostrobin Pyrazophos Pyridaben Pyridaphenthion Pyrimethanil Pyriproxyfen Quintozene Quizalofop -p-ethyl Rotenone1 Spinosad Spirodiclofen Spiromesifen Spiroxamine1 Sulfentrazone Sulfometuron-methyl Sulfosulfuron1 Sulfotep1 Tebuconazole Tebufenozide Tebufenpyrad1 Tebuthiuron Temephos Terbufos Tetraconazole Tetradifon Thiabendazole Thiacloprid Thiamethoxam Thiobencarb Thiodicarb Thionazin1 Tolylfluanid Tralkoxydim Triadimefon Triadimenol Triazophos Trichlorfon Trifloxystrobin Trifloxysulfuron Triflumizole Trifluralin Vamidothion2 Vinclozolin Zoxamide 1
Active ingredient never authorized in Brazil 2
Active ingredients previously authorized in Brazil Table options

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How to Easily Remove Pesticides From Your Fruits and Vegetables

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Food Control, 22 (2011), pp. 1701–۱۷۰۶ Article  |   PDF (165 K)  |  View Record in Scopus  |  Citing articles (16) IBGE, 2006 IBGE (Instituto Brasileiro de Geografia e Estatística)
Censo Agropecuário 2006. Brasil, Grandes Regiões e Unidades da Federação
(۲۰۰۶) Rio de Janeiro Jensen et al., 2009 B.H. Jensen, A. Petersen, T. Christensen
Probabilistic assessment of the cumulative dietary acute exposure of the population of Denmark to organophosphorus and carbamate pesticides
Food Additives & Contaminants Part A, 26 (2009), pp. 1038–۱۰۴۸ View Record in Scopus  |  Full Text via CrossRef  |  Citing articles (6) Katz and Winter, 2009 M. Katz, C.K. Winter
Comparison of pesticide exposure from consumption of domestic and imported fruits and vegetables
Food and Chemical Toxicology, 47 (2009), pp. 335–۳۳۸ MAPA, 2011 MAPA (Ministério da Agricultura, Pecuária e Abastecimento)
Agrofit. Sistema de Agrotóxicos Fitosanitários
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A national residue control plan from the analytical perspective–the Brazilian case
Analytica Chimica Acta, 637 (2009), pp. 333–۳۳۶ Article  |   PDF (455 K)  |  View Record in Scopus  |  Citing articles (25) Mendes et al., 2005 C.A. Mendes, G.E. Mendes, J.P. Cipullo, E.A. Burdmann
Acute intoxication due to ingestion of vegetables contaminated with aldicarb
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Postulated pathogenic pathway in triazole fungicide induced dysmorphogenic effects
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Pesticide monitoring programme of the Ministry of health of Brazil
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Results from the monitoring of pesticide residues in fruit and vegetables on the Danish market, 2000–۰۱
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Pesticides exposure in Culturama, Brazil–knowledge, attitudes, and practices
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Pesticide residue on fruits and vegetables from Ontario, Canadá, ۱۹۹۱–۱۹۹۵
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Monitoring program report – Fiscal year 2008
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Do farmers understand the information displayed on pesticide product labels? A key question to reduce pesticides exposure and risk of poisoning in the Brazilian Amazon
Crop Protection, 26 (2007), pp. 576–۵۸۳ Zicari et al., 2011 G. Zicari, V. Soardo, E. Cerrato, D. Rivetti
Results from the monitoring of pesticide residues in fruits and vegetables marketed in Piedmont (Italy), 2000–۲۰۰۸
Ig Sanita Pubbl, 67 (2011), pp. 149–۱۶۸ View Record in Scopus  |  Citing articles (1) Corresponding author. Fax: +۵۵ ۶۱ ۳۱۰۷۱۸۷۱٫
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Food Safety Magazine

When Consumers and Science Collide
When Consumers and Science Collide
During the last 45 years, while Americans have been taught not to trust institutions, the food business has grown into a large, complex system.

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Articles

FSM EDIGEST
From Sanitation to the Environment and Beyond: Your Free Guides to Foodservice Packaging
By Foodservice Packaging Institute
From Sanitation to the Environment and Beyond: Your Free Guides to Foodservice Packaging
ENEWSLETTER
A Look Back at 2015 Food Recalls
By Tiffany Maberry
A Look Back at 2015 Food Recalls
ENEWSLETTER
FSM Scoop: Pet Food Safety
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FSM Scoop: Pet Food Safety
FSM EDIGEST
Food Defense in the Age of Domestic Terrorism
By Robert A. Norton, Ph.D.
Food Defense in the Age of Domestic Terrorism
FSM EDIGEST
FSMA Update: Importing Food under the Foreign Supplier Verification Program
By Kathy Hardee, Esq.
FSMA Update: Importing Food under the Foreign Supplier Verification Program
FSM EDIGEST
The 2015 Food Recovery Summit: EPA’s Role in Reducing Wasted Food
By Mathy Stanislaus
The 2015 Food Recovery Summit: EPA’s Role in Reducing Wasted Food
SANITATION
An Investigational Team Approach to Plant Pathogen Contamination
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An Investigational Team Approach to Plant Pathogen Contamination
TESTING
Avoiding Allergens: It’s the Right Thing to Do
By Jeffrey Barach, Ph.D.
Avoiding Allergens: It’s the Right Thing to Do
HACCP
How Food Companies Can Modify Their Existing HACCP Plans into an All-Encompassing Food Safety Plan
By Amanda M. Yotty, M.Sc., John A. Marcy, Ph.D., Fred W. Pohlman, Ph.D., and Leslie D. Edgar, Ph.D.
How Food Companies Can Modify Their Existing HACCP Plans into an All-Encompassing Food Safety Plan
WATER
Process Water: Going Green Doesn’t Mean Less Safe
By Food Safety Magazine
Process Water: Going Green Doesn’t Mean Less Safe
PROCESS CONTROL
HACCP Issues and Impacts
By Regina Tihfon, M.Sc.
HACCP Issues and Impacts
TOXICOLOGY
Understanding the Difference
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Understanding the Difference
FSM EDIGEST
Crisis Management: Protecting Your Brand against Adverse FDA Publicity
By Meghan E. Tepas, Esq.
Crisis Management: Protecting Your Brand against Adverse FDA Publicity
FSM EDIGEST
Is My Sushi Safe? Why Government Regulation Is Coming to Sushi
By Cynthia LaBelle-Tun
Is My Sushi Safe? Why Government Regulation Is Coming to Sushi
FSM EDIGEST
Learning from Chipotle: Ensuring Food Safety at All Levels
By Wade Winters
Learning from Chipotle: Ensuring Food Safety at All Levels
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