BIOCHAR APPLICATION ESSENTIAL SOIL MICROBIAL ECOLOGY

الأمراض الفطرية الوبائية التى تصيب أشجار المانجو

كتاب أمراض النبات 2011

تحميل

Patulin in Apple Juice, Apple Juice Concentrates and Apple Juice Products

http://www.fda.gov/Food/FoodborneIllnessContaminants/NaturalToxins/ucm212520.htm

I. Introduction

Patulin is a mycotoxin that is produced by certain species of Penicillium, Aspergillus and Byssochylamys molds that may grow on a variety of foods including fruit, grains, and cheese. Patulin has been found to occur in a number of foods including apple juice, apples and pears with brown rot (Harwig et al. 1973, Brain et al. 1956), flour (Hasseltine and Graves, 1966), and malt feed (Ukai et al. 1954). However, given the nature of the food, the manufacturing processes, or consumption practices for many foods, patulin does not appear to pose a safety concern, with the exception of apple juice (Fritz, 1981). For instance, the rotten portions of most fruits and grains typically are removed prior to consumption. In foods such as cheese, the high cysteine content of the food interacts with patulin to render it inactive (Ciegler et al., 1977). Patulin is reported to be destroyed by fermentation and thus is not found in either alcoholic fruit beverages or vinegars produced from fruit juices. Thermal processing appears to cause only moderate reductions in patulin levels, thus patulin present in apple juice will survive the pasteurization processes (IARC 1986, WHO 1990, Harrison 1989, McKinley and Carlton, 1991).

In this supporting document, FDA presents the scientific information and the risk management considerations it took into account in arriving at the 50 µg/kg action level which is part of the CPG.

II. Safety Assessment and Risk Management for Patulin

Synopsis FDA employed the "safety assessment" method as the risk assessment approach for considering the available safety data on patulin. FDA used the outcome of the safety assessment to evaluate whether processors should implement controls for patulin in apple juice, and to identify a level, (i.e., an "action level") at which FDA would consider taking legal action against apple juice products bearing patulin under Section 402(a)(1) of the Federal Food Drug and Cosmetic Act, which states that a food is "adulterated" if it bears or contains an added poisonous or deleterious substance which may render it injurious to health.
The safety assessment method, originally described in a 1954 paper by Lehman and Fitzhugh (Lehman and Fitzhugh, 1954), introduced the use of 10-fold safety factors, which later also became known as "uncertainty factors," in assessing the safety of substances, e.g. contaminants, in food. Lehman and Fitzhugh described the application of the 10-fold safety/uncertainty factors as useful for establishing a "target" margin of safety. However, they concluded there were no scientific or mathematical means by which absolute values for these factors could be derived. Over the years these factors have been used routinely both in the U.S. and internationally to ensure an adequate margin of safety (WHO, 1987).
Typically, for a contaminant in a food such as apple juice, where there is a potential for chronic exposure to the contaminant, FDA would determine the exposure level that would ensure an adequate safety margin from known adverse effects by applying two 10-fold safety factors (equating to a 100-fold safety factor) to the "no observed adverse effect level" (NOAEL) from lifetime animal feeding studies. One safety factor accounts for the extrapolation from animal data to humans (i.e., interspecies variation), and the second accounts for variation in sensitivity to the contaminant's effects within humans (i.e., intraspecies variation). This calculation yields a provisional tolerable daily intake (PTDI) or provisional tolerable weekly intake (PTWI) for the contaminant.
An action level may be identified by calculating a maximum level for the contaminant in the food that would ensure that exposure to the contaminant results in an acceptable margin of safety, considering the PTDI or PTWI.
In deriving the action level for patulin, FDA considered consumption of apple juice by consumers of all ages who drink apple juice, and by consumers who drink apple juice among small children in two age categories, children less than one year old and children 1-2 years old. FDA considered the two age categories for small children because small children consume higher amounts of apple juice relative to their body weight than other age groups. Older children, e.g., 2-10 year olds, were not included as a separate group in FDA's assessment because consumption of apple juice on a "relative to body weight" basis declines substantially after age two. Therefore, there are no special risk considerations affecting older children that would need to be taken into account in a safety assessment.
Reviews of Toxicity Data; NOAEL Patulin toxicity data are reviewed in detail in: "IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans" (IARC, 1986) and "Toxicological evaluation of certain food additives and contaminants" (WHO, 1990). In addition to considering these reviews, FDA independently reviewed the available information on patulin toxicity (FDA Memorandum, 1994).
FDA's review found that the toxicological studies on patulin demonstrate that patulin is toxic upon repeated administration of oral doses around 1.5 mg/kg body weight (bw), which caused premature death in rats (Becci et al., 1981). Studies have not demonstrated convincing evidence of carcinogenicity or of germ cell mutagenic potential. The studies demonstrate that feto- or embryotoxic effects in rodents occurred only after administration of patulin doses that were also overtly toxic to the mothers. The studies demonstrate that immunotoxic effects are associated only with patulin doses that are much higher than those to which humans are exposed (Llewellyn et al., 1998).
The NOAEL for patulin was derived from a 109 week feeding study (Becci, et al. (1981)) in which doses of 0.0, 0.1, 0.5, and 1.5 mg/kg bw, were administered to both male and female rats three days per week by gastric intubation. Patulin at the high dose level caused a significant increase, compared to controls, in the mortality rate in both sexes. These effects could have resulted from the mechanics of repeated intubation.
No adverse effects were observed in the group receiving the lowest dose level, i.e., 0.1 mg/kg bw three times per week. That group received a cumulative weekly dose of 0.3 mg/kg bw, which is the NOAEL FDA used in its safety assessment.
Generally, safety experts consider animal studies to be appropriate models for assessing potential adverse effects in humans. However, animal studies that demonstrate adverse effects would not be used in assessing potential human health effects if it was established by mechanistic or other studies that the toxic effects observed in animals would not occur in humans. FDA is not aware of any toxicological data that would suggest that the effects observed in the study of Becci, et al. will not occur in humans at some level of exposure to patulin. Therefore, based upon adverse effects due to patulin in animal studies, FDA believes that humans may be at risk of harm at some level of exposure to patulin.
Provisional Tolerable Daily Intake After its own independent evaluation of the data, FDA concurs with the PTDI for patulin, which was established at the 44^th meeting of the Joint Expert Committee on Food Additives (JECFA) in 1995. JECFA is an international organization that provides science - based toxicological evaluations of food additives and contaminants and advises the Codex Committee on Food Additives and Chemical Contaminants on risk assessment of substances of interest to that committee. JECFA originally had established a PTWI for patulin at its 35^th meeting in 1990. JECFA subsequently took into account the fact that most of the patulin ingested by rats is eliminated within 48 hours. The absence of accumulation ultimately led JECFA to establish a maximum provisional tolerable daily intake (PTDI) of 0.43 µg/kg bw per day. The PTDI is derived from the NOAEL for patulin from the Becci study, i.e. 0.3 mg/kg bw per week. That weekly intake is converted to a daily intake by dividing it by 7, and that result is divided by 100 to apply the two 10-fold safety factors to arrive at the PTDI, as follows:
1. 0.3 mg/kg bw per week divided by 7 = 0.043 mg/kg bw per day
2. 0.043 mg/kg bw per day divided by 100 (safety factor) = 0.00043 mg/kg bw per day, or 0.43 µg/kg bw per day, which is the PTDI.

Assessment of exposure to patulin versus PTDI Two exposure assessments were calculated, FDA's initial assessment and a revised assessment that was carried out after FDA's Food Advisory Committee reviewed the scientific information supporting an action level for patulin, as discussed below.
In evaluating the estimated exposure to patulin with respect to the PTDI, FDA considered the estimated exposure to patulin for apple juice drinkers of "all ages" and for apple juice drinkers among small children in two age categories, children less than one year old, and children 1-2 years old. The interpretation of the exposure estimates for the various age categories with respect to the PTDI is discussed below in section 4 B., "Revised assessment."
To estimate exposure to a dietary contaminant, FDA must obtain intake (consumption) data for the food bearing the contaminant and data on the occurrence level for the contaminant in that food. If age specific intake data are available, exposure may be calculated for specific age groups, as was done in this instance.
In making both sets of estimates, the FDA used a probabilistic modeling method known as a "Monte Carlo analysis" to estimate patulin exposure (Rubinstein, 1981). Monte Carlo simulations can be used to evaluate models in which one or more inputs (in this case, food intakes and patulin levels) can be defined by a distribution of values. A Monte Carlo simulation takes a random value from the distribution of possible values for the input, uses that value in calculating the outcome of the model, stores the result, and then repeats the procedure a determined number of times (iterations) using new random values of the input taken from the distribution for each iteration. The resulting output from this procedure (e.g., exposures) is a range of possible outcomes for the model. A probability distribution function can be prepared from the range and can be used to estimate exposures (typically mean and/or 90^th percentile) to substances in the diet. It should be stressed, however, that the model FDA used assumes that food choices are random, which might not be appropriate for a "visible" additive, such as a high-intensity sweetener.
The availability of distributions of food intakes, patulin levels in apple juice and apple juice containing products, and survey information evaluating the percentage of eaters of each food in the population, as well as the invisibility of patulin in food, enable the use of Monte Carlo modeling for evaluating patulin exposure.
The juice intake data used to calculate exposure were taken from the 1994-1996 United States Department of Agriculture Nationwide Food Consumption Survey (category: Apple Juice Specified as an Ingredient). This category encompasses apple juice intake as pure juice, as well as apple juice as an ingredient in juice blends and other foods. The food consumption data are based on 2 day food consumption surveys of consumers, which are very short survey times that result in overestimation of actual long-term consumption. Long-term food consumption surveys would be most appropriate to use considering that the PTDI was based upon a lifetime animal bioassay. However, since long-term consumption data are seldom available, the 90^th percentile exposure from short term food consumption surveys usually are used, and this approach is considered by experts to be a conservative approach that ensures that an appropriate degree of protection is obtained in the safety assessment.

Initial assessment Patulin occurrence data were taken from 2977 samples of apple juice analyzed for patulin levels. The majority of the samples were commercial samples taken from lots of bulk juice and analyzed privately for the industry, and the results were made available to FDA. Such analyses typically are performed by industry to determine the acceptability of a lot of juice offered by the supplier. The remaining samples were collected and analyzed by FDA as part of its monitoring and enforcement activities.
The patulin level inputs were taken from patulin occurrence data in apple juice that were categorized into groups with ranges of <5 100-199="" 200-500="" 5-49="" 50-99="" and="">500 µg/kg. For each iteration during the Monte Carlo analysis, a patulin group first was selected from one of these groups based on the frequency of samples in each group. After a group was selected, a patulin value was calculated by the computer based upon the assumption that the patulin values would be distributed uniformly about the mid-value of each range. FDA used this approach because at the time we conducted the initial assessment, we did not have the actual measured patulin levels for many of the apple juice samples tested for industry. Rather, much of the industry data originally were reported to FDA as categorized data, i.e. the number of samples with patulin levels within the above ranges.
Tables 1 and 2 present the estimated exposures to patulin (Apple juice intakes are expressed as grams per person per day; Patulin exposures are expressed as µg/kg bw per day; Mean body weights used in the calculations are 8 kg for <1 1-2="" 12="" 1974="" 64="" ages="" all="" and="" for="" group="" kg="" ohnson="" olds="" p="" the="" year=""> The estimated patulin exposures shown in Table 1 were calculated using patulin levels from all 2977 apple juice samples. Industry sources have informed FDA that the samples analyzed by industry include many commercial lots that were rejected by the importers for excessive patulin. Thus, the estimated patulin exposures presented in Table 1 likely exaggerate actual patulin exposures and reflect upper bound potential exposures if processors exercise no controls for patulin. In Table 2, the 545 samples with a patulin level greater than 50 µg/kg were excluded from the Monte Carlo simulation to represent the expected impact on exposure of processors implementing controls for patulin to limit its occurrence in accord with the level set out in the guidance.

**Table 1: No Juice Samples Excluded**
Age Group	Mean Apple Juice Intake (g/p/d)	Mean Patulin Exposure (µg/kg bw/d)	90^th Percentile Apple Juice Intake (g/p/d)	90^th Percentile Apple Patulin Exposure (µg/kg bw/d)
All ages	200	0.094	250	0.22
1-2 years	216	0.58	434	1.3
<1 td="" year="">	128	0.50	372	1.1

**Table 2: Juice Samples with Patulin Levels > 50 µg/kg Excluded**
Age Group	Mean Apple Juice Intake (g/p/d)	Mean Patulin Exposure (µg/kg bw/d)	90^th Percentile Apple Juice Intake (g/p/d)	90^th Percentile Apple Patulin Exposure (µg/kg bw/d)
All ages	200	0.031	250	0.078
1-2 years	216	0.17	434	0.42
<1 td="" year="">	128	0.13	372	0.38

The results in Table 1 indicate that if processors do not implement controls for patulin, the estimated 90^th percentile patulin exposure for apple juice consumers of all ages would be below the PTDI of 0.43 µg/kg bw per day. However, the exposure for children under 1 year of age would be nearly 3 times the PTDI and exposure for children 1-2 years old would be 3 times the PTDI (equating to an exposure level only 33-fold less than the NOAEL).
The results in Table 2 indicate that if processors implement controls for patulin at the 50 µg/kg level, the estimated 90^th percentile patulin exposure for all the age groups considered would not exceed the PTDI of 0.43 µg/kg bw per day. In fact, the exposure for apple juice consumers of all ages would be 5-fold less than the PTDI, providing a 500-fold safety factor (considering the PTDI incorporates a 100-fold safety factor) for lifetime consumption. Exposure would be slightly below the PTDI for children under 1 year of age, and essentially at the PTDI for 1-2 year old children, meaning that at least a 100-fold safety factor would exist for children in these age categories under this assessment.

Revised assessment FDA presented the above scientific information supporting the establishment of an action level for patulin to its Food Advisory Committee (FAC) in June 1999 (see discussion below). In response to comments made by some members of the FAC, FDA subsequently carried out a revised assessment of exposure to patulin to ensure the best possible assessment of exposure to patulin.
FDA subsequently obtained the measured patulin levels for 2647 apple juice samples, including many of the 2977 samples considered in the initial assessment and also some more recently analyzed samples. In addition, industry provided the patulin results for 118 samples of apple juice intended for infants. In the revised assessment, the Monte Carlo calculations were based upon the actual values for patulin in the 2647 samples for the "all ages" group and the 1-2 year old group. For each iteration, an actual patulin value was selected from the sample population. For the <1 3="" 4.="" 71="" a="" analysis="" and="" apple="" are="" assessment="" available="" data="" detailed="" determined="" for="" from="" group="" in="" infants.="" infants="" intake="" intended="" juice="" large="" of="" old="" p="" population="" presented="" receive="" remainder="" results="" revised="" sample="" selected="" simulation="" tables="" that="" the="" therefore="" these="" this="" time.="" time="" year="">

**Table 3: No Juice Samples Excluded**
Age Group	Mean Apple Juice Intake (g/p/d)	Mean Patulin Exposure (µg/kg bw/d)	90^th Percentile Apple Juice Intake (g/p/d)	90^th Percentile Apple Patulin Exposure (µg/kg bw/d)
All ages	200	0.14	250	0.26
1-2 years	216	0.80	434	1.7
<1 td="" year="">	128	0.21	372	0.40

**Table 4: Juice Samples with Patulin Levels > 50 µg/kg Excluded**
Age Group	Mean Apple Juice Intake (g/p/d)	Mean Patulin Exposure (µg/kg bw/d)	90^th Percentile Apple Juice Intake (g/p/d)	90^th Percentile Apple Patulin Exposure (µg/kg bw/d)
All ages	200	0.04	250	0.10
1-2 years	216	0.22	434	0.67
<1 td="" year="">	128	0.13	372	0.27

The results of the revised assessment in Table 3 indicate that if no controls for patulin levels are carried out by processors, the estimated 90^th percentile patulin exposure for apple juice consumers of all ages would be approximately one half of the PTDI of 0.43 µg/kg bw per day. However, the exposure for children under 1 year of age is approximately the same as PTDI and exposure for children 1-2 years is 4 times the PTDI (equating to an exposure level only 25-fold less than the NOAEL).
The results of the revised assessment in Table 4 indicate that if processors implement controls for patulin at the 50 µg/kg level, the estimated 90^th percentile patulin exposure for apple juice consumers of all ages would be 4-fold less than the PTDI, providing a 400 fold safety factor for lifetime consumption. The estimated exposure for the <1 1-2="" 64-fold="" above="" age="" an="" approximately="" be="" children="" estimated="" exposure="" for="" group.="" group="" however="" less="" level="" noael="" of="" old="" one-half="" p="" ptdi.="" ptdi="" result="" slightly="" still="" than="" the="" this="" would="" year=""> In carrying out a safety assessment, FDA generally considers only the estimated exposure for "all ages" when the PTDI has been derived from a lifetime feeding study, as is the case for patulin. In such a case, FDA would consider that there is an adequate margin of safety if the estimated patulin exposure for the 90^thpercentile apple juice drinker of "all ages" is less than or equal to the PTDI. In the lifetime feeding study, the animals in each dosage group were exposed to a single patulin dose level (relative to body weight) throughout their lives. In contrast, FDA recognizes that human exposure to patulin varies substantially according to age. Patulin exposure in small children is higher relative to body weight because small children consume significantly greater amounts of apple juice relative to their body weight. Thus, FDA also considered the estimated exposure to patulin by children in these two age categories with respect to the PTDI.
FDA believes that in view of the greater exposure to patulin by small children, the exposure for apple juice consumers of all ages should be significantly below the PTDI to ensure an adequate margin of safety for long term consumption of apple juice. If long term exposure to patulin is significantly below the PTDI, FDA believes that it is not necessary for patulin exposure for small children to be at or below the PTDI during this relatively short portion of the lifespan. However, FDA recommends as a prudent protective measure, that processors control patulin levels so as to limit to the exposure to patulin for children 1-2 years old.
In this manner, Table 4 indicates that public health protection will be achieved if processors control patulin levels in apple juice to not exceed the action level. Estimated exposure for apple juice consumers of all ages is significantly below the PTDI (i.e., estimated exposure for lifetime consumption is 4-fold less than the PTDI) and estimated exposure for 1-2 year old children is 64-fold less than the NOAEL.
Conversely, if processors do not control patulin levels in apple juice, the exposure estimates in Table 3 indicate that for children 1-2 years old, the exposure level would only be 25-fold less than the NOAEL. FDA believes that this relatively low margin of protection and the accompanying greater long-term exposure may not provide optimum long-term protection for apple juice consumers.
Furthermore, the exposure estimate in Table 4 likely overestimates the exposure to patulin that will occur if processors of apple juice implement controls for patulin. This is because FDA expects that, in order to have a high degree of confidence that their products will not exceed the action level, juice manufacturers will exercise the necessary degree of control (e.g. strict quality specifications on incoming apples) to ensure that their products are actually well below the action level. This appears to have occurred in the United Kingdom (U.K.). In 1993, the U.K. Ministry of Agriculture, Food, and Fisheries (MAFF) set a patulin advisory level of 50 µg/kg in apple juice. Since that time, the percentage of apple juice samples in the U.K. containing patulin levels above the advisory level has been reduced and patulin levels also have been reduced in samples that comply with the advisory level. Prior to the implementation of the advisory level, 27% of samples in the U.K. had less than 10 µg/kg patulin and 7% of the samples contained 10-24 µg/kg. The 300 samples analyzed in Britain in 1998 had 69% and 22%, respectively, in those two categories (MAFF, 1999).
A similar change in the distribution of patulin levels in apple juice samples in the U.S. would change the exposure estimates presented in Table 4. When, for example, the 300 patulin samples from the 1998 British survey were used to calculate the exposure of the 90^th percentile U.S. apple juice drinker for the age groups "<1 0.06="" 0.34="" 0.40="" 1-2="" 50="" a="" action="" adequate="" age="" ages="" all="" an="" and="" apple="" at="" be="" bw="" children="" consumers.="" day="" essentially="" exposure="" exposures="" for="" further="" g="" juice="" kg="" level="" margin="" of="" old="" p="" per="" provide="" ptdi.="" respectively.="" safety="" supports="" that="" the="" this="" values="" were="" would="" year="" years=""> In addition, the exposure estimates in Table 4 may overestimate exposure to patulin for children who often consume apple juice that has been diluted with water. In fact, the American Academy of Pediatrics advises parents who frequently offer juice to their children to dilute the juice, ½ portion of juice to ½ portion of water (Dietz and Stern, 1999). FDA has not attempted to quantify any additional margin of safety that would be realized for children who consume diluted apple juice because not all parents may dilute the juice they serve to their children and an adequate margin of safety exists without accounting for the practice of dilution.

Action Level Based upon the above discussion, FDA believes that if processors do not implement controls for patulin, apple juice consumers may not be optimally protected from potential adverse effects due to long-term exposure to patulin from the consumption of apple juice. FDA thus believes that it is appropriate that apple juice processors voluntarily establish controls for patulin. Based upon the exposure estimates in Table 4, FDA believes that consumers of apple juice would be at negligible risk of adverse health effects from patulin if processors controlled patulin levels in apple juice to a level of 50 µg/kg or below.
Control of patulin levels in apple juice is achievable in practice. Most frequent patulin contamination results from contamination with mold on apples with surface damage. For example, in a study, Lovett et al. (1975) purposefully contaminated apples in a controlled manner with patulin-producing mold. The investigators then successfully reduced patulin contamination approximately 90% by trimming away the rotten portion of the fruit. FDA believes that control by processors of patulin levels to 50 µg/kg or below can be achieved principally by removing spoiled and visually damaged apples from the product stream used for the production of apple juice.
Other measures such as water treatment also may be effective in reducing patulin levels. Sydenham et al. (1995) found a significant reduction of patulin levels following an initial water treatment step and removal by hand of rotten and damaged fruit prior to juice production.
Evidence also suggests that certain varieties of apples with an open calyx (blossom end) are particularly susceptible to patulin formation thin the core of the apple. In such a situation, damage to the fruit it is not easily observed and the apple may not be removed from juice production (British Code of Practice, 1993). Therefore, the presence of patulin in juice made from seemingly wholesome fruit cannot be totally avoided.

III. Additional Considerations

Review by FDA's Food Advisory Committee
FDA presented the scientific information supporting an action level of 50 µg/kg for patulin in apple juice and apple juice containing products to its Food Advisory Committee (FAC) in June of 1999. The presentation to the FAC was based upon the "Initial assessment" presented above. The FAC supported FDA's recommendation that an action level be set for patulin in apple juice and apple juice containing products. It further agreed with FDA's analysis that a patulin level of 50 µg/kg of apple juice on a ready-to-eat basis would be sufficient for protection of human health. Some FAC members qualified their agreement with the level of 50 µg/kg by expressing a desire for more information in three areas. The FDA has researched these areas as requested and the results are discussed below.
Some members of the FAC asked whether more current information about apple juice consumption by young children was available. The agency looked for more current information about apple juice consumption for the two age groups considered, but was unable to locate any more recent reliable information. The data from the 1994-1996 United States Department of Agriculture Nationwide Food Consumption Survey are the best consumption data available, and FDA is not aware of any reason why these data are not suitable for use in the safety assessment for patulin. However, in response to the comments of these members of the FAC that stressed the need to ensure adequate protection for small children, FDA carried out the "Revised assessment" of exposure to patulin described above.
Commenting on the data in one of the tables presented in the Becci study, a member of the FAC also questioned whether FDA, in its safety assessment, had incorporated properly the doses of patulin received by the rats in the study. FDA subsequently checked with one of the authors of the study who stated that the doses of patulin presented in the published paper, e.g., 0.0, 0.1, 0.5, and 1.5 mg/kg bw, were the doses given by gavage three times per week. Thus, FDA did incorporate properly the doses received by the rats in its safety assessment, as did JECFA when calculating the PTDI.
A member of the FAC expressed concern that the elderly in institutional settings (e.g., nursing homes) may consume high amounts of apple juice. The agency did not evaluate intake by the elderly as a separate class. Instead, their intake was considered in the "all ages" category. In response to the committee member's comment, the agency did review the information it had available on the intake of apple juice by the elderly. Although data on intake by the elderly in institutional settings were not available, intake by the elderly among the general population was not significantly different than intake for the all ages group. Given that the estimated exposure to patulin is 4-fold less than the PTDI for apple juice consumers in the all ages group, if in fact the elderly in institutional settings consume significantly more apple juice than the elderly in the general population, FDA believes that a substantial margin of safety still would exist for the elderly in institutional settings.

IV. Conclusion

The information presented in this paper supports a 50 µg/kg action level for patulin in apple juice, apple juice concentrates, and apple juice products based on the level found or calculated to be found in single strength apple juice or in the single strength apple juice component of the product.

V. References

Becci, P. J., Hess, F. G., Johnson, W. D., Gallo, M. A., Babish, J. G., Dailey, R. E., & Parent, R. A. (1981) Long-term carcinogenicity and toxicity studies of patulin in the rat. J. Appl Toxicol 1(5):256-261.
Brain, P. W. (1956) Production of patulin in apple fruits by Penicillium expansum, Nature (London) 178: 263.
British Code of Practice for the Production of Apple Juice, British Soft Drinks Association, November 1993.
Ciegler, A. (1977) Patulin. Rodericks JV et al. (ed) Mycotoxins in human and animal health. Pathotox Publ. p 609-623.
Dietz, W.H. and Stern, L. (ed) (1999) American Academy of Pediatrics, "Expanding your baby's diet." Ch. 2, p 33. Villard Books.
FDA Memorandum, "Hazards or Patulin in Apple Juice." May 5, 1994.
Fritz, W. and Engst, R. (1981) Survey of Selected Mycotoxins in Food. J. Environ. Sci. Health B16(2): 193-210.
Harrison, M A (1989) Presence and stability of patulin in apple products: A review. J Food Safety 9: 147-153.
Hasseltine, C.W. and Graves, R.R. (1966) Microbiology of flours, Econ. Bot. 20: 156.
Harwig, J. et al. (1973) Occurrence of patulin and patulin-producing strains of Penicillium expansum in natural rot of apples in Canada. Can. Inst. Food Technol. J. 6: 22.
IARC (1986). Patulin, IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans. 40: 8398.
Johnson, P.E. (1974) Nutrition Standards: Man, Part 1, United States: Children and Adults. Altman, P. L. & Dittmer, D.S. (ed) Biology Data Book, 2^nd Ed. Fed Am Soc Biol. Bethesda, MD, 3: 1447.
Lehman, AJ and Fitzhugh OG (1954) Ten-fold safety factor studies. Assoc Food Drug Officials of the US Quarterly Bulletin XVIII(1): 33-35.
Lovett, J., Thompson, R.G. and Boutin, B. (1975) Trimming as a means of removing patulin from Fungus-rotted apples. J Assoc Off Anal Chem Sep;58(5): 909-11.
Llewellyn, G.C., McCay, J.A., Brown, R.D., Musgrave, D.L., Butterworth, L.F., Munson, A.E., and white, K.L. Jr. (1998) Immunological evaluation of the mycotoxin patulin in female B6C3F₁ mice. Food Cosmet. Tox. 36: 1107-1115.
MAFF, Joint Food Safety and Standards Group, Food Surveillance, Number 173, April 1999.
McKinley E R, Carlton WW (1991) Patulin. In Mycotoxins and Phytoalexins, Ed. Sharma R P, Salunkhe D K. CRC Press Atlanta.
Rubinstein, R. Simulation and the Monte Carlo Method. J. Wiley and Son, 1981.
Sydenham et al. (1995) Reduction of patulin in apple juice samples-influence of initial processing. Food Control 6: 195-200.
Ukai, T. et al. (1954) Studies on the poisonous substance from a strain of Penicillium (Hori-Yamamoto strain), II. Culture method of Hori-Yamamoto strain and chemical structure of its poisonous substance. Proc. Phar. Soc. Jpn. 74: 450.
WHO (1987) Principles for Food Safety Assessment of Food Additives and Contaminants in Food, Environmental Health Criteria 70.
WHO IARC (1990) Patulin. WHO Food Additives Series. 26: 143-165.

Compliance Policy Guide

CPG Sec.510.150 Apple Juice, Apple Juice Concentrates, and Apple Juice Products - Adulteration with Patulin

Fungi of Great Britain and Ireland

الموسوعة الام للعلاج بالنباتات والاعشاب الطبية

الموسوعة العربية للأمراض النباتية والفطريات Arabic Encyclopedia of Plant Pathology & Fungi ( A h-k)

الموسوعة العربية للأمراض النباتية والفطريات Arabic Encyclopedia of Plant Pathology & Fungi ( A h-k))

Dr.Mohammed Al-Hamdany

الموسوعة العربية للأمراض النباتية والفطريات Arabic Encyclopedia of Plant Pathology & Fungi ( A h-k)

Bio-pesticides produced at Kenya Biologics

Biocontrol Biopesticides - Trichoderma (Hindi) - NIPHM

Trichoderma species

TRICHODERMA

Trichoderma Production

TRICHODERMA

Trichoderma

Septoria Leaf Blotch of Wheat

Barley Leaf Spots

الاسس العلمية لكتابة الرسائل الجامعية

30 ظاهرة خارقة حيرت العلماء

الجغرافيا العملية وقراءة الخرائط

الجغرافيا النباتية

ppm - parts per million

What is ppm?

ppm is an abbreviation of parts per million. ppm is a value that represents the part of a whole number in units of 1/1000000.

ppm is dimensionless quantity, a ratio of 2 quantities of the same unit. For example: mg/kg.

One ppm is equal to 1/1000000 of the whole:

1ppm = 1/1000000 = 0.000001 = 1×10^-6

One ppm is equal to 0.0001%:

1ppm = 0.0001%

ppmw

ppmw is an abbreviation of parts per million weight, a subunit of ppm that is used for part of weights like milligrams per kilogram (mg/kg).

ppmv

ppmv is an abbreviation of parts per million volume, a subunit of ppm that is used for part of volumes like milliliters per cubic meter (ml/m³).

Parts-per notations

Other part-per notations are written here:

Chemical concentration

ppm is used to measure chemical concentration, usually in a solution of water.

Solute concentration of 1 ppm is solute concentration of 1/1000000 of the solution.

The concentration Cin ppm is calculated from the solute mass m_solutein milligrams and the solution mass m_solutionin milligrams .

C_(ppm) = 1000000 × m_solute / (m_solution + m_solute)

Usually the solute mass m_soluteis much smaller than the solution mass m_solution.

m_solute ≪ m_solution

Then the concentration C in ppm is equal to 1000000 times the solute mass m_solute in milligrams (mg) divided by the solution mass m_solution in milligrams (mg):

C_(ppm) = 1000000 × m_solute_(mg) / m_solution_(mg)

The concentration C in ppm is also equal to the solute mass m_solute in milligrams (mg) divided by the solution mass m_solution in kilograms (kg):

C_(ppm) = m_solute_(mg) / m_solution_(kg)

When the solution is water, the volume of mass of one kilogram is approximately one liter.

The concentration C in ppm is also equal to the solute mass m_solute in milligrams (mg) divided by the water solution volume V_solution in liters (l):

C_(ppm) = m_solute_(mg) / V_solution_(l)

Concentration of CO₂

The concentration of carbon dioxide (CO₂) in the atmosphere is about 388ppm.

Frequency stability

The frequency stability of an electronic oscillator component can be measured in ppm.

The maximal frequency variation Δf, divided by the frequency f is equal to the frequency stability

Δf_(Hz) / f_(Hz) = FS_(ppm)/ 1000000

Example

Oscillator with frequency of 32MHz and accuracy of ±200ppm, has frequency accuracy of

Δf_(Hz) = ±200ppm × 32MHz / 1000000 = ±6.4kHz

So the oscillator produces clock signal within the range of 32MHz±6.4kHz.

The supplied frequency variation is caused from temperature change, aging, supply voltage and load changes.

Decimal, percent, permille, ppm, ppb, ppt conversion calculator

Enter proportion part in one of the text boxes and press the Convert button:

Moles per liter (mol/L) to milligarms per liter (mg/L) to ppm conversion calculator

Water solution, molar concentration (molarity) to milligrams per liter to parts per million (ppm) converter.

PPM conversions

How to convert ppm to decimal fraction

The part P in decimal is equal to the part P in ppm divided by 1000000:

P_(decimal)= P_(ppm) / 1000000

Example

Find the decimal fraction of 300ppm:

P_(decimal) = 300ppm / 1000000 = 0.0003

How to convert decimal fraction to ppm

The part P in ppm is equal to the part P in decimal times 1000000:

P_(ppm) = P_(decimal) × 1000000

Example

Find how many ppm are in 0.0034:

P_(ppm) = 0.0034 × 1000000 = 3400ppm

How to convert ppm to percent

The part P in percent (%) is equal to the part P in ppm divided by 10000:

P_(%) = P_(ppm) / 10000

Example

Find how many percent are in 6ppm:

P_(%) = 6ppm / 10000 = 0.0006%

How to convert percent to ppm

The part P in ppm is equal to the part P in percent (%) times 10000:

P_(ppm) = P_(%) × 10000

Example

Find how many ppm are in 6%:

P_(ppm) = 6% × 10000 = 60000ppm

How to convert ppb to ppm

The part P in ppm is equal to the part P in ppb divided by 1000:

P_(ppm) = P_(ppb) / 1000

Example

Find how many ppm are in 6ppb:

P_(ppm) = 6ppb / 1000 = 0.006ppm

How to convert ppm to ppb

The part P in ppb is equal to the part P in ppm times 1000:

P_(ppb) = P_(ppm) × 1000

Example

Find how many ppb are in 6ppm:

P_(ppb) = 6ppm × 1000 = 6000ppb

How to convert milligrams/liter to ppm

The concentration C in parts-per million (ppm) is equal to the concentration C in milligrams per kilogram (mg/kg) and equal to 1000 times the concentration C in milligrams per liter (mg/L), divided by the solution density ρ in kilograms per cubic meter (kg/m³):

C_(ppm) = C_(mg/kg) = 1000 × C_(mg/L) / ρ_(kg/m3₎

In water solution, the concentration C in parts-per million (ppm) is equal to 1000 times the concentration C in milligrams per liter (mg/L) divided by the water solution density at temperature of 20ºC, 998.2071 in kilograms per cubic meter (kg/m³) and approximately equal to the concentration C in milligrams per liter (mg/L):

C_(ppm) = 1000 × C_(mg/L) / 998.2071_(kg/m3₎ ≈ 1_(L/kg) × C_(mg/L)

How to convert grams/liter to ppm

The concentration C in parts-per million (ppm) is equal to 1000 times the concentration C in grams per kilogram (g/kg) and equal to 1000000 times the concentration C in grams per liter (g/L), divided by the solution density ρ in kilograms per cubic meter (kg/m³):

C_(ppm) = 1000 × C_(g/kg) = 10⁶ × C_(g/L) / ρ_(kg/m3₎

In water solution, the concentration C in parts-per million (ppm) is equal to 1000 times the concentration C in grams per kilogram (g/kg) and equal to 1000000 times the concentration C in grams per liter (g/L), divided by the water solution density at temperature of 20ºC 998.2071 in kilograms per cubic meter (kg/m³) and approximately equal to 1000 times the concentration C in milligrams per liter (mg/L):

C_(ppm) = 1000 × C_(g/kg) = 10⁶ × C_(g/L)/ 998.2071_(kg/m3₎ ≈ 1000 × C_(g/L)

How to convert moles/liter to ppm

The concentration C in parts-per million (ppm) is equal to the concentration C in milligrams per kilogram (mg/kg) and equal to 1000000 times the molar concentration (molarity) c in moles per liter (mol/L), times the solute molar mass in grams per mole (g/mol), divided by the solution density ρ in kilograms per cubic meter (kg/m³):

C_(ppm) = C_(mg/kg) = 10⁶ × c_(mol/L) × M_(g/mol) / ρ_(kg/m3₎

In water solution, the concentration C in parts-per million (ppm) is equal to the concentration C in milligrams per kilogram (mg/kg) and equal to 1000000 times the molar concentration (molarity) c in moles per liter (mol/L), times the solute molar mass in grams per mole (g/mol), divided by the water solution density at temperature of 20ºC 998.2071 in kilograms per cubic meter (kg/m³):

C_(ppm) = C_(mg/kg) = 10⁶ × c_(mol/L) × M_(g/mol) / 998.2071_(kg/m3₎ ≈ 1000 × c_(mol/L) × M_(g/mol)

How to convert ppm to Hz

The frequency variation in hertz (Hz) is equal to the frequency stability FS in ppm times the frequency in hertz (Hz) divided by 1000000:

Δf_(Hz) = ± FS_(ppm) × f_(Hz)/ 1000000

Example

Oscillator with frequency of 32MHz and accuracy of ±200ppm, has frequency accu0racy of

Δf_(Hz) = ±200ppm × 32MHz / 1000000 = ±6.4kHz

So the oscillator produces clock signal within the range of 32MHz±6.4kHz.

ppm to ratio, percent, ppb, ppt conversion table

المصدر

Name	Notation	Coefficient
Percent	%	10^-2
Per-mille	‰	10^-3
Parts per million	ppm	10^-6
Parts per billion	ppb	10^-9
Parts per trillion	ppt	10^-12

	Enter decimal:

	Enter percent:		%

	Enter permille:		‰

	Enter ppm:		ppm

	Enter ppb:		ppb

	Enter ppt:		ppt





	Enter molar concentration (molarity):	c_(mol/L)	=		mol/L

	Enter solute molar mass:	M_(g/mol)	=		g/mol
	Enter milligrams per liter:	C_(mg/L)	=		mg/L

	Enter water temperature:	T_(ºC)	=		ºC
	Enter parts per million:	C_(mg/kg)	=		ppm




Parts-per million (ppm)	Coefficient / Ratio	Percent (%)	Parts per billion (ppb)	Parts per trillion (ppt)
1 ppm	1×10^-6	0.0001%	1000 ppb	1×10⁶ ppt
2 ppm	2×10^-6	0.0002%	2000 ppb	2×10⁶ ppt
3 ppm	3×10^-6	0.0003%	3000 ppb	3×10⁶ ppt
4 ppm	4×10^-6	0.0005%	4000 ppb	4×10⁶ ppt
5 ppm	5×10^-6	0.0005%	5000 ppb	5×10⁶ ppt
6 ppm	6×10^-6	0.0006%	6000 ppb	6×10⁶ ppt
7 ppm	7×10^-6	0.0007%	7000 ppb	7×10⁶ ppt
8 ppm	8×10^-6	0.0008%	8000 ppb	8×10⁶ ppt
9 ppm	9×10^-6	0.0009%	9000 ppb	9×10⁶ ppt
10 ppm	1×10^-5	0.0010%	10000 ppb	1×10⁷ ppt
20 ppm	2×10^-5	0.0020%	20000 ppb	2×10⁷ ppt
30 ppm	3×10^-5	0.0030%	30000 ppb	3×10⁷ ppt
40 ppm	4×10^-5	0.0040%	40000 ppb	4×10⁷ ppt
50 ppm	5×10^-5	0.0050%	50000 ppb	5×10⁷ ppt
60 ppm	6×10^-5	0.0060%	60000 ppb	6×10⁷ ppt
70 ppm	7×10^-5	0.0070%	70000 ppb	7×10⁷ ppt
80 ppm	8×10^-5	0.0080%	80000 ppb	8×10⁷ ppt
90 ppm	9×10^-5	0.0090%	90000 ppb	9×10⁷ ppt
100 ppm	1×10^-4	0.0100%	100000 ppb	01×10⁸ ppt
200 ppm	2×10^-4	0.0200%	200000 ppb	2×10⁸ ppt
300 ppm	3×10^-4	0.0300%	300000 ppb	3×10⁸ ppt
400 ppm	4×10^-4	0.0400%	400000 ppb	4×10⁸ ppt
500 ppm	5×10^-4	0.0500%	500000 ppb	5×10⁸ ppt
1000 ppm	0.001	0.1000%	1×10⁶ ppb	1×10⁹ ppt
10000 ppm	0.010	1.0000%	1×10⁷ ppb	1×10¹⁰ ppt
100000 ppm	0.100	10.0000%	1×10⁸ ppb	1×10¹¹ ppt
1000000 ppm	1.000	100.0000%	1×10⁹ ppb	1×10¹² ppt

Parts Per Million Conversions

PPM conversion values and serial dilutions

How to dilute and calculate ppm concentrations and percentage amounts.
How to convert ppm to Molarity and Molarity to ppm

PPM = parts per million

PPM is a term used in chemistry to denote a very, very low concentration of a solution. One gram in 1000 ml is 1000 ppm and one thousandth of a gram (0.001g) in 1000 ml is one ppm.

One thousanth of a gram is one milligram and 1000 ml is one liter, so that 1 ppm = 1 mg per liter = mg/Liter.
PPM is derived from the fact that the density of water is taken as 1kg/L = 1,000,000 mg/L, and 1mg/L is 1mg/1,000,000mg or one part in one million.

OBSERVE THE FOLLOWING UNITS

1 ppm = 1mg/l = 1ug /ml = 1000ug/L
ppm = ug/g =ug/ml = ng/mg = pg/ug = 10 ^-6
ppm = mg/litres of water

1 gram pure element disolved in 1000ml = 1000 ppm

PPB = Parts per billion = ug/L = ng/g = ng/ml = pg/mg = 10 ^-9

Making up 1000 ppm solutions

1. From the pure metal : weigh out accurately 1.000g of metal, dissolve in 1 : 1 conc. nitric or hydrochloric acid, and make up to the mark in 1 liter volume deionised water.

2. From a salt of the metal :
e.g. Make a 1000 ppm standard of Na using the salt NaCl.

FW of salt = 58.44g.
At. wt. of Na = 23
1g Na in relation to FW of salt = 58.44 / 23 = 2.542g.
Hence, weigh out 2.542g NaCl and dissolve in 1 liter volume to make a 1000 ppm Na standard.

3. From an acidic radical of the salt :
e.g. Make a 1000 ppm phosphate standard using the salt KH₂PO₄

FW of salt = 136.09
FW of radical PO₄ = 95
1g PO₄ in relation to FW of salt = 136.09 / 95 = 1.432g.
Hence, weigh out 1.432g KH₂PO₄ and dissolve in 1 liter volume to make a 1000 ppm PO₄ standard.
Click this link for Atomic absorption standards

PPM to Molarity

Convert ppm to gram based or milligram based concentration.

ppm = 1 mg solute per liter solution or
ppm = 0.001 gram per liter solution

e.g. What is the Molarity of 400ppm Ca ions in an aqueous CaCO3 solution?

Using the 0.001g/l concentration: 400ppm x 0.001g/l = 0.4g/l.
or, Divide 400 mg by 1000 to get g/l = 0.4 g/l
Now divide by the At. Mass of Ca to get Molarity.
0.4g/l divided by 40g/mol =0.01M

Using the mg/l concentration, the 40g Ca must be converted to milligrams by multiplying by 1000 to give 40,000mg.
Hence Molarity = 400ppm divided by 40,000mg/mol = 0.01M

Ppm (parts per million) to % (parts per hundred)

Divide the ppm amount by 1,000,000 and multiply by 100 to get %. e.g. :

1 ppm = 1/1,000,000 = 0.000001 = 0.0001%
10 ppm = 10/1,000,000 = 0.00001 = 0.001%
100 ppm = 100/1,000,000 = 0.0001 = 0.01%
200 ppn = 200/1,000,000 = 0.0002 = 0.02%
5000 ppm = 5000/1,000,000 = 0.005 = 0.5%
10,000 ppm = 10000/1,000,000 = 0.01 = 1.0%
20,000 ppm = 20000/1,000,000 = 0.02 = 2.0%

(Parts per hundred) % to ppm

Divide the % value by 100 and multiply by 1,000,000 to get ppm. e.g. :

1% =0.01 x 1,000,000 = 10,000 ppm
0.5% =0.0.005 x 1,000,000 = 5,000 ppm
0.1% =0.001 x 1,000,000 = 1,000 ppm
0.01% = 0.0001 x 1,000,000 = 100 ppm

المصدر

المصدر.

تعرف على أعفان جذور أشجار «نخيل البلح» الفطرية.. وكيفية مقاومتها

دكتور / خالد حسين عرفات

مرض أعفان جذور اشجار نخيل البلح الفطرية من الأمراض الشائعة والخطيرة التى تصيب جذور النخيل، و قد يؤدى إلى موت الفسائل بل والأشجار الكبيرة أيضا، ويحدثنا عن هذا المرض الدكتور خالد حسين عرفات أستاذ أمراض النبات بكلية زراعة الوادى الجديد فيقول:ـ
الأعراض المميزة والتشخيص الحقلى للمرض:
يسبب هذا المرض ظهور أعراض إصفرار على الجريد، وقد يؤدى الى موت فسائل وأشجار النخيل حيث يدخل الفطر عن طريق الجذور مما يؤدى الى تعفنها وموتها، وعادة ما يصعب تشخيص هذا المرض حيث يسبب فى الاطوار الأولى منه أعراضا شائعة لكثير من الاصابات المرضية، تتمثل فى اصفرار وموت السعف ونقص تدريجى فى النمو والانتاج. المسبب المرضى: تسبب أعفان جذور النخيل مجموعة كبيرة من الفطريات القاطنة فى التربة خاصة بعض الأنواع من الفطر Fusarium spp.
وكذلك الفطر Ceratocystis paradoxa الذى ينتشر فى الوجه البحرى نتيجة لتوفر الظروف البيئية الملائمة لانتشاره والطور الشائع هو الكونيدى paradoxa Thielaviopsis كما يسبب مرض أعفان جذور النخيل مجموعة من الفطريات الاخرى منها Rhizoctonia solani, Botryodiploida theobromae, Phytophthtora sp.
الظروف الملائمة لحدوث المرض: زيادة ماء الرى، وزيادة الملوحة فى التربة وماء الرى تؤدى الى زيادة نسبة وشدة الاصابة بأمراض أعفان الجذور، زراعة فسائل مصابة.، عدم معاملة الفسائل قبل زراعتها بالمبيدات الفطرية الجهازية. المكافحة المتكاملة للمرض:
* ازالة الاشجار والفسائل الميتة والمصابة وحرقها.
* عدم تكرار الزراعة فى الجور المصابة من قبل.
* يوصى بغمس الفسائل قبل زراعتها فى محلول المبيد كيمازد بمعدل 3 جم/ لتر ماء.
* يوصى برى الفسائل واشجار النخيل المصابة بمبيد التوبسين ام 70 او الكربندازيم او تشجارين بمعدل 60 جرام من المبيد تذاب فى 20 لتر ماء / لكل نخلة قبل الرى مباشرة.
* يتم الرش باحد المبيدات السابقة بتركيز 1 جم / لتر – ثلاث مرات وبين كل منها حوالى اسبوعين.
* العناية بالتسميد العضوى والكيماوى باستخدام السماد المركب وخاصة الذى يحتوى على العناصر الصغرى الهامة لتقوية الاشجار.
* عند اصابة جذور النخيل بفطر الفيتوفثورا Phytophthtora فانه ينصح بغمر التربة حول الاشجار بمحلول من مبيد الاليت بمعدل 20 جم / 20 لتر ماء / شجرة.
* فى حالة الاصابة بفطر الريزوكتونيا سولانى Rhizoctonia solani تعامل التربة بمبيد مون كت بمعدل 60 جم / 20 لتر/ لكل شجرة تربة غمر حول الاشجار.
* عند الاصابة بفطريات Fusarium spp. تعامل التربة ثلاث مرات بمبيد كربندازيم بمعدل 3 جم/ لتر ماء او بمبيد بلتانول بمعدل 2 سم3/ لتر ماء تربة وتكرر المعاملة كل اسبوعين.

المصدر:
تعرف على أعفان جذور أشجار «نخيل البلح» الفطرية.. وكيفية مقاومتها

مشروع نقل تقانة المكافحة الحيوية كعنصر اساسى فى الادارة المتكاملة للآفات لمكافحة حشرة سوسة النخيل الحمراء فى الشرق الأوسط

مشروع نقل تقانة المكافحة الحيوية كعنصر اساسى فى الادارة المتكاملة للآفات لمكافحة حشرة سوسة النخيل الحمراء فى الشرق الأوسط

DOWNLOAD
مشروع نقل تقانة المكافحة الحيوية كعنصر اساسى فى الادارة المتكاملة للآفات لمكافحة حشرة سوسة النخيل الحمراء فى الشرق الأوسط

تقرير تقييم المشروع الاقليمى البحثى للكشف المبكر عن مرض البيوض على النخيل وتطوير تقانات مكافحته

DOWNLOAD
تقرير تقييم المشروع الاقليمى البحثى للكشف المبكر عن مرض البيوض على النخيل وتطوير تقانات مكافحته

Phytopathology موقع علم أمراض النبات

I. Introduction

II. Safety Assessment and Risk Management for Patulin

III. Additional Considerations

IV. Conclusion

V. References

Compliance Policy Guide

الموسوعة العربية للأمراض النباتية والفطريات Arabic Encyclopedia of Plant Pathology & Fungi ( A h-k))

Dr.Mohammed Al-Hamdany

ppm - parts per million

What is ppm?

ppmw

ppmv

Parts-per notations

Chemical concentration

Concentration of CO2

Frequency stability

Example

Decimal, percent, permille, ppm, ppb, ppt conversion calculator

Moles per liter (mol/L) to milligarms per liter (mg/L) to ppm conversion calculator

PPM conversions

How to convert ppm to decimal fraction

Example

How to convert decimal fraction to ppm

Example

How to convert ppm to percent

Example

How to convert percent to ppm

Example

How to convert ppb to ppm

Example

How to convert ppm to ppb

Example

How to convert milligrams/liter to ppm

How to convert grams/liter to ppm

How to convert moles/liter to ppm

How to convert ppm to Hz

Example

ppm to ratio, percent, ppb, ppt conversion table

PPM = parts per million

OBSERVE THE FOLLOWING UNITS

Making up 1000 ppm solutions

Dilution Formula : C1V1 = C2V2

Serial dilutions

Molarity to ppm

PPM to Molarity

Ppm (parts per million) to % (parts per hundred)

(Parts per hundred) % to ppm

تعرف على أعفان جذور أشجار «نخيل البلح» الفطرية.. وكيفية مقاومتها

دكتور / خالد حسين عرفات

Translate

بحث هذه المدونة الإلكترونية

من أنا

التسميات

أرشيف المدونة الإلكترونية

المشاركات الشائعة

Concentration of CO₂