Journal of Environmental Protection, 2011, 2, 581-591
doi:10.4236/jep.2011.25067 Published Online July 2011 (
Copyright © 2011 SciRes. JEP
Use of the Environmental Impact Quotient to
Estimate Health and Environmental Impacts of
Pesticide Usage in Peruvian and Ecuadorian
Potato Production
Peter Kromann1, Willy Pradel2, Donald Cole3, Arturo Taipe1, Gr eg or y A. Forbes2
1International Potato Center (CIP), Quito, Ecuador; 2Internat i onal Potato Center, Lima, Peru; 3Dalla Lana School of Public Health,
University of Toronto, Toronto, Canada
Received January 1st, 2011; revised April 2nd, 2011; accepted May 6th, 2011.
Currently there is no effective mechanism for measuring the potential benefits of integrated pest and disease interven-
tions in terms of reducing pesticide risks in potato production in developing countries. The environmental impact quo-
tient (EIQ), a composite hazard indicator, was applied to data from potato field trials implemented in Ecuador to eva-
luate the practical boundaries of this metric related to potato production practices in the Andes. The EIQ was also ap-
plied to data from two independent farmer surveys, one from Peru and one from Ecuador to compare potato farming
practices and the utility of the EIQ when applied to existing survey data. In the Ecuadorian field trials, the EIQ values,
i.e., environmen tal impact (EI) per ha, varied greatly among th e different potato systems tested a nd ranged fro m 40 for
an integrated pest management system (resistant cultivar plus less hazardous pesticides) to 1235 for a high -input con-
ventional system (susceptible cultivar plus frequent use of hazardous pesticides). Thus, this parameter demonstrates
substantial variation under different conditions and different crop management approaches. EI per ha values from the
two surveys fell within the range found in the field trial, but in the survey values were toward the lower end, ranging
from 64 to 213. Methodical and biophysical factors are discussed that may account for the relatively low EI per ha
found in the field survey data. Our study demonstrates the utility of the EIQ for assessing health and environmental
hazards of potato production in the Andes and potentially other areas in the developing world. Nonetheless, there are
limitations to the EIQ as presently u sed and care is ne eded in the interp reta tion of resu lts. We see our work as an initial
step in the development of an integrated metric to estimate environmental and human health hazards related to pesti-
cide use in potato production in the diverse conditions of developing countries.
Keywords: Insecticide, Fungicide, Farmer Training, Andean Weevil, Late Blight
1. Introduction
Potato is the most important crop in the Peruvian Andes,
both in terms of area planted, and farm households pro-
ducing - approximately 600 thousand. In Ecuador there
are approximately 90 thousand potato producers. Cur-
rently, the potato crop contributes 11% and 7% of the
agricultur al gross domestic produ ct in Peru and Ecuador,
respectively, equivalent to a total added value of US
$684 million in 2006 [1]. It is estimated that the potato
producers in the two countries represent 5% of the agri-
cultural economically active population, and more than
30 million workdays are generated each year in the
potato sector [1]. Thus, the potato cr op is one of th e main
labour and income sources in the rural areas of Andean
Peru and Ecuador. However, average potato yields in the
two countries remain low: 12.3 t·ha–1 in Peru and 7.8
t·ha–1 in Ecuador, compared to 17.2 t·ha–1 in the neigh-
bouring country Co lombia and the world average of 17.6
t·ha–1 [1]. Farms in the Andean highlands of Peru and
Ecuador are characterized by small-scale agriculture and
significantly rely on a rain-fed cro pping system. Potato is
predominantly grown for local and regional markets and
is a subsistence crop for many of the poorest Andean
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
582 Peruvian and Ecuadorian Potato Production
The main potato disease in the Andes is late blight,
which is caused by the oomycete pathogen Phytopht hora
infestans . According to one study, about 42% of the
268,000 ha cultivated with potato in Peru are at risk from
high late blight severity and approximately 15% of the
Peruvian potato crop is lost annually to late blight [2]. In
Ecuador, in the northern wet Andes, late blight is particu-
larly widespread because farmers plant potato year-round
and the dry seasons are generally relatively short [3] .
Pests are also major biotic constraints to potato pro-
duction in the Andes, especially the Andean potato wee-
vil (Premnotrypes spp.), the potato tuber moths (Sym-
metrischema plaesiosema, Tecia solanivora, Phthori-
maea operculella) and flea beetles (Epitrix spp.).
The use of pesticides is common practice among po-
tato farmers due to the prevalent pest and disease prob-
lems. In both countries fungicides are routinely used for
control of potato late blight and insecticides are applied
primarily to control Andean potato weevil, but also fre-
quently for flee beetle. The product types and number of
sprays commonly used are highly variable from one lo-
cation to another. The use of highly hazardous (World
Health Organization, WHO class Ia and Ib) and moder-
ately hazardous (WHO class II) pesticides has been re-
ported to be common [4]. A study done in 1999 in north-
ern Peru [5] found that farmers applied fungicides 6
times on the average to their potato crops. Two surveys
carried out by the International Potato Center (CIP) in the
1990’s found that farmers in northern Ecuador on the
average sprayed potato 7 times with an average of 2.5
products in a mixture at each application [6]. A recent
intensive follow-up study of producers in northern Ec-
uador found that the situation has ch anged little; the new
study reported an aver age of 7.3 sprays per season [7].
CIP and its partners have put a high priority on the
development and diffusion of integrated pest (and disease)
management (IPM) knowledge and technologies that
help to reduce the damage caused by pests and diseases,
while also reducing dependency on hazardous pesticides.
These technologies include use of potato cultivars with
resistance to late blight, biological control, and alterna-
tive management practices to reduce the overall need
for insecticides and the complete avoidance of highly
toxic insecticides for control of Andean potato weevil
(World Health Organization, WHO category Ia and Ib)
Measuring the success of IPM and related technologies
can be done in several ways. For example, one can dem-
onstrate increased productivity and/or economic benefits
of any practice that is to be adopted by farmers. This can
be done with a large number of established techniques
routinely used in field trials, including demonstration
plots or the more participatory farmer field schools [9].
Yield measurements and simple economic analysis are
readily carried out with farmers to compare crop man-
agement practices [10].
Within the developing countries where CIP and its
partners work, however, there is no effective mecha-
nism for measuring the potential benefits of IPM inter-
ventions in reducing environmental and human health
risks. It has become increasingly clear that assessments
based solely on the costs of pesticides or on the vol-
umes applied are not sufficient metrics for evaluating
the potential environmental or health benefits of IPM
approaches [11]. Furthermore, given the resource limi-
tations and difficulties associated with work in many
developing countries, any metric adopted for assessing
health and environmental risks should require a mini-
mum of input information.
Many tools, which summarize the complexity of envi-
ronmental and h uman health haza rd s and risks, hav e be en
developed for the evaluation of secondary adverse effects
of pesticides [12]. One of the more widely used measures
is the EIQ [13], a composite system, which permits the
integration of several important environmental and hu-
man health impacts into one value [14]. The EIQ is re-
garded as relatively easy to use and has been presented in
the scientific literature as useful for estimating potential
environmental hazards associated with agricultural pesti-
cide use in diverse environments [15-25].
In this article, we apply the EIQ to data from con-
trolled field trials implemented in Ecuador to evaluate
the practical boundaries of this metric for different crop
management practices that may be found in potato pro-
duction in the Andes. We also use the EIQ to compare
potato farming practices reported in two independent
surveys, one involving three locations in Peru and the
other from two locations in Ecuador. We propose the
EIQ as a simple metric for comparing crop management
practices in potato production in developing countries.
We discuss some limitations of this approach as well as
research that may facilitate or improve it.
2. Materials and Methods
2.1. The Environmental Impact Quotient (EIQ)
The EIQ is a mathematical and conceptual summary of
environmental and health hazards [14]. It combines the
pesticide hazard posed to farm workers (applicator and
picker effects), consumers (consumer effect and ground-
water effect), and the local environment (aquatic and
terrestrial effects) into a composite hazard indicator (Eq-
uation (1)) .
Equation (1):
opyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in 583
Peruvian and Ecuadorian Potato Production
 
 
 
here: nic toxicity
ues half-life
hropod toxicity by toxicity in-
ever, for
ntal impact (EI) of each a.i. per hectare
active ingredient
× is the amount of formulation in ki-
of Potato nts in
A coeriment was implemented three times in
C = chro
DT = dermal toxicity
P = plant surface resid
S = soil residues half-life
SY = systemicity
L = leaching poten
F = fish toxicity
R = surface loss p
D = bird toxicity
Z = bee toxicity
B = beneficial art
Values in the equation are determined
rmation from several sources including the Extension
Toxicology Network (EXTOXNET), CHEM-NEWS,
SELCTV, individual chemical manufacturers’ data sheets,
and public data sources, such as those available from the
US Environmental Protection Agency [13]. The mini-
mum EIQ for a pesticide active ingredient (a.i.) is 6.7 and
the maximum 210. Most EIQ values used in this study
were taken from a database of over 450 a.i. that are cur-
rently available on a Cornell Uni versity website
( How
some pesticide a.i. that were not available at that site, we
used the EIQ of a chemically similar product which be-
longed to the same hazard classification of the World
Health Organization (WHO) [8]. For example, benalaxyl
and oxycarboxin, not on the published list, were given
the value of 15.55, which is the average value of the
chemically similar fenhexamid and carboxin, which are
on the list. All four products are classified as “U”, un-
likely to present acute hazard in normal use, in the WHO
The environme
a) was calculated for each individual field or experi-
mental plot with the following formula:
EI per ha = EIQ × [dosage ha–1] × %-
no. applications;
Where dosage ha–1
grams or liters per ha. The total EI per ha was calcu-
lated by summing the EI per ha for each individual a.i.,
across all applications of the season.
2.2. Environmental Impact (EI)
Production Systems in Field Experime
ntrolled exp
Ecuador in important potato production zones. The ex-
periments were designed to give estimates of EI of dif-
ferent production practices ranging from those consid-
ered most ecological to those highly dependent on pesti-
cides. One trial was conducted in the CIP-Quito experi-
mental station in the province of Pichincha in 2008, a
second in a farmer’s field in San Vincente de Tiazo in the
province of Chimborazo also in 2008 and a third in a
farmer’s field in Pillaro in the province of Tungurahua in
2009. The experiments were designed to estimate the
environmental and health hazards of six different potato
management systems (Table 1). Each system included a
potato cultivar and technology package. The technology
packages were designed in consultation with farmers and
workers from the national potato program. The trials in-
cluded the cultivars Fripapa, Superchola and Capiro,
which were combined with conventional practices which
depend heavily, but to a varying degree, on pesticide
inputs, and the late blight resistant and early maturing
breeding varieties C8, C11 and CIP 575045, which were
combined with IPM practices recommended by CIP and
national partner scientists. Thus, conventional production
systems differed from IPM production systems in that the
former generally included both more applications of pes-
ticides and also pesticides with higher EIQ values (Table
1). For example, conventional systems used sys-
temic/transla- minar fungicides such as dimethomorph
(EIQ = 24.01) and cymoxanil (EIQ = 35.48) and the
contact fungicides mancozeb (EIQ = 25.72) and
chlorothalonil (EIQ = 37.42), while the IPM systems
generally used phosphonate fungicides (EIQ = 8.67)
(Table 1). A similar situation existed for insecticides.
CIP 575045 was not included in the trial in Tungu
a. Conventional farmer practices for the first three cul-
tivars consisted of calendar sprays with pesticides that
were selected based on interviews with farmers who reg-
ularly grew the cultivars and selected pesticides accord-
ing to the pests that were present and the perceived se-
verity of late blight. Several pesticides were used to rep-
resent common pesticide choices in the different prov-
inces. For the management systems based on IPM prac-
tices, late blight was treated by spraying primarily with
phosphonate fungicides after each 50 mm accumu- lated
rainfall [26]. IPM insect control consisted of traps for
Andean potato weevil, monitoring and, when needed,
applications primarily with the insecticides acephate and
deltamethrin, both with relatively low EIQ values (Table
3) for control of weevil and flea beetle respectively [27].
At all sites a randomized complete block design was
ed with four replicates. To verify natural pest and dis-
ease levels, six additional control plots with each of the
six cultivars (five in Tungurahua) without pesticide ap-
plications were included. Plot size was approximately 6 ×
6 m with an intra-row distance of 0.8 m for all cultivars
Copyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
Peruvian and Ecuadorian Potato Production
Copyright © 2011 SciRes. JEP
inix different potato pest management systems in field trials
Integrated pest management system1
Tabel 1. Pesticide active ingredients and range of sprays used s
carried out at three locations in Ecuador in 2008 and 2009.
Active ingredients Capiro-C and Super chola-C C8 and C11 Fripapa-C CIP 575045
Fungicide2 Number of spray
3 - 11 2 - 8
ph 0 -
0 -0 -0 -
ide mber of sprays
1 - 3 1 - 3 1 1
/ Carbosulfan 0
1 -
Dimethomor2 - 3 1 - 2 1
Fosetyl-Al 2 - 4 2 - 3 2 - 4 - 1
Metalaxyl 2 - 5 2 - 4 0 - 1 0 - 1
Ca-,Cu-or K- 2 - 3
Chlorothalonil 2 2 1 1 - 3
Mancozeb 3 - 7 2 - 4 0 - 1
Maneb / Propineb 0 - 3 0 - 2
Sulfur 0 - 4 0 - 3
Insectic Nu
Carbofuran0 - 6 0 - 2 - 1
Deltamethrin 1 - 3 1 - 3 3 1 - 3
Methamidopho1 - 2 1 - 2
Profenofos 2 - 3 1 - 2
1nvolves one potato variety and a peshnology package. Thoowed by “C” are considered conventional and are deved from inter-
xcept Superchola and Capiro, which were planted with
r Survey
nt department of the
numbers of farmers were recruited from the three dis-
een June and Au-
farmer participa-
Each system iticide tecse follri
views with farmers and consultations with local potato researchers. The others are based on integrated disease and pest management recommendations. See
Table 2 for more information on locations and Table 3 for EIQ values of pesticides; 2Cymoxanil, dimethomorph and metalaxyl were used in mixture with a
contact fungicide.
an intrarow distance of 1.1 m as is commonly done by
farmers. Cultural practices and fertilization were done
following recommendations for each cultivar indivi-
dually and the latter was based on soil analyses. Pesti-
cides included in the treatments were applied with
20-liter lever-operated knap-sack sprayers with constant
flow valves (CFValve R11–16SY; G.A.T.E, Sebastian,
FL). The three experiments were all planted to coincide
with th e rainy season to insure natural late blight disease
pressure. To differentiate experimental units and reduce
potential interference effects of pesticide drift or patho-
gen/pest spread, all plots were surrounded with 1 to 2 m
of oats (Avena sativa).
2.3. Peruvian Farme
Three districts, each from a differe
Peruvian highlands were selected for the study (Table 3).
La Encañada and Huamachuco are in the departments of
Cajamarca and La Libertad, respectively, both in north-
ern Peru, while Chaglla is in the department of Huánuco
in central Peru. These zones were selected because of
their importance in Peruvian potato production. A total of
307 farmers were surveyed between March and April of
2006 to gather information about potato production dur-
ing their most recent crop cycle. Approximately equal
tricts. In La Encañada 101 farmers were interviewed; in
Huamachuco 104; and in Chaglla 102, representing ap-
proximately 4.9%, 5.5% and 46.1% of the potato area in
each respective district. Average potato area per farmer
differed substantially, with 0.89 ha in La Encañada, 1.55
ha in Huamachuco and 4.96 ha in Chaglla. All farms
included in the survey were located more than 3000 m
above sea level (m.a.s.l). The survey included questions
on farm and potato plot sizes, varieties grown and details
of pesticide use. Data were collected by agronomists vis-
iting the farms and interviewing the farm owners. Data
were based primarily on farmers’ perceptions, but at times
the interviewers attempted to verify the answers by in-
specting equipment, plots or pesticide stocks.
2.4. Ecuadorian Farmer Survey
A detailed survey was carried out betw
gust of 2007 to analyze the impact of
tion in a program aimed at fomenting associations in the
central region of Ecuador. Those who participated in the
program received some IPM training. Data were col-
lected in the provinces of Chimborazo and Tungurahua,
two important potato production zones, which represent
typical smallholder farming in the central Ecuadorian
highlands. All data were collected for production fields
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in 585
Peruvian and Ecuadorian Potato Production
mental Impact (EI) of Potato
ion Systems in Field Experiments in
all e with foliage severity at 100 days after
ms that
mental Impact
Thir t fungicide a.i. and 32 insecticide a.i.
Table 2. Number of pesticide sprays and environmental impact (EI) from six different potato pest management systems in
found at more than 3000 m.a.s.l. Farmers were carefully
selected and labeled as either 1) participants in the asso-
ciation program, 2) non-participants in the same commu-
nities or 3) non-participating farmers in control commu-
nities (those where the program was not implemented).
The latter were communities that had similar characteris-
tics to the association communities at the initiation of the
association program. A study of the socio-economic im-
pact of the program was published previously [28]. We
report total aggregated pesticide usage from the two Ec-
uadorian provinces to facilitate a comparison with pesti-
cide usage reported from the Peruvian farmer survey. We
also report results aggregated by group to evaluate the
effect of the farmer association program on pesticide
usage patterns. Only data from potato plots with detailed
information on the completed crop cycle were included
in our analysis. Data are presented from 338 potato plots,
representing 43% of all communities that participated in
the intervention program and from 515 potato plots from
farmers in the other two groups. Average potato area per
farmer in the survey was 1.18 ha. Average potato plot size
in Chimborazo was 0.59 ha and in Tungurahu a 0.9 ha.
3. Results
3.1. Environ
blight was controlled satisfactorily in all systems in
planting never surpassing 10% in any of the treatments.
Likewise, Andean weevil and other insects were con-
trolled to acceptable levels, with less than one percent
tuber damage incidence at harvest in all treatments (data
not shown). In the cultivars Fripapa, Superchola, Capiro
and breeding clone CIP 575045 late blight severity gen-
erally reached 50% - 100% before 100 days after plant-
ing in control plots (those without fungicide sprays) and
in C8 and C11 late blight severity generally reached 1% -
5% in control plots, demonstrating these varieties high
level of resistance relative to the other cultivars.
The EI per ha varied greatly among the syste
ere tested (Table 2 ), with values calculated for conven-
tional farming systems with susceptible cultivars ranging
from 419 to 1235. EI values for systems using late blight
resistant and early maturing cultivars were lower and
ranged from 40 to 174. Thus, the overall range in EI from
all three trials was from 40 to 1235.
3.2. Pesticide Usage and Environ
(EI) in Peruvian and Ecuadorian Potato
ty-four differen
were reported as having been used to control pests and
diseases in the Peruvian and Ecuadorian farmer surveys.
Although many products were rarely used and only re-
ported by a few farmers, several products were com-
monly used, but often in manners that were strongly site
specific, resulting in differences between and within
countries (Table 3). For example, in Ecuador the most
commonly used fungicide was mancozeb, a contact pro-
duct, while in Peru farmers tended to depend more on
systemic fungicides, particularly formulations containing
metalaxyl. Insecticide use between countries was also
different, e.g., profenophos and acephate, which were
common in Ecuador were not used at all in Peru. The
most commonly used insecticides across all three dis-
tricts in Peru were carbofuran and methamidophos, both
highly hazardous [8] (Ta ble 3).
Products were also used differentially within countries.
e fungicide dimethomorph was used in 26% of plots in
field trials carried out at three locations in Ecuador in 2008 and 2009.
CIP Station ChTungurahua imborazo
Production system1
Spray EI4 Sprays Sprays EI
s3 EI
Capiro- C 16/9 1235 12/9 798 12/10 616
4/3 40
uperchola-C 13/7 840 12/9 798 12/10 616
Fripapa-C 10/5 676 10/8 634 9/8 419
CIP 575045 3/2 113 5/4 174
C8 5/2 88 4/5 87
C11 5/2 88 4/5 87 4/3 40
1Each integrated anagement systemnvolves otato variety a pesticide tech packagse followed by “e consid ered cotional pest m ione p andnologye. ThoC” arnven
and are derived from interviews with farmers. The others are based on integrated disease and pest management recommendations; 2See Materials and Methods
for more information on locations; 3Fungicides/insecticides; 4Environmental impact based on the environmental impact quotient (EIQ); see Materials and
Copyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
586 Peruvian and Ecuadorian Potato Production
Percentage of plots using formulations
Table 3. Environmental impact Quotient (EIQ), WHO hazard class and percentages of plots where farmers had applied the
specified pesticide active ingredients per location/province for the most commonly used fungicides and insecticides in two
locations in Ecuador (2007) and three in Peru (2006).
Perucuador E
Active ingredients EIQ WHO Class4
ChagllaHuamachucoazo ungurahua La Encañada ChimborT
Mancozeb 251.0334
248 III
.72 U 3 .0 .6 3.3 4.2
Maneb 21.43 U 0.0 0.0 0.0 2.7 1.3
Propineb 16.90 U 11.2 0.7 24.9 1.4 3.4
32.66 U 0.5 0.0 0.0 4.5 12.3
moxanil 35.48 III 38.8 27.0 24.4 29.2 17.9
imethomorph 24.01 U 26.6 0.0 0.0 10.8 3.7
Metalaxyl 3 19.07 III 4.2 59.2 46.7 10.8 8.1
Total plots
Acephate .80 .00 .00 .0 3 5.65 4.9
ta-cyfluthri31.57 II 0.0 36.1 16.9 0.0 0.0
Carbofuran 50.67 Ib 47.3 38.1 61.9 13.1 9.9
Chlorpyrifos 26.85 II 0.0 1.5 0.0 7.7 1.1
Cypermethrin 36.35 II 21.5 2.0 0.0 5.0 1.3
Deltamethrin 28.38 II 0.0 0.0 0.0 1.3 3.8
mbda-cyhalothr44.17 II 5.0 0.0 0.0 2.1 0.6
Methamidophos 36.83 Ib 14.7 14.4 13.8 5.8 20.7
Oxamyl 33.33 Ib 6.5 0.0 0.0 0.4 0.4
rofenofos59.53 II 0.0 0.0 0.0 22.1 2.7
Total plots 279 202 189 520 526
1Cymoixture w of thect fung copper hide (EIQ = 33.O class = III), folpet ( 31.73; WHO clU), man-
cozeb, or pr2Dimethomorph was in mixture with mozeb; 3Mas in mixtureith one of th contact funs; copper oxych (EIQ =
ds of potato produc-
. The EIQ permitted several types of
xanil was in m
opineb; ith one contaicides;
anc ydrox
etalaxyl w2; WH
wEIQ =
gicide ass =
33.20; WHO class = III), chlorothalonil (EIQ = 37.42; WHO class = U) or mancozeb; 4WHO recommended classification of pesticides by hazard; Ib = highly
hazardous; II = moderately hazardous; III = slightly hazardous; U = unlikely to present acute hazard in normal use.
haglla but not at all in Huamachuco or La Encañada. gicide applications. C
Within Ecuador, the fungicide dimethomorph and the
insecticide profenfos were used more in Chimborazo
than in Tungurahua while the insecticide methamidophos
was used more in Tungurahua than in Chimborazo (Ta-
ble 3).
Similarly, total pesticide amount used were also vari-
able among locations. Average insecticide amount used
in Chaglla was only 1 kg/ha/season while in Huama-
chuco it was about 2 kg/ha/season and in La Encañada
over 5 kg/ha/season (Table 4).
The total amount of pesticide used also varied between
countries. In general, more pesticides were applied in
Ecuador than in Peru (Table 4), however, this was only
evident by the total amount used and the EI, as the num-
ber of sprays per ha was relatively similar for the two
countries. Thus, farmers in Ecuador tended to use higher
dosages of fungicides. There were also differences rela-
ted to cultivar - in Ecuador the cultivar Superchola,
which is susceptible to late blight, received the most fun-
Data from the Ecuadorian survey showed that farmers
who had participated in a training program used pesti-
cides in a manner that resulted in lower EI than that of
farmers in the control communities (Table 5). This was
not only associated with reduction in the amount of pes-
ticide used but also in greater use of low EIQ products.
The main reduction in EI was associated with fungicide
applications; program participants applied less fungicide.
Non-participants from communities where the training
was done also had an EI lower than did farmers from
control communities (Table 5).
4. Discussion
Our study demonstrates the utility of the EIQ for assess-
ing health and environmental hazar
tion in the Andes
assessment that otherwise would have been more diffi-
cult (or not possible) based on total pesticide u se or num-
ber of applications. For example, in comparing the Peru-
opyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in 587
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t u
) and three in Peru (2006).
Table 4. Average number of pesticide sprays, pesticide amounsed (commercial formulation) and environmental impact (EI)
per ha in potato production in two locations in Ecuador (2007
Sprays/field/season Pesticide amount (L or Kg/ha/season) EI/ha1
Location / cultivar Number of Ha. Fungicide InsecticideFungicide Insecticide Fungicide InsecticideTotal
Chimborazo. Ecuador
Fripapa 117 3.40
166Gabriela 77
98 40 319
46. 17.
94 90 95 33
Rosita 14 2.00 1.30 2.86 3.88 71 188
Superchola 15 5.06 2.18 5.08 0.96 93 16 109
Fripapa 78 3.27 2.22 8.52 3.35 54 213
Gabriela 22 68 66 67
Rosita 34 2.89 1.78 7.74 4.72 107 65 172
14 4.00 2.00 3.57 2.32 76 40 116
Average E 3.22 1.70 6.75 2.65 134 48 182
Chaglla, Peru
Canchan 239 5.31 2.26 3.19 1.00 31 48 64
Yungay 225
14 30 14 00 08 62
Amarilis 73 2.81
1.37 1.58
55 Canchan 50
82 67 94
2.28 87 68
La Encañada,
Liberteña 43
Amarilis 21 3.01 3.01 5.33 6.62 53.30 134.04 187
Average Peru 3.64 2.77 3.14 2.94 36.83 54.12 91
1ntal impac t based on theironmentalt quotie); see MateriaMethods.
l pesticide amot used (commercial formulation), enmental impI) per hatio “Total EI/T
Environme env impacnt (EIQls and
Table 5. Totaunvironact (E and raotal
pesticide” in potato farming in three farmer groups in the highlands of Ecuador.
Farmer groups1
Total pesticide
(L or Kg/ha/season) Total EI/ha/season2
“Total EI/Total pesticide”
Farmer intervention p rogram Fungicide InsecticideFungicideInsecticideTotal Fungicide Insecticide
Participants 6.40 2.95 106.78 141.50 16.68 11.77 34.72
Non-participants in treatment communities 103.66
5.21 1.71 32.18 135.84 19.90 18.82
Non-participants in control com 10.32 2.02 174.96 30.30 205.26 16.95 15
1Data is from a survey carried out among Ecua
and Methods. dn far 2007; nmentaased oroctt (EIQ); srials
terms of pesticide hazard, the higher number
f fungicide sprays in Chaglla would be compensated to about double the dose in Ecuador, however insecticides
were applied more frequently and at a somewhat higher
oriamers in2Envirol impact bn the envinmental impa quotienee Mate
vian locations Chaglla and La Encañada, one could as-
sume that indifficult. It was evident that fungicides were applied at
some degree by the greater amount per ha of insecticide
applied in La Encañada. However, it may not be evident
that this would lead to an EI in La Encañada which was
two to three times that of Chaglla. Thus, the EI helped to
quantify impact patterns that could otherwise only be ge-
neralized. Similarly, comparing countries based solely on
number of applications and dosages would have been
dose in Peru. Since insecticides tend to have a higher
EIQ, the overall pesticide hazards were not clear for each
country. However, the EI assessment showed that on
average, hazard was twice as high in Ecuador. The com-
parison of farmers participating in IPM interventions
with those who did not participate (Table 5) also demon-
strated the utility of the EIQ.
Copyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
588 Peruvian and Ecuadorian Potato Production
cies related to methodo-
thermore, the number of fungicide applications
s [30].
he farmers. The high application rate
ming pro-
r ha per season as farmers in Hua-
The observation above on dosages highlights one of
the potential limitations of this approach that should be
controlled as much as possible in future applications of
the EIQ. The very large differences in fungicide dosages
between Ecuadorian and Peruvian farmers stimulated us
to consider possible discrepan
gy used in the surveys. As noted, these data are prima-
rily collected from farmer memory. Furthermore, there
are a number of estimations involved in the calculation of
dosage per ha, including area, volume of solution applied
per area, and even the concentration of the product in the
solution. Under general production practices, these things
are not usually measured precisely and a parti cular com-
ponent of the dosage estimation may vary greatly
among farmers. For example, one study in Ecuador de-
monstrated that volumes of pesticide applied per ha per
application ranged from 300 to over 900 L depending
on spray equipment [29]. The published documents
from the surveys we studied do not permit us to identify
possible factors that may have affected estimates of
dosage in either Ecuador or Peru, but the study does
highlight the need to verify the accuracy of dosage data
taken in future surveys. This is another utility of the
EIQ. As with any meta-analysis, the EIQ can help iden-
tify extreme differences that may represent reality or
may represent artifacts, but nonetheless warrant verifi-
Our field study in Ecuador indicated that potato pro-
duction in the Andes could be expected to have EI values
ranging from less than 100 to more than 100 0 (Table 2).
The values from the two farmer surveys all fell within
this range but in all cases toward the lower part of the
range. Fur
as lower than expected in all cases. Earlier surveys had
placed the average number of fungicide applications in
Peru at 6 [5] and in Ecuador at 7 [6,7], both of which are
higher than values reported in the surveys herein.
In spite of the data reported in the recent surveys, we
consider that the upper boundaries set by the Ecuadorian
study are not unrealistic. Oyarzun et al. [3] reported that
farmers in northern Ecuador sometimes spray potato
crops as much as 18 times per season, and another study
reported a similarly high number of application
omann et al. [26] found that cultivars susceptible to
late blight could not be protected in Peru or Ecuador us-
ing weekly or even 5-day schedules of application with a
contact fungicide.
The relatively low number of fungicide applications
reported in the recent surveys could result from several
factors, including cultivar resistance, prevailing weather
conditions, access to and price of fungicides and the fi-
nancial capacity of the farmers, and the disease manage-
ment capacity of t
ported by Oyarzun et al. [3] was from northern Ecua-
dor where farmers were growing the cultivar Capiro,
which is probably more susceptible than any used by
farmers in the surveys reported herein. The northern Ec-
uador farmers are also relatively large-scale and have
resources to buy inputs. Finally, these far mers often grow
Capiro under contract for potato chip production and are
therefore assured a good price. A survey done in 2006 by
the Ecuadorian national potato program (unpublished)
found that small-scale farmers in the central parts of the
country generally tend to apply less pesticide than their
compatriots in the north. Therefore, cost of fungicides
and household economies may have influenced the
amounts used in the surveys. This hypothesis is less evi-
dent in Peru where the larger farmers in Chaglla applied
more fungicide but less insecticide (Table 4). Late blight
severity was not measured in the two surveys reported
herein so we do not know if the interviewed farmers
were successful in controlling the disease. At least one
study from Bolivia indicated that many farmers do not
spray enough for adequate control of late blight [31].
Farmers with training tend more so than other farmers to
adjust the amount of fungicide for the level of resistance
in the cultivar and for weather conditions [9]. In the case
of Ecuador in our study, training also was associated
with differences in the amount of fungicide used, but this
was less evident with insecticides (Table 5).
Other studies using the EIQ have also reported high EI
values. In some of the locations studied in Europe, EI per
hectare in tomato production was over 1000 and on the
island of Reunion EI per hectare (tomato) was over 1500
[32]. Tomato producers in Reunion used about 40 kg·ha–1
of pesticide per season. In our study, the far
am at the CIP-Quito experimental site with cultivar
Capiro involved 63 kg·ha-1 of pesticide per season result-
ing in an EI of 1235.
Yield data from the Ecuadorian and Peruvian farmer
surveys indicated that productivity was highly variable
among farmers and not clearly associated with EI. In the
three study locations in Peru, yield ranged from about 5
t·ha–1 to 30 t·ha–1 (data is not shown). Farmers in Chaglla
had similar total EI pe
achuco, but their average productivity was about three
times that of the latter. On the other hand, farmers in
Huamachuco had similar productivity but a much higher
EI than farmers in La Encañada. Average yield for farm-
ers participating in the intervention program in Ecuador
was 8.4 t·ha–1 and the average yield for non-participating
farmers in the two control farmer groups in Ecuador was
6.3 t·ha–1 (data not shown). The extent to which pesticide
use may have influenced yields is not known.
opyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in 589
Peruvian and Ecuadorian Potato Production
and limi-
ide usage
robable or definite risk to hu-
lications in five zones in the high-
pesticide use patterns, and particularly to com-
ys in Ecuador. This research was funded by
er (CIP) with support from
elopment Assistance (DAN-
Numerous tools have been developed to assess envi-
ronmental and human health hazards or risks associated
with pesticide use [12,14]. Levitan et al. [14] classified a
number of tools as ranging from anecdotal accounts to
holistic assessments of impact of agriculture. For each
tool, examples, units of measure, objectives
tions were presented [14]. Examples of recent scoring
systems that have been used for pesticides include the
Environmental Hazard Index and the Priority Substances
List in Canada [16]; the Ecological Relative Risk indica-
tor in Austria [33], the European Risk Ranking method
(EURAM); the Chemical Hazard Evaluation for Man-
agement Strategies from University of Tennessee; and
Purdue Research Foundation’s Pollution Prevention Pro-
gress Measurement Method in the USA [12].
The EIQ is an external analysis, insensitive to site-
specific data, which makes the method insensitive to lo-
cal environmental parameters, but also highly practical as
there is no need for detailed information that often is not
available in developing countries. The primary advantage
of using a common metric for comparing pestic
ross time and space is that it can facilitate comparisons
across these dimensions and among crops. However, for
such comparisons there is an underlying assumption that
the metric is appropriate for all locations. The EIQ is
composed of three hazard components: farm worker,
consumer and environment, which obviously are not the
same in all locations. Based on a rapidly increasing body
of knowledge, hazards to farm workers (and their fami-
lies) is higher in the developing world than in industria-
lized countries [34,35]. The current EIQ values do not
take into account differences in application technology or
in use of personal protective equipment (Kovach J, pers.
comm.) and hence some overestimation in applicator
exposure may occur in higher income countries, or even
underestimation in developing countries where use of
protective clothing is rare [4,29]. Greater bystander ex-
posure might also be expected in lower and middle in-
come countries where separation of agricultural opera-
tions and home life is less clear. As well, potentially vul-
nerable fauna may have greater exposure due to unsafe
pesticide use practices e.g. washing backpack sprayers in
streams, or may themselves be more susceptible to pesti-
cide toxicity due to species differences and variation in
environmental conditions.
The EIQ, e.g., is heavily weighted to assess impacts on
beneficial insects of apple production in the USA, for
which the equation was originally developed, and there
are particular limits for the human health component.
Firstly, the use of a limited range of ordinal ratings to
assign an a.i. a possible, p
an health and the low ordinal values assigned to these
ratings dilute the underlying extent of variability in toxi-
city values that may be present. This ordinal ranking
would cause the EIQ values assigned to a.i. to appear
more similar in hazard level than would be reflected in
the original data, subsequently attenuating the variation
in the hazard present for different crops and geographic
areas. Secondly, studies used for dermal toxicity (DT)
values are entirely rabbit or rat based models with a.i.
being applied directly to the skin. The EIQ should thus
be modified in areas where farmers do use protective
clothing, although, again, this would appear to be rare in
developing countries.
While, to our knowledge, this article is the first EIQ-
based evaluation of pesticide use on potatoes in develop-
ing countries, it follows other studies where the EIQ was
used on other crops in low to lower-middle income coun-
tries. Mazlan and Mumford [17] compared cabbage farm-
ers and insecticide app
nds of Malaysia. Bardenes-Perez and Shelton [18] used
the EIQ to compare potential impact of cruciferous vege-
tables growing in the Kenyan highlands and in three ar-
eas in the Kullu Valley in India. Morse et al. [21] as-
sessed the environmental impact of an agricultural shift
to genetically modified cotton production in South Africa.
Muhammetoglu and Uslu [36] used the EIQ to select the
least detrimental pesticide from an evaluation of different
pesticide management scenarios in an agricultural area in
At this time the EIQ appears to be an effective tool for
comparing potato production patterns in the diverse con-
ditions found in developing countries. It is understood
that the EIQ primarily should be used as a tool for agri-
cultural practitioners to rapidly assess the hazards associ-
ated with
re the relative differences among different pesticide
use practices; it does not constitute a detailed risk as-
sessment of a particular scenario. It is essential that the
EIQ values from the Cornell University web page be
constantly updated and adjusted with the latest health and
environmental impact information on pesticides, and that
agronomists and researchers in developing countries ex-
plore ways to make the EIQ more representative of local
5. Acknowledgements
We thank the Agricultural Development Economics Di-
vision of the Food and Agriculture Organization of the
United Nations for letting us analyze their data from
farmer surve
the International Potato Cent
the Danish International Dev
IDA) and the Canadian International Development Agen-
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Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
590 Peruvian and Ecuadorian Potato Production
Potato (
tophthora infe Profile,” Proceed-
5, No. 3, July 2009, pp. 255-
cy (CIDA).
[1] A. Devaux, M. Ordinola, A. Hibon and R. Flores, “El
sector papa en la región andina: Diagnostico y elementos
para una visión estratégica (Bolivia, Ecuador y Perú),”
Centro Internacional de la Papa, 2010.
[2] R. Egúsquiza and W. Apaza, “Rancha of
stans) in Peru. CountryPhy-
ings the International Workshop Complementing Resis-
tance to Late Blight (Phytophthora Infestolans) in the
Andes, February 2001, International Potato Center, Lima,
Peru, October 2002, pp. 27-37.
[3] P. J. Oyarzún, C. D. Garzón, D. Leon, I. Andrade and G.
A. Forbes, “Incidence of Potato Tuber Blight in Ecua-
dor,” American Journal of Potato Research, Vol. 82,
March 2005, pp. 117-122.
[4] F. A. Orozco, D. C. Cole, G. A. Forbes, J. Kroschel, S.
Wanigaratne and D. Arica, “Monitoring Adherence to the
International FAO Code of Conduct on the Distribution
and Use of Pesticides: Highly Hazardous Pesticides in
Central Andean Agriculture and Farmers’ Rights to
Health,” International Journal of Occupational and En-
vironmental Health, Vol. 1
[5] O. Ortiz, P. Winters and H. Fano, “La percepción de los
agricultores sobre el problema del tizón tardío o rancha
(Phytophthora infestans) y su manejo: Estudio de casos
en Cajamarca, Perú,” Revista Latinoamericana de la
Papa, Vol. 11, No. 1, January 1999, pp.97-120.
[6] C. Crissman, P. Espinosa and V. H. Barrera, “El uso de
plaguicidas en la producción de papa en Carchi,” In: D.
Yanggen, C. Crissman and P. Espinosa, Eds., Los
Plaguicidas: Impactos en producción, salud y medio
ambiente en Carchi, Ecuador, CIP – INIAP, Quito, 2003,
pp. 9-24.
[7] M. Paredes, “Peasants, Potatoes and Pesticides - Hetero-
geneity in the Context of Agricultural Modernization in
the Highland Andes of Ecuador,” Ph.D. Dissertation,
Wageningen University, Wageningen, 2010.
[8] IPCS (International Program on Chemical Safety), “The
WHO Recommended Classification of Pesticides by
Hazard and Guidelines to Classification 2004,” World
Health Organization, June 2006.
[9] O. Ortiz, K. A. Garrett, J. J. Heath, R. Orrego and R. J.
Nelson, “Management of Potato Late Blight in the Peru-
vian Highlands: Evaluating the Benefits of Farmer Field
Schools and Farmer Participatory Research,” Plant Dis-
ease, Vol. 88, May 2004, pp. 565-571.
[10] CIMMYT, “La formulación de recomendaciones a partir
de datos agronómicos: un manual metodológico de
evaluación económica,” CIMMYT, México, 1988.
[11] Food and Agriculture Organization of the United Nations,
“Panel of Experts on Pesticide Management: Report on
the Second Session, 7-10 November 2
, 006,” Rome, Italy
[12] C. Pittinger, T. Brennan, D. Badger, P. Hakkinen and M.
C. Fehrenbacher, “Aligning Chemical Assessment
across the Hazard-Risk Continuum,” Risk Analysis, Vol.
23, No. 3, June 2003, pp. 529-535.
[13] J. Kovach, C. Petzoldt, J. Degni and J. Tette, “A Method
ach, “Assessing the
ts of Agricultural Pesti-
to Measure the Environmental Impact of Pesticides,” New
York’s Food and Life Sciences Bulletin, No. 139, 1992,
pp. 1-8.
[14] L. Levitan, I. Merwin and J. Kov
Relative Environmental Impac
cides: The Quest for a Holistic Method,” Agriculture,
Ecosystems and Environment, Vol. 55, No. 3, October
1995, pp. 153-168. doi:10.1016/0167-8809(95)00622-Y
[15] J. Maud, G. Edwards-Jones and F. Quin, “Comparative
Evaluation of Pesticide Risk Indices for Policy Develop-
ment and Assessment in the United Kingdom,” Agricul-
ture, Ecosystems and Environment, Vol. 86, No. 1, July
2001, pp. 59-73. doi:10.1016/S0167-8809(00)00258-9
[16] G. J. Gallivan, H. Berges and B. McGee, “Evaluation of
the Changes in Pesticide Risk. Research Project SR9128:
Survey of Pesticide Use and Evaluation of the Changes in
Pesticide Risk on Agricultural Crops in Ontario,” June
[17] N. Mazlan and J. Mumford, “Insecticide Use in Cabbage
Pest Management in the Cameron Highlands, Malaysia,”
Crop Protection, Vol. 24, No. 1, January 2005, pp. 31-39.
ultural Practices among Farmers
[18] F. R. Badenes-Perez and A. M. Shelton, “Pest Manage-
ment and Other Agric
Growing Cruciferous Vegetables in the Central and
Western Highlands of Kenya and the Western Himalayas
of India,” International Journal of Pest Management, Vol.
52, No. 4, 2006, pp. 303-315.
[19] P. Cross and G. Edwards-Jones, “Variation in Pesticide
Hazard from Arable Crop Production in Great Britain
from 1992 to 2002: Pesticide Risk Indices and Policy
Analysis,” Crop Protection, Vol. 25, No. 10, October
2006, pp. 1101-1108. doi:10.1016/j.cropro.2006.02.013
rnative Way to Evalu-[20] T. J. Greitens and E. Day, “An Alte
ate the Environmental Effects of Integrated Pest Man-
agement: Pesticide Risk Indicators,” Renewable Agricul-
ture and Food Systems, Vol. 22, No. 3, September 2007,
pp. 213- 222. doi:10.1017/S1742170507001755
[21] S. Morse, R. Bennet and Y. Ismael, “Environmental Im-
pact of Genetically Modified Cotton in South Africa,”
Agriculture, Ecosystems and Environment, Vol. 117, No.
4, December 2006, pp. 277-289.
[22] G. A. Kleter, R. Bhula, K. Bodnaruk, E.Carazo, A. S.
Felsot, C. A. Harris, A. Katayama, H. A. Kuiper, K. D.
Racke, B. Rubin, Y. Shevah, G. R. Stephenson, K. Ta-
opyright © 2011 SciRes. JEP
Use of the Environmental Impact Quot i ent to Estimate Health and Environmen t al Impacts of Pestici d e Usage in
Peruvian and Ecuadorian Potato Production
Copyright © 2011 SciRes. JEP
Crops and the Associ-
ental Perspect
naka, J. Unsworth, R. D. Wauchope and S. Wong, “Al-
tered Pesticide Use on Transgenic
ated General Impact from an Environmive,”
Pest Management Science, Vol. 63, No. 11, September
2007, pp. 1107-1115. doi:10.1002/ps.1448
[23] M. Stenrod, H. E. Heggen, R. Bolli and O. M. Eklo,
“Testing and Comparison of Three Pesticide Risk Indica-
tor Models under Norwegian Conditions: A Case Study in
the Skuterud and Heiabekken Catchments,” Agriculture,
Ecosystems and Environment, Vol. 123, No. 1-3, January
2008, pp. 15-29. doi:10.1016/j.agee.2007.03.003
[24] C. A. Bahlai, YinGen Xue, C. M. McCreary, A. W.
Schaafsma and R. H. Hallett, “Choosing Organic Pesti-
cides over Synthetic Pesticides May Not Effectively
Mitigate Environmental Risk in Soybeans,” PLoS ONE,
Vol. 5, No. 6, 22 June 2010.
[25] G. Brookes and P. Barfoot, “Global Impact of Biotech
Crops: Environmental Effects, 1996-2008,” AgBioForum,
Vol. 13, No. 1, 2010, pp. 76-94.
[26] P. Kromann, A. Taipe, W. G. Perez and G. A. Forbes,
“Rainfall Thresholds as Support
Applications in the Control of Pota
for Timing Fungicide
to Late Blight in Ec-
uador and Peru,” Plant Disease, Vol. 93, No. 2, February
2009, pp. 142-148. doi:10.1094/PDIS-93-2-0142
[27] P. Gallegos and G. Avalos, “Control integrado de
and Agricultural Organization (FAO),
tact Fungicide in the Control of
Premnotrypes vorax (Hustache) mediante manejo de la
población de adultos y control químico en el cultivo de
papa,” Revista Latinoamericana de la Papa, Vol. 8, No. 1,
1995, pp. 55-60.
[28] R. Cavatassi, M. Gonzale z, P. Winters, J. Andrade-P
G. Thiele and P. Espinosa, “Linking Smallholders to the
New Agricultural Economy: An Evaluation of the Plata-
formas Program in Ecuador,” ESA Working Paper No.
09-06, Agricultural Development Economics Division
(ESA), The Food
Rome, Italy, 2009.
[29] P. Kromann, D. Leon, A. Taipe, J. L. Andrade-Piedra,
and G. A. Forbes, “Comparison of Two Strategies for Use
of Translaminar and Con
Potato Late Blight in the Highland Tropics of Ecuador,”
Crop Protection, Vol. 27, No. 7, July 2008, pp. 1098-
1104. doi:10.1016/j.cropro.2008.01.006
[30] W. E. Peterson, A. Zuloaga, B. E. Swanson, J. E. Uquillas
and C. Crissman, “El sistema tecnológico de la papa en el
Ecuador,” Centro Internacional de la Papa, Fundagro,
in the Andes,” In: Impact on a Changing World:
e Environmental Impact of the Pesti-
Eco- systems
[31] R. Torrez, J. Tenorio, C. Valencia, R. Orrego, O. Ortiz, R.
Nelson and G. Thiele, “Implementing IPM for Late
Program Report 1997-98, The International Potato Center,
Lima, pp. 91-99.
[32] R. Bues, M. Dadomo, J. P. Lyannaz, G. di Lucca, J. I.
Macua Gonzalez, H. Prieto Losada and Y. Dumas,
“Evaluation of th
cides Applied in Processing Tomato Cropping,” Acta
Horticulturae, No. 613, 2003, pp. 255-258.
[33] F. Sánchez-Bayo, S. Baskaran and I. R. Kennedy, “Eco-
logical Relative Risk (EcoRR): Another Approach for
riSk Assessment of Pesticide s,” Agriculture,
and Environment, Vol. 91, No. 1-3, September 2002, pp.
37-57. doi:10.1016/S0167-8809(01)00258-4
[34] C. Wesseling, M. Corriols and V. Bravo, “Acute Pesticide
Poisoning and Pesticide Registration in Central America,”
Toxicology and Applied Pharmacology, Vol. 207, No. 2,
oxic Burden in an
ental Impacts of pesti-
Sup. 1, September 2005, pp. 697-705.
[35] D. C. Cole, S. Sherwood, M. Paredes, L. H. Sanin, C.
Crissman, P. Espinosa and F. Muñoz, “Reducing Pesti-
cide Exposure and Associated Neurot
Ecuadorian Small Farm Population,” International Jour-
nal of Occupational and Environmental Health, Vol. 13,
No. 3, July 2007, pp. 281-289.
[36] A. Muhammetoglu and B. Uslu, “Application of Envi-
ronmental Impact Quotient Model to Kumluca Region,
Turkey to Determine Environm
cides,” Water Science and Technology Journal, Vol. 56,
No. 1, January 2007, pp. 139-145.