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A faunistic survey of mites was conducted in many product stores during a 6-year study period, 2000-2005, in Greece. A total of 1,073 samples were taken from 34 Greek counties. The survey was carried out on grains (wheat, maize, oat, barley), flour, bran, manufactured agricultural foodstuffs, dried fruits (figs, raisins), residues and dust, stored in varying quantities in five types of storage facilities (stores of agricultural cooperative unions, farm stores, commercial stores, flour mills and silos). Dominance-frequency analysis and redundancy analysis (RDA) were used to reveal the preferences of the collected taxa. Approximately 55% of the samples contained mites and 65 mite taxa were identified, belonging to 15 families in four orders. Six species, namely, Acarus gracilis Hughes, A. immobilis Griffiths, Caloglyphus oudemansi (Zachvatkin), Suidasia medanensis Oudemans, Tyrophagus perniciosus Zachvatkin and Kleemania plumigera (Oudemans), were new to the fauna of Greece. Five species, Tyrophagus similis Volgin, Blattisocius mali (Oudemans), Neoseiulus barkeri (Hughes), Cheyletus cacahuamilpensis Baker and Storchia robustus (Berlese), were recorded for the first time in stored products in Greece. Lepidoglyphus destructor (Schrank), Tyrophagus putrescentiae (Schrank) and Acarus siro L. were dominant or intermediate in all storage facilities examined. Cheyletus malaccensis Oudemans was the most common predatory mite. The highest percentage of infestation (65.3) was recorded in the samples from stores of agricultural cooperative unions. Residue-type materials had the highest degrees and percentages of infestation.
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Exp Appl Acarol (2008) 44:213–226
DOI 10.1007/s10493-008-9145-y
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Mites associated with stored products in Greece
Nickolas E. Palyvos · Nickolas G. Emmanouel ·
Costas J. Saitanis
Received: 28 October 2007 / Accepted: 20 March 2008 / Published online: 1 April 2008
© Springer Science+Business Media B.V. 2008
Abstract A faunistic survey of mites was conducted in many product stores during a
6-year study period, 2000–2005, in Greece. A total of 1,073 samples were taken from 34
Greek counties. The survey was carried out on grains (wheat, maize, oat, barley), Xour,
bran, manufactured agricultural foodstuVs, dried fruits (Wgs, raisins), residues and dust,
stored in varying quantities in Wve types of storage facilities (stores of agricultural coopera-
tive unions, farm stores, commercial stores, Xour mills and silos). Dominance-frequency
analysis and redundancy analysis (RDA) were used to reveal the preferences of the col-
lected taxa. Approximately 55% of the samples contained mites and 65 mite taxa were
identiWed, belonging to 15 families in four orders. Six species, namely, Acarus gracilis
Hughes, A. immobilis GriYths, Caloglyphus oudemansi (Zachvatkin), Suidasia medanensis
Oudemans, Tyrophagus perniciosus Zachvatkin and Kleemania plumigera (Oudemans),
were new to the fauna of Greece. Five species, Tyrophagus similis Volgin, Blattisocius
mali (Oudemans), Neoseiulus barkeri (Hughes), Cheyletus cacahuamilpensis Baker and
Storchia robustus (Berlese), were recorded for the Wrst time in stored products in Greece.
Lepidoglyphus destructor (Schrank), Tyrophagus putrescentiae (Schrank) and Acarus siro
L. were dominant or intermediate in all storage facilities examined. Cheyletus malaccensis
Oudemans was the most common predatory mite. The highest percentage of infestation
(65.3) was recorded in the samples from stores of agricultural cooperative unions. Residue-
type materials had the highest degrees and percentages of infestation.
Keywords Stored-product mites · Grains · Storage facilities · Dominance · Frequency ·
RDA · Dust · Residue
N. E. Palyvos (&) · N. G. Emmanouel
Laboratory of Agricultural Zoology and Entomology, Agricultural University of Athens,
75 Iera Odos, 11855 Athens, Greece
e-mail: palyvos@in.gr
C. J. Saitanis
Laboratory of Ecology and Environmental Sciences, Agricultural University of Athens,
75 Iera Odos, 11855 Athens, Greece
214 Exp Appl Acarol (2008) 44:213–226
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Introduction
Insects, mites and rodents are the major pests of stored agricultural products. It is well
documented that insects (Coleoptera, Lepidoptera and Psocoptera) and mites are the most
damaging pests associated with stored grains. The degree of a product’s infestation
depends on the pests involved, the environmental conditions (e.g. temperature and moisture
content), how the product is stored and the degree of proper hygiene conditions. The type of
storage technology applied is considered a serious abiotic factor inXuencing the stored-grain
quality (Stejskal et al. 2003).
Studies intended to record the mites infesting stored agricultural products have been
conducted in several regions throughout the world (O’Farrell and Butler 1948; Zdarkova
1967, 1979, 1998; Cusack et al. 1975; JeVrey 1976; Pagliarini 1979; Saleh et al. 1985;
Corpuz-Raros et al. 1988; Mahmood 1992; Emmanouel et al. 1994; Franz et al. 1997;
Long-shu and Qing-Hai 1997; Thind and Clarke 2001; Stejskal et al. 2003; Kucerova and
Horak 2004; Hubert et al. 2006). Although some general trends can be seen, data from one
study may not be comparable with others and generalizations are often problematic.
Although European Union and USA administratives dictate a zero or near-zero toler-
ance level for mite infestation in stored products (Krizkova-Kudlikova et al. 2007), the
problem of stored-product mites of various agricultural commodities still exist. Mites can
seriously reduce the quality and quantity of stored agricultural products. They cause not
only a direct weight loss in food materials, but they also seriously reduce the viability of
seed stocks, as their attack is mainly conWned to the embryo (Zdarkova 1996). In wheat
grains mites destroy mostly the germ and only exceptionally the endosperm (Solomon
1946). Moreover, the stored product may acquire an odor due to lipid secretions by mites.
Stored-product mites cause serious economic losses by feeding on stored grain and endan-
ger the public health by contamination of food with allergens. Several studies demonstrated
that storage mites caused symptoms of bronchial asthma, allergic rhinitis and conjunctivi-
tis, particularly in rural occupational environments (Blainey et al. 1989; Iversen and Dahl
1990). There is increasing evidence that human health can be aVected by the ingestion of
mites and/or their by-products (Scala 1995). Mites also serve as vectors for several kinds of
moulds and bacteria (Zdarkova 1967; Hubert et al. 2003). Under favorable conditions,
mites, whether fungivorous, granivorous, predators or parasites, may reach high densities,
capable of causing direct or indirect damage (Sinha 1973).
Although many studies are available about the occurrence of other pest categories of
stored products (e.g. insects), information about mites is still inadequate. Previous studies
in Greece have indicated that mites were dominant in raw stored grains during the entire
year (Athanassiou et al. 2001, 2003; Palyvos and Emmanouel 2006). The objective of our
present investigation was to study the composition of the mite species occurring in diVerent
types of storage facilities, in the framework of a large-scale survey in Greece.
Materials and methods
Sampling started at the beginning of 2000 and was completed at the end of 2005. Samples
were collected from 34 counties in Greece. These samples included a great variety of stored
agricultural products from the following types of storage facilities (in parentheses the
abbreviation of store type and the number of stores): i. stores of agricultural cooperative
unions (ACUs, 17), ii. farm stores (FARMs, 49), iii. commercial stores (COMs, 22), iv. Xour
mills (MILLs, 9), and v. silos (SILOs, 12). A total of 1,073 sub-samples were examined from
Exp Appl Acarol (2008) 44:213–226 215
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the following groups of stored products (in parentheses the abbreviation of each group and
the number of sub-samples): 1. animal fodder (maize, wheat, barley, oats, straw, clover)
(FODDERs, 498), 2. Xour and bran (wheat, maize) (FLOURs, 156), 3. edible products
(grains, legumes, dried fruits, cheese) (EDIBLE, 67), 4. various other products (seeds as
propagules, cotton Wber etc.) (OTHERs, 51), and 5. residues and dusts (RESIDs, 301).
Sampling equipment
A plastic cylindrical receptacle of 300 ml capacity was used for obtaining samples from
animal fodder, Xour and seeds. Sampling of straw, clover, etc., was conducted by hand.
Samplings of cheese products, from cooling rooms in cheese-dairies and supermarkets, was
conducted by scraping oV part of the surface of the products with a knife. A small broom
and a dustpan was used for the collection of residues from agricultural products and dust
from the Xoors and the corners of the stores.
Sampling procedures
The sampling procedures were modiWed according to the type of material, its quantity and
the type of storage facility. Samples of bulk grain were taken from the surface of the bulk.
In bins and silos, samples were taken in the upper grain layer via the hatch at the top.
Where grain, Xour, legumes etc. were stored in sacks, a sample was taken from the top
20 cm of the product.
The samples weighed from 25 to 250 g according to the product. Each sample was
placed into a plastic bag, labeled with the origin of its collection and the type of the prod-
uct’s storage. The samples were transferred to the laboratory and examined as soon as pos-
sible. The Berlese–Tullgren method was used to extract mites from the samples (Evans
et al. 1961; Cusack et al. 1975). The device used was based on the ‘modiWed Tullgren
apparatus’, as suggested by Haarlov (1947). This apparatus is a unit of 36 funnels based on
a tiered system of strip lighting and funnel bearing shelves. Alternate shelves carried four
60-W strip lights as heat source. The heat from the light bulbs desiccated the sample, forcing
the mite individuals to burrow deeper into the substrate, eventually falling into a screw-top
collecting vial suspended underneath. The sample was completely dried due to the continu-
ous eVect of the lights. Each sample was then weighed in order to express the mites found
as individuals/dry weight unit, which is considered the most accurate approach (Cusack
et al. 1975; Emmanouel et al. 1994). The collected mites were identiWed using a compound
research microscope.
In addition to these sampling procedures, visual inspection of all locations visited was
carried out. All structures, machinery and equipment etc. were examined and the presence
or absence of pests was recorded. Information was also obtained on types of structures,
presence or absence of ventilating and thermistor systems, duration of storage, degree of
hygiene practiced and control measures normally adopted.
Data analysis
The taxa collected were categorized using the criteria of dominance and frequency (Curry
1973; Cusack et al. 1975; Emmanouel et al. 1994). ‘Dominance’ indicates the percentage
of individuals of a given taxon, compared with the total number of individuals of all taxa
found. Hence, a given particular taxon is classiWed as ‘dominant’, ‘inXuent’ or ‘recedent’, if
it constitutes >10, 5–10 or <5% of the total number of individuals, respectively. Similarly,
216 Exp Appl Acarol (2008) 44:213–226
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three categories are recognized for the ‘frequency’ of occurrence of a taxon in the samples:
it is classiWed as ‘constant’, ‘accessory’ or ‘accidental’, if it occurs in >50, 25–50 or <25%
of the total number of samples, respectively.
The number of taxa per store type per product was submitted to analysis of variance
(ANOVA) (type III SS). Fisher’s LSD test was used for the analysis of the diVerences
between groups based 95%-conWdence ranges. Before the analysis, data were transformed
according to Box–Cox procedure (Box and Cox 1964).
The data were further submitted to multivariate analysis. From an ecological point of
view, abundant as well as rare species may be important and thus all were included in the
analysis. For the ordination analysis the environmental variables (‘store type’ and ‘prod-
uct’) were split to dummy (0–1) variables (one dummy variable for each class of each envi-
ronmental variable). In order to choose between linear and unimodal ordination analysis
methods, the data were preliminarily submitted to detrended canonical correspondence
analysis (DCCA) and the gradient length, that measures the extent of species turnover (beta
diversity) along the coordination axes, was calculated. The longest gradient value was quite
short (1.42) suggesting the use of a linear gradient analysis model (PCA or RDA) (Lepn
and Kmilauer 2003). Thus, the data were submitted to RDA and PCA analyses using
several combinations of scaling (either inter-species correlation scaling or sample distance
scaling) and transformations.
For data processing Microsoft Excel v. 2003 was used. ANOVA was conducted with
XLSTAT software. Ordination analysis (calculations and biplot) was performed using
CANOCO v. 4.5.
Results
Approximately 55% of the samples contained mites, of which 65 taxa in 15 families and
four orders were identiWed (Table 1). Twenty-two taxa were in the order Astigmata, corre-
sponding to 92.7% of the total number of the collected mites, followed by 5.7% Prostig-
mata, 1.3% Mesostigmata and 0.2% Cryptostigmata. Six species were new to the fauna of
Greece: Acarus gracilis Hughes, A. immobilis GriYths, Caloglyphus oudemansi (Zachvatkin),
Suidasia medanensis Oudemans, Tyrophagus perniciosus Zachvatkin, and Kleemania
plumigera (Oudemans). Five species were recorded for the Wrst time in stored products in
Greece: Tyrophagus similis Volgin, Blattisocius mali (Oudemans), Neoseiulus barkeri
(Hughes), Cheyletus cacahuamilpensis Baker, and Storchia robustus (Berlese).
Concerning the number of taxa, no statistical diVerence was found between store types
(F= 0.825, df = 4, P= 0.511). The store type * product interaction was also not statisti-
cally signiWcant (P=0.465). DiVerences were found between product types (F=8.324,
df = 4, P= 0.0001), with ‘residues’ showing the highest number of species and ‘Xour’ the
lowest (Fig. 1).
Stores of agricultural cooperative unions (ACUs)
Sixty-Wve percent of the samples contained mites. Most samples contained infestations of
<10 mites/10 g d.w., but some ‘residue’ samples had higher infestations (Table 2).
Forty-four taxa of mites were identiWed (Table 1). Tyrophagus putrescentiae (Schrank)
and Lepidoglyphus destructor (Schrank) were ‘dominant’ and ‘accessory’ and occurred in
59 and 54 of the 213 samples, respectively. Aleuroglyphus ovatus (Troupeau) was ‘inXu-
ent’ and ‘accidental’. The following taxa were recorded only in this type of storage facility:
Exp Appl Acarol (2008) 44:213–226 217
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Table 1 Dominance and frequency of mite taxa found in each type of storage facility
ID Taxa ACUs COMMs FARMs MILLs SILOs
Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq.
I. Astigmata
1Acarus gracilis 0.50 R 0.42 Ac
2Acarus immobilis 0.58 R 1.41 Ac 0.02 R 0.40 Ac 0.14 R 0.42 Ac
3Acarus siro 0.46 R 7.51 Ac 38.36 D 9.92 Ac 9.23 In 4.40 Ac 25.16 D 4.29 Ac 25.87 D 3.33 Ac
4Aleuroglyphus ovatus 7.83 In 6.57 Ac 1.21 R 3.97 Ac 4.78 R 5.44 Ac
5 Anoetidae 0.05 R 0.47 Ac
6Caloglyphus oudemansi 0.05 R 0.79 Ac 0.14 R 0.42 Ac 0.07 R 1.43 Ac
7Caloglyphus sp. 0.01 R 0.47 Ac 0.12 R 0.40 Ac
8Carpoglyphus lactis 2.59 R 5.16 Ac
9Chortoglyphus arcuatus 0.07 R 1.41 Ac 10.07 D 1.98 Ac 0.72 R 1.05 Ac 0.43 R 2.86 Ac
10 Ctenoglyphidae 0.14 R 0.84 Ac
11 Dermatophagoides farinae 0.38 R 2.35 Ac 0.05 R 1.19 Ac 0.77 R 0.84 Ac 2.23 R 4.29 Ac
12 Glycyphagus domesticus 0.17 R 1.88 Ac 0.05 R 1.19 Ac 2.65 R 2.51 Ac 4.03 R 10.00 Ac
13 Gohieria fusca 0.11 R 2.81 Ac 0.003 R 0.40 Ac 0.43 R 0.63 Ac 6.33 In 4.29 Ac
14 Lepidoglyphus destructor 26.95 D 25.40 A 37.92 D 17.46 Ac 36.08 D 13.60 Ac 33.07 D 18.57 Ac 32.34 D 20.00 Ac
15 Rhizoglyphus echinopus 0.52 R 1.41 Ac 0.33 R 0.40 Ac 0.44 R 0.84 Ac 0.17 R 1.67 Ac
16 Rhizoglyphus sp. 0.37 R 1.88 Ac 0.45 R 1.59 Ac 0.23 R 1.05 Ac
17 Suidasia medanensis 0.07 R 1.41 Ac 0.01 R 0.40 Ac 0.23 R 0.21 Ac 0.86 R 1.43 Ac
18 Suidasia nesbitii 3.62 R 2.82 Ac 0.09 R 1.59 Ac 1.08 R 1.67 Ac 0.14 R 1.43 Ac 0.33 R 3.33 Ac
19 Tyrophagus longior 0.02 R 1.41 Ac 0.95 R 1.46 Ac
20 Tyrophagus perniciosus 0.01 R 0.47 Ac
21 Tyrophagus putrescentiae 47.17 D 27.70 A 8.31 In 24.21 Ac 20.09 D 15.70 Ac 14.74 D 14.29 Ac 6.14 In 18.30 Ac
22 Tyrophagus similis 0.04 R 1.59 Ac 0.89 R 1.05 Ac
II. Prostigmata
23 Acarophenax tribolii 0.01 R 0.47 Ac 0.14 R 0.63 Ac
24 Acaropsis docta 0.43 R 1.88 Ac 0.01 R 0.40 Ac 0.04 R 0.21 Ac 0.14 R 1.43 Ac
25 Acaropsis sollers 0.01 R 0.47 Ac 0.03 R 1.59 Ac 0.72 R 2.51 Ac 0.29 R 4.29 Ac 0.33 R 3.33 Ac
26 Bdellidae 0.05 R 2.82 Ac 0.01 R 0.79 Ac 0.08 R 0.21 Ac
27 Caligonellidae 0.08 R 1.41 Ac 0.05 R 0.79 Ac 2.48 R 1.25 Ac 0.33 R 1.67 Ac
28 Chelacheles sp. 0.15 R 0.40 Ac
218 Exp Appl Acarol (2008) 44:213–226
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Table 1 continued
ID Taxa ACUs COMMs FARMs MILLs SILOs
Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq.
29 Cheletomorpha lepidopterorum 0.13 R 2.78 Ac 0.12 R 0.42 Ac 1.66 R 3.33 Ac
30 Cheyletus aversor 0.003 R 0.40 Ac 0.10 R 0.21 Ac 0.07 R 1.43 Ac
31 Cheyletus cacahuamilpensis 0.01 R 0.47 Ac 0.07 R 1.43 Ac
32 Cheyletus eruditus 0.05 R 1.19 Ac 0.37 R 1.25 Ac 0.86 R 4.29 Ac
33 Cheyletus malaccensis 5.08 In 16.4 Ac 0.60 R 11.90 Ac 4.86 R 12.13 Ac 1.65 R 8.57 Ac 10.28 D 15.00 Ac
34 Cheyletus trux 0.37 R 4.70 Ac 0.37 R 2.38 Ac 0.25 R 0.63 Ac 0.22 R 1.43 Ac
35 Cunaxa setirostris 0.02 R 0.79 Ac 0.27 R 1.25 Ac 1.16 R 3.33 Ac
36 Eupodidae 0.02 R 0.21 Ac
37 Ker sp. 0.003 R 0.40 Ac 0.08 R 0.42 Ac
38 Lorryia nesziyyonensis 0.03 R 1.41 Ac 0.04 R 0.40 Ac 0.17 R 0.42 Ac 0.36 R 2.86 Ac 0.17 R 1.67 Ac
39 Lorryia sp. 0.29 R 0.94 Ac 0.04 R 1.19 Ac 0.56 R 1.05 Ac 0.50 R 3.33 Ac
40 Neopronematulus sp. 0.15 R 0.42 Ac
41 Pseudocheyletidae 0.02 R 0.21 Ac
42 Pseudotriophtydeus vegei 0.08 R 0.63 Ac
43 Pyemotes sp. 0.07 R 0.47 Ac 0.08 R 0.21 Ac 0.17 R 1.67 Ac
44 Pygmephoridae 0.003 R 0.40 Ac
45 Raphignathidae 0.02 R 1.41 Ac 0.02 R 1.19 Ac 0.23 R 1.05 Ac 0.17 R 1.67 Ac
46 Storchia robustus 0.05 R 0.94 Ac 0.01 R 0.40 Ac 0.17 R 0.63 Ac
47 Tarsonemus granarius 0.43 R 1.41 Ac 0.51 R 3.57 Ac 1.30 R 2.51 Ac 0.07 R 1.43 Ac 0.17 R 1.67 Ac
48 Tenuipalpidae 0.01 R 0.47 Ac
49 Tetranychidae 0.04 R 3.76 Ac 0.04 R 2.78 Ac 0.23 R 0.84 Ac 0.22 R 2.86 Ac 0.50 R 1.67 Ac
50 Tydeus kochi 0.28 R 1.41 Ac 0.06 R 1.98 Ac 0.87 R 1.05 Ac 0.50 R 1.43 Ac 0.83 R 3.33 Ac
51 Tydeus sp. 0.32 R 3.29 Ac 0.25 R 4.76 Ac 0.93 R 1.05 Ac 6.76 In 4.29 Ac 0.33 R 1.67 Ac
III. Mesostigmata
52 Neoseiulus barkeri 0.01 R 0.47 Ac 0.06 R 0.63 Ac 0.17 R 1.67 Ac
53 Ameroseiidae 0.57 R 1.43 Ac
54 Androlaelaps casalis casalis 0.03 R 0.40 Ac 0.08 R 0.42 Ac
55 Blattisocius keegani 0.18 R 4.70 Ac 0.16 R 3.97 Ac 1.59 R 2.72 Ac 0.29 R 1.43 Ac 18.41 D 10.00 Ac
56 Blattisocius mali 0.25 R 1.88 Ac 0.17 R 0.63 Ac
57 Blattisocius tarsalis 0.70 R 3.29 Ac 0.08 R 1.59 Ac 0.89 R 2.51 Ac 0.5 R 2.86 Ac
Exp Appl Acarol (2008) 44:213–226 219
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Table 1 continued
Dominance: a given taxon is classiWed as dominant (D), inXuent (In) or recedent (R) if it constitutes >10, 5–10 or <5% of the total number of individuals, respectively.
Frequency: a taxon is classiWed as constant (C), accessory (A) or accidental (Ac) if it occurs in >50, 25–50 or <25% of the total number of samples, respectively. Storage facility
types: ACUs, agricultural cooperative unions; COMMs, commercial stores; FARMs, farm stores; MILLs, Xour mills; SILOs, grain silos
ID Taxa ACUs COMMs FARMs MILLs SILOs
Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq. Dom. Freq.
58 Gamasellodes sp. 0.01 R 0.47 Ac 0.06 R 0.21 Ac 0.07 R 1.43 Ac
59 Kleemannia plumigera 0.03 R 0.94 Ac 0.17 R 0.42 Ac
60 Kleemannia plumosus 0.04 R 1.19 Ac 0.54 R 1.67 Ac
61 Laelapidae 0.14 R 0.21 Ac
62 Parasitidae 0.01 R 0.40 Ac 0.25 R 0.63 Ac
63 Uropodina 0.22 R 2.35 Ac 0.08 R 1.59 Ac 0.44 R 1.05 Ac
IV. Cryptostigmata
64 Haplochthonius sp. 0.04 R 4.70 Ac 0.1 R 0.40 Ac 0.85 R 0.42 Ac
65 Paleosomata 0.93 R 0.63 Ac
220 Exp Appl Acarol (2008) 44:213–226
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Carpoglyphus lactis (L.), Anoetidae and Tenuipalpidae. Carpoglyphus lactis was found
almost exclusively on edible products containing sugar, like dried Wgs and dried raisins
(Fig. 2).
Farm stores (FARMs)
Fifty-one percent of the samples contained mites. In the ‘residue’ group 31.2% of the sam-
ples were classiWed into the 1–10 mites/10 g d.w. category, whereas in the ‘Xour’ group
2.6% were classiWed into the 11–25 mites/10 g d.w. category (Table 2, Fig. 1).
Fifty-six mite taxa were identiWed (Table 1). Tyrophagus putrescentiae and L. destruc-
tor were dominant and accidental, A. siro was inXuent and accidental. Acarus gracilis and
Ctenoglyphidae were recorded only in FARMs.
Commercial stores (COMs)
Fifty-eight percent of the samples contained mites. In the ‘residue’ group 19.7% of samples
contained mites, with 1–10 mites/10 g d.w., whereas in the ‘edible’ group 14.8% contained
51–250 mites/10 g d.w. (Table 2, Fig. 1).
Forty-four taxa were identiWed (Table 1). Acarus siro, L. destructor and Chortoglyphus
arcuatus (Troupeau) were dominant and accidental, T. putrescentiae was inXuent and acci-
dental. Chelacheles sp. was recorded only in COMs.
Flour mills (MILLs)
Of the 70 samples collected 46% contained mites. The highest percentage of infestation
was recorded in residues (68.2). In the residues 23% of samples contained 1–10 mites/10 g
d.w., 9% contained 11–25 mites/10 g d.w. and 9% 26–50 mites/10 g d.w. Fewer infesta-
tions occurred in animal fodder and Xour (Table 2, Fig. 1), in which 26 taxa were recorded
Fig. 1 The average number of taxa (mean + SE) per store type per product. Products or store types marked
by the same letter do not diVer signiWcantly according to Fisher’s LSD test (= 0.05)
0
2
4
6
8
10
12
14
16
18
20
ACU stores
Number of taxa
Edible
Flours
Fodders
Others
Residues
(a) (a) (a) (a) (a)
(b, c)
(c)
(b)
(b, c)
(a)
SilosFlour millsFarm storesCommercial stores
Exp Appl Acarol (2008) 44:213–226 221
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(Table 1). Tyrophagus putrescentiae, L. destructor and A. siro were dominant and acciden-
tal, Gohieria fusca (Oudemans) and Tydeus sp. were inXuent and accidental.
Silos (SILOs)
Fifty-seven percent of samples contained mites. In the residues 40% of samples were
infested with 1–10 mites/10 g d.w. and 5% with 11–25 mites/10 g d.w. Fewer infestations
occurred in the other groups of samples (Table 2, Fig. 1).
Of the 20 taxa identiWed, L. destructor, A. siro and the predatory mites Cheyletus
malaccensis Oudemans and Blattisocius keegani Fox were dominant and accidental,
T. putrescentiae was found to be inXuent and accidental (Table 1).
RDA analysis
Permutation tests, with 999 permutations, on the Wrst canonical axis and on all axes of RDA
analysis were signiWcant (P= 0.004 and P= 0.006, respectively). However, the explained
variance was quite low (8.1%) suggesting highly structured data with rather uncorrelated
Table 2 Number of samples, percentage of infestation and degree of infestation of the collected samples
AThe letters indicate the level of infestation (number of mites/10 g dry weight of sample): a = <1; b = 1–10;
c = 11–25; d = 26–50; e = 51–100; f = 101–250; g = 251–500; h = 501–1,000; i = 1,001–2,000 and
j
= >2,000. In parentheses the percentage of total samples of each group infested with mites
Storage facility Group of stored
products
Number
of samples
Percentage
of infestation
Degree of infestationA
Agricultural
Cooperative
Unions
Animal fodder 71 56.3 a(46.5), b(7), d(2.8)
Flour and bran 13 61.5 a(30.8), b(15.4), c(7.7), d(7.7)
Edible products 34 70.6 a(52.9), b(14.7), c(2.9)
Residues 95 71.6 a(41), b(18.9), c(3.2), d(1), e(3.2),
f(1), g(1), h(1), i(1)
Total 213 65.3
Farm stores Animal fodder 295 44.1 a(29.8), b(12.2), c(1.7), e(0.3)
Flour and bran 78 48.7 a(29.5), b(16.7), c(2.6)
Various products 12 50.0 a(41.7), b(8.3)
Residues 93 75.3 a(44.1), b(31.2)
Total 478 51.0
Commercial stores Animal fodder 91 48.3 a(32.9), b(14.3), e(1.1)
Flour and bran 24 45.8 a(29.2), b(8.3), c(4.2), e(4.2)
Edible products 27 48.1 a(25.9), c(3.7), d(3.7), e(7.4), f(7.4)
Various products 39 61.5 a(46.1), b(5.1), c(2.6), d(2.6),
e(2.6), f(2.6)
Residues 71 77.5 a(39.4), b(19.7), c(7), d(4.2), e(1.4),
f(1.4), g(4.2)
Total 252 58.3
Flour mills Animal fodder 11 18.2 a(18.2)
Flour and bran 37 40.5 a(29.7), b(10.8)
Residues 22 68.2 a(27.3), b(22.7), c(9.1), d(9.1)
Total 70 45.7
Silos Animal fodder 30 56.7 a(46.6), b(10)
Flour and bran 4 50.0 a(50)
Edible products 6 66.7 a(66.7)
Residues 20 55.0 a(10), b(40), c(5)
Total 60 56.7
222 Exp Appl Acarol (2008) 44:213–226
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variables (taxa). The resulting diagram (Fig. 2) shows that the Wrst principal axis is positively
associated with Residues and ACUs stores and negatively associated with FLOURs and
SILOs, whereas the second axis is positively associated with COMs and negatively associate
with FARMs and ACUs stores. With scaling focused on the inter-sample distances, the dis-
tance between the centroids of store type and commodity classes approximates the Euclidean
distance (Lepn and Kmilauer 2003). In the Wgure it is seen that the distances between classes
of products are greater than the distances between store-type classes, indicating greater diVer-
ences in species compositions between products than between store types.
By projecting the environmental variables on the species arrows we can approximate the
average value of the species in the particular class of the (dummy) environmental variable.
For example (in parentheses the species ID; Table 1), C. lactis (8) and S. medanensis (17)
prefer edible products, whereas A. siro (3) is found more often in Commercial stores. Che-
lacheles sp. (28), Pygmephoridae (44), C. arcuatus (9), C. oudemansi (6) and Caloglyphus
sp. (7) have higher relative abundance in Commercial stores and other products. The taxa
projected on the lower right quarter of the plain, as well as those close to the right part of
the Wrst axis (e.g., C. trux Rohdendorf (34), L. destructor (14), T. putrescentiae (21),
A. docta Berlese (24), S. robustus (46), A. ovatus (4), A. immobilis (2), C. malaccensis (33)
and Bdellidae (26)) are expected to be more abundant in Residues’ samples and in ACUs.
Acaropsis sollers Kuzin (25), N. barkeri (52), Pyemotes sp. (43) and C. setirostris (Hermann)
Fig. 2 Species–environment biplot diagram from redundancy analysis (RDA), summarizing the association
among species (arrows) as well as between species and environmental variables (circles indicate classes o
f
products and squares indicate classes of storage facilities). The species ID is given in Table 1
Exp Appl Acarol (2008) 44:213–226 223
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(35) are expected to be more abundant in samples belonging to Silos, whereas A. gracilis
(1), Ctenoglyphidae (10), Neopronematulus sp. (40), Pseudocheyletidae (41), P. vegei
Andre (42), Laelapidae (61) and Paleosomata (65) are expected to be more abundant in
fodders and farms stores.
Discussion
Of the total number of samples (1,073), 55.5% contained mites, showing the extremely
high mite occurrence in all types of stored products. In a similar study, Franz et al. (1997)
studied 859 samples of stored products in Germany and reported 86.4% infestation. Pagliarini
(1979) found 73.3% infestation in 353 samples from Croatia. Cusack et al. (1975) noted a
75.3% infestation during a study on 766 samples from Ireland. Zdarkova (1967) recorded
68.6% infestation in 389 samples from former Czechoslovakia, whereas Chmielewski
(1971) reported 30% in 905 samples from Poland. Thind and Clarke (2001) studied 571
samples of cereal-based food products in UK and reported 21% of infestation. Comparing
the degree of infestation in the present survey with these values, the rate of mite infesta-
tions in stored products in Greece seems to be somewhat below the European average.
Perhaps this is due to Greece’s warm and dry climate, because these conditions are generally
suboptimal for the development of most mites.
The highest percentage of infestation was found in samples from stores of agricultural
cooperative unions. Although in the majority of these facilities fumigations were often
applied, the poorly conserved premises along with the lack of preventive hygiene measures,
before the storage of the products, may be considered as the main reasons for the high mite
presence. The lowest infestation rate was noticed in samples from Xour mills, probably due
to the more frequent fumigations or other insecticidal applications (e.g. structural treat-
ments), and the more intensive hygiene measures, compared with other storage facilities.
Still, the high mite numbers in the residues clearly indicate their importance as infestation
sources.
During the course of the survey 65 taxa of mites were collected, although identiWcation
to the species level was not always possible. In previous surveys Franz et al. (1997) in
Germany recorded 49 taxa, Long-shu and Qing-Hai (1997) in China 79 taxa, Mahmood
(1992) in Iraq 16 taxa, Corpuz-Raros et al. (1988) in Philippines 65 taxa, Saleh et al. (1985)
in Egypt 33 taxa, Pagliarini (1979) in Croatia 23 taxa, Cusack et al. (1975) in Ireland 70
taxa, Zdarkova (1967, 1998) in former Czechoslovakia 41 and 32 taxa, respectively, and
O’Farrell and Butler (1948) in Northern Ireland recorded 62 taxa. In Greece, in earlier
surveys of a more limited geographical extent, Emmanouel et al. (1994) recorded 17 taxa,
Palyvos et al. (2002) 37 taxa, and Papaioannou-Souliotis (1991) found 28 taxa of mites in
house dust. Eliopoulos and Papadoulis (2001) reported Wve new records of cheyletid mites
from stored products.
The highest number of taxa was found in samples from farm stores, but most FARMs
samples had low infestation levels. These Wndings are consistent with those of Emmanouel
et al. (1994), where most taxa had been found in the farm stores too. The highest degree of
infestation was noticed in samples from stores of agricultural cooperative unions and com-
mercial stores, where most products are stored in sacks. According to O’Farrell and Butler
(1948) and Cusack et al. (1975), bagged stored products present a larger surface area and
permit a greater increases in moisture content, consequently they allow faster mite develop-
ment. In a grain column, aeration and other climatic conditions are suitable for mites only
224 Exp Appl Acarol (2008) 44:213–226
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in the highest zone of the bulk, and thus in such stored-grains more mites occur at the upper
layer than at deeper layers (Athanassiou et al. 2003; Palyvos and Emmanouel 2006).
The highest percentages and the highest degrees of infestation were found in residue-
type materials. These samples usually contained residues of products mixed with dust, col-
lected from the Xoors and the corners of stores. The residues are usually in contact with the
ground, and therefore have a higher moisture content than the samples from other parts of
the stores, providing improved conditions for mite growth (Sinha 1979). Infested residues
are an important source of mites for adjacent stored products. This is consistent with earlier
Wndings of mites in residues (Cusack et al. 1975; Pagliarini 1979; Emmanouel et al. 1994;
Zdarkova 1998; Palyvos et al. 2002).
Astigmatid mites were the most numerous in the current study, with 22 taxa found.
Lepidoglyphus destructor (Glycyphagidae) was dominant in all Wve types of storage facilities
and it was accessory in the stores of agricultural cooperative unions. Many researchers
believe that this species can develop high densities, similar to A. siro, although the former
is of less economic importance (O’Farrell and Butler 1948; Cusack et al. 1975). Lepidogly-
phus destructor seems to be quite noticeable and common in Greek stores, according to
previous studies (Emmanouel et al. 1994; Palyvos et al. 2002). Gohieria fusca of the same
family was inXuent only in Xour mills.
Tyrophagus putrescentiae was recorded either as dominant or as inXuent in each type of
storage facility examined, whilst it was both dominant and accessory in stores of agricul-
tural cooperative unions. This species is found in an extremely large variety of commodi-
ties with high fat and protein contents (Hughes 1976). In Spain it is considered to be an
important pest of dry-cured ham where it feeds on the surface layer (Arnau and Guerrero
1994; Garcia 2004). This species can develop at higher temperatures than other stored-
product astigmatids (Sinha and Watters 1985; Sinha 1991) and it is very common in Greek
storage facilities (Emmanouel et al. 1994; Palyvos et al. 2002).
Acarus siro was found in three out of Wve types of storage facilities as dominant, and
only in one as inXuent. It is a major pest of stored grains in the temperate regions of the
world (Hughes 1976). Its occurrence is considerable in Greece as well, but at a lower level
in comparison with other central and northern European countries. This may be attributed
to the warm and dry Greek climate that negatively aVects its development (Emmanouel
et al. 1994). In the present study this species developed population densities of over 200
mites per 10 g of dry sample weight, especially in stored cheese in cooling rooms.
Aleuroglyphus ovatus (Acaridae) was inXuent in the stores of agricultural cooperative
unions. Exposure to this mite may cause allergy, especially important for workers in the
grain industry (Geary et al. 2000).
Twenty-nine prostigmatid taxa were found, mostly belonging to the Cheyletidae (10
taxa) and Tydeidae. Cheyletus malaccensis was the most common cheyletid, accounting for
75.4% of all individuals of the Cheyletidae. In fact, this species was recovered from all cat-
egories of storage facilities, being dominant in silos and inXuent in stores of agricultural
cooperative unions. This species feeds not only on pest mites but also on insect eggs (Rizk
et al. 1979; Yousef et al. 1982) and it is associated with both grain mass and grain residues
(Hubert et al. 2006). In the present study C. eruditus, common in central and northern
Europe (Hubert et al. 2006; Lukas et al. 2007), was found in much lower numbers.
Twelve Mesostigmata taxa were found, of which Blattisocius keegani (Ascidae) was
present in all Wve storage types and dominant in the silos. Only two Cryptostigmata taxa
were found, whose occurrence was considered recedent and accidental.
Summarizing, one of the most signiWcant Wndings of this survey was the relatively high
percentage of infestation of a wide range of stored products, despite the relatively dry and
Exp Appl Acarol (2008) 44:213–226 225
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warm Greek climate. Many mite species were found. The survey emphasizes the impor-
tance of mites in stored products, information that may aid in understanding and preventing
economic losses caused by mite contamination of stored agricultural products.
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