CC BY
165Russian Journal of Nematology, 2019, 27 (2), 107 - 121
Distribution and occurrence of plant-parasitic nematodes associated with raspberry (Rubus idaeus) in Souss-Massa region of Morocco: relationship with soil physico-chemical factors
Fouad Mokrini1, Salah-Eddine Laasli1, 2, Driss Iraqui1, Ahmed Wifaya1, Abdelaziz Mimouni1, Gul Erginbas-Orakci3, Mustafa Imren4 and Abdelfattah A. Dababat3
biotechnology unit, Regional Central of Agricultural Research, National Institute of agriculture Research (INRA), Rabat, Morocco 2Faculty of Science, Mohammed V University, Laboratory of Botany, Mycology and Environment, Rabat, Morocco 3International Maize and Wheat Improvement Centre (CIMMYT), Emek, Ankara, Turkey ^Department of Plant Protection, Faculty of Agriculture and Natural Science, Bolu Abant Izzet Baysal University, Bolu, Turkey
email: [email protected]
Accepted for publication 2 August 2019
Summary. Raspberry (Rubus idaeus) polytunnels in Morocco's Souss-Massa region were surveyed between February and April 2018. The study was aimed to investigate the diversity and incidence of plant-parasitic nematodes affecting raspberry crop and to assess the effects of soil physico-chemical properties on the nematodes. Twelve nematode genera were identified form the soil and root samples collected from 41 raspberry polytunnels across the three provinces (Belfaa, Biougra and Khmis Ait Aimra). The most common plant-parasitic nematodes (PPN) were Pratylenchus spp., Meloidogyne spp. and Helicotylenchus spp. In terms of their abundance and frequency, four PPN (Pratylenchus spp., Meloidogyne spp., Helicotylenchus spp. and Tylenchus spp.) were abundant and frequent throughout the region. Several genera of nematodes were significantly associated with soil texture, organic matter and pH, which indicate that soil properties play an important role in PPN communities. This description of PPN assemblages associated with red raspberry polytunnels in Souss-Massa region provides a starting point from which further studies will be implemented for the other regions of Morocco cultivating raspberries, and to develop efficient management strategies.
Key words: Helicotylenchus, management, Meloidogyne, nematode survey, Pratylenchus, soil characteristics, Tylenchus.
Red raspberry (Rubus idaeus L.) is cultivated more or less intensively in different countries of the world such as Russia, USA, Poland, Mexico, Morocco and Serbia (McGregor, 1976; Jennings, 1988; Trager, 1995; Hummer, 2010). The total world production of raspberries is estimated to be 812.735 t year1 (FAO, 2017), with Russia supplying 18% (146.377 t). Other major producers were Mexico (14.8%), Serbia (13.5%), the USA (13.0%) and Poland (12.8%). In Morocco, the main red raspberry production areas are the Loukkos and Souss-Massa regions, which cover approximately more than 2000 ha and produce 319 t year-1 (MAPM, 2017). During recent years, interest is increasing in red raspberry cultivation as an alternative cash crop for big farms in Souss-Massa region of Morocco.
Raspberry production decreased drastically due to biotic and abiotic factors. Among the biotic stresses, plant-parasitic nematodes (PPN) play an important role in decreasing crop yield (Gigot et al., 2013). Several PPN were associated with red raspberry disease throughout the world (McElroy, 1972, 1977; Tsolova & Koleva, 2015; Kroese et al., 2016), including Pratylenchus spp., Helicotylenchus spp., Tylenchorhynchus spp., Criconemoides xenoplax and Ditylenchus dipsaci (Coev et al., 1971; Kroese et al., 2016; Pinkerton et al., 2008; Poiras et al., 2014). Species of dagger nematodes (Xiphinema bakeri, X. diversicaudatum and X. americanum) and needle nematodes (Longidorus elegantus, L. macrosoma and L. attenuatus) are ectoparasitic nematodes significantly associated with this crop since they
© Russian Society of Nematologists, 2019; doi:10.24411/0869-6918-2019-10011
transmit some devastating viruses such as Raspberry ringspot virus (RRSV) and Strawberry latent ringspot (McElroy, 1972). Due to the intensive and continuous cultivation system, soil borne diseases, especially nematodes, become an important constraint in red raspberry production.
In Morocco, red raspberry is cultivated in the South of the country, which is characterised by a wide diversity of soil types (silty clay and clay loam) and climates (arid and semi-arid). Several reports highlighted the diversity, distribution and density of PPN on various crops in Morocco (Mokrini et al., 2009, 2016; Janati et al., 2018) but there is currently no literature available on the occurrence and distribution of PPN associated with raspberry and their relationship with soil physico-chemical properties in Morocco. In order to guide further research, we present an extensive overview on the incidence of PPN associated with raspberry in Souss-Massa region of Morocco. This study aimed: i) to study which PPN taxa are associated with raspberry in Souss-Massa region; ii) to determine PPN occurrence and abundance in Southern Morocco raspberry growing region; and iii) to investigate the effect of soil physico-chemical properties on PPN community structure.
MATERIAL AND METHODS
Nematode survey. An intensive survey was conducted between February and April 2018 to determine the occurrence and distribution of PPN in raspberry in polytunnels located in Khmis Ait Amira (30°10'36.546'' N, -9°29'20.901'' E), Biogra (30°12'52" N, 9°22'15" O) and Belfaa (29°58'55.344'' N, -9°30'19.476'' E) provinces of Souss-Massa region, Morocco (Fig. 1). The number of polytunnels sampled per province was determined as a function of the importance (surface planted) of the raspberry crop. A total of 41 representative polytunnels were visited and sampled (Fig. 1), representing three provinces of the raspberry production area. In each province, eight to thirteen raspberry polytunnels were randomly selected for sampling. From each polytunnel, 10 subsamples were arbitrarily collected then mixed thoroughly to form a representative sample of 2 kg soil. Samples were kept in plastic bags and stored at 4°C before analysis to minimise changes in nematode populations (Berker et al., 1969). Analyses of soil texture and composition from each surveyed polytunnel were carried out at the Regional Centre of Agricultural Research (INRA) in Agadir, Morocco, and are summarised in Table 1.
Nematode extraction and identification.
Representative samples from each surveyed polytunnel were carefully mixed and processed for extraction no later than 48 h after storage. For each sample, nematodes were extracted separately from roots and soil. Roots of each sample were gently washed in tap water to free adhered soil particles, chopped into pieces (ca 0.5 cm) and then nematodes were extracted from a sub-sample of 20 g using a modified Baermann technique (Hooper, 1986). Nematodes were also extracted from 100 cm3 of soil using the same modified Baermann technique used for extraction of nematodes from roots. After 48 h, nematode suspensions from both soil and roots were collected in beakers, allowed to settle for 2 h and concentrated to about 20 ml by removing excess water (supernatant) using the settling-siphon method (Caveness, 1975). Nematodes were identified to genus level using dichotomous keys (Mai & Lyon, 1975; Mai & Mullin, 1996). The Seinhorst (1959) method as modified by De Grisse (1969) was used to kill and fix the nematodes by adding 4% hot (60-80°C) formaldehyde to a small drop of water in a glass cavity vessel that contained the nematodes. The nematodes were transferred to solution I (99 parts 4% formaldehyde + 1-part pure glycerin) in a square 7 cm diam. watch glass. This square watch glass dish was placed in a desiccator containing about one-tenth of its volume of 96% ethanol. The next day, the watch glass containing the nematodes was removed from the desiccator and placed in an incubator at 37°C. Then 3 ml of solution II (95 parts 96% ethanol + 5 parts pure glycerin) was added to the watch glass. This was repeated three times at intervals of 3 h, while the watch glass was partially covered by a glass slide to allow evaporation. Finally, 2 ml of solution III (50 parts 96% ethanol + 50 parts pure glycerin) was added and the watch glass was left overnight at 37°C in the incubator. The nematodes in pure glycerin from each sample were mounted on glass slides for identification to species level under a light microscope. Species of root-lesion nematodes were identified using the keys of Castillo & Vovlas (2007) and Ryss (1988).
Assessment of nematode population densities.
Nematode diversity and incidence were assessed by calculating the prevalence, mean abundance and maximum density (Boag, 1993). Prevalence was defined as the number of samples having a particular nematode species, divided by the total number of samples examined, expressed as a percentage. Mean abundance was defined as the number of individuals of a particular nematode species per 100 cm3 soil in the positive samples, divided by the number of positive samples, and maximum density was defined
determined as the maximum number of individuals of a particular nematode species per 100 cm3 soil recovered from a sample.
Physico-chemical analyses of soil. The soil analyses were carried out at the INRA soil laboratory in Agadir, using standard methods (Anderson & Ingram, 1993). The following soil properties were analysed including soil texture: proportions of clay (0-2 ^m), silt (2-50 ^m) and sand (50 to > 2-00 ^m); pH and electrical conductivity EC (^S cm-1) using 1:2.5 soil: water ratio methodology described by Richards (1954); exchangeable cations: potassium, manganese and magnesium; exchangeable acidity; total soil organic matter; nitrogen content; soil solution including iron, copper, zinc, sodium, and phosphorus.
Diversity of plant-parasitic nematodes. The
taxon dominance parameter was calculated for each nematode genus in prospected localities together with the frequency. This parameter represents the regression between abundance and frequency for each sampling genera (Fortuner & Merny, 1973). The distribution diagram of nematodes communities was applied as abundance variables were transformed to log10 (X + 1) before analysis.
Statistical analysis. Principal component analyses (PCA) were applied to explore PPN community patterns and physico-chemical soil factor patterns in relation to the surveyed localities. After data normalisation using the Shapiro-Wilk normality test (Shapiro & Wilk, 1965), PPN and soil variables associated with the principal component analyses were subjected to a one-way ANOVA performed using XLSTAT 2016.02.28451 software (Addinsoft,
USA). Significant differences among variables were tested by the protected least significant difference (LSD) at probability level (P < 0.001). An advanced Heat map analysis was used to investigate relationships between PPN and soil physico-chemical properties using R package.
RESULTS
Density and diversity of PPN associated with raspberry. PPN were detected in all polytunnels surveyed in Biougra, Khmis Ait Amira and Belfaa provinces. Twelve genera were morphologically identified from the 41 soil samples collected from the representative polytunnels (Table 2). Biougra possessed 12 genera, Khmis Ait Amira 11 genera, Belfaa possessed 9 genera, while 8 genera were common to the three regions (Table 2). Data concerning their prevalence, mean abundance and maximum density of nematodes in each province surveyed are presented in Table 2. Among the most prevalent nematodes on raspberry in Biougra province were Meloidogyne spp. (65%), Pratylenchus spp. (60%), and Tylenchus spp. (55%). In Khmis Ait Aimera province, the most prevalent genera were Helicotylenchus spp. (84.6%), Pratylenchus spp. (53.8%), and Tylenchus spp. (54%). For Belfaa province, Helicotylenchus spp. (75%), Meloidogyne spp. (62.5%), and Pratylenchus spp. (62%), were the most prevalent genera. The following species were identified from the randomly selected specimens: Pratylenchus penetrans, P. thornei, Meloidogyne incognita, M. javanica and Ditylenchus dipsaci. The density of PPN associated
Fig. 1. Map of the agro-ecological locations in Souss-Massa region of Morocco where samples were collected from raspberry polytunnels.
Table 1. Major ecological characteristics of the surveyed eco-regions of red raspberry.
Locality (Province) Altitude (m a.s.l.) Soil texture Temperature (◦C) Rainfall (m /year) Samples per site Letter code
Biougra 133 Sandy clay loam 19.3 214 20 BIO
Khmis Ait Amira 97 Sandy clay loam 24.1 212 13 KAM
Belfaa 137 Sandy loam 20.0 250 8 BEL
Table 2. Prevalence, mean, and maximum density of plant-parasitic nematodes from soil (100 cm3) sampled from red
raspberry polytunnels in Souss-Massa region of Morocco.
Biougra Khmis Ait Amira Belfaa
Nematodes Prevalence Mean Max Prevalence Mean Max Prevalence Mean Max
(%) abundance density (%) abundance density (%) abundance density
Meloidogyne spp. M. javanica 65 4 16 38 2 12 62.5 3 12
M. incognita Pratylenchus spp.
P. penetrans 60 3 15 53.8 4 23 62 2 7
P. thornei
Ditylenchus spp. 30 1 6 15.3 1 4 50 1 2
Helicotylenchus spp. 50 2 11 84.6 2 7 75 2 5
Paratylenchus spp. 35 1 8 46.1 1 7 12.5 1 2
Tylenchus spp. 55 2 9 54 4 30 50 1 3
Tylenchorhynchus spp. 45 2 8 23 1 8 0 0 0
Longidorus spp. 5 1 1 7 3 0 0 0
Xiphinema spp. 20 1 5 0 0 0 37.5 2 7
Rotylenchus spp. 10 1 3 23 1 3 0 0 0
Criconemoides spp. 20 1 3 23 1 4 37.5 1 3
Trichodorus spp. 10 1 3 15.3 1 2 25 1 2
with red raspberry differed between the sampled regions. The total PPN densities were generally higher in Khmis Ait Amira province (45 PPN (100 cm3 soil)1). The lowest density were found in Biougra (4 PPN (100 cm3 soil)1) followed by Belfaa province (5 PPN (100 cm3 soil)1) (Table 3). The genera with the highest mean abundance and maximum densities wereMeloidogyne spp. (4 and 16 in Biougra, respectively; 3 and 12 in Belfaa), Pratylenchus spp. (4 and 23 in Khmis Ait Amira; 3 and 15 in Biougra; 2 and 7 in Belfaa), Tylenchus spp. (4 and 30 in Khmis Ait Amira), and Xiphinema spp. (2 and 7 in Belfaa) (Table 2).
Community patterns of plant associated nematodes. PCA analysis of the nematode genera distribution across total localities of the surveyed red raspberry fields showed that the fraction of variance accounted for by the first two PC axes is 19.24% and 16.72% (eigenvalues), respectively (Fig. 2A). The PC1 axis is related to Meloidogyne, Longidorus, Ditylenchus and Tylenchus species (positive PC values), and to Pratylenchus and Rotylenchus species (negative PC values). The PC2 axis is related to Helicotylenchus, Paratylenchus, Tylenchorhynchus and Trichodorus species (positive PC values), and to Pratylenchus and Rotylenchus species (negative PC
values). The projection of the sample eigenvalues on the PC axes indicated that Pratylenchus spp., Helicotylenchus spp., Paratylenchus spp., and Tylenchus spp. were significantly abundant in Ait Amira region. Meloidogyne spp. and Tylenchorhynchus spp. were also more abundant in Biougra region. The Belfaa region had just two genera, Meloidogyne and Helicotylenchus, with moderate presence (Fig. 2B).
Physico-chemical soil patterns and their relationship between red raspberry nematodes communities. After soil assessment (Table 5), PCA analysis of the soil characteristics across total localities of the surveyed red raspberry polytunnels showed that the fraction of variance accounted for the first two PC axes is 30.36% and 23.05% (eigenvalues), respectively. The loading plot of the soil factors (Fig. 3A) indicated that the PC1 axis was related to sand (San), limestone (Cal), humic organic matter (HOM), electrical conductivity (EC) and mineral content (especially Na, K, Mg, N, P, Ca and Zn). Meanwhile, the PC2 axis was related to silt (Sil), clay (Cla), soil pH and to mineral content such as (Cu, Mn and Fe). The Bi-plot of soil factors in interaction with sampling regions indicated an important differentiation between all surveyed localities
Fig. 2. Plant-associated nematode community patterns in all surveyed red raspberry fields. A: PCA loading plot for the nematode genera identified. B: Mean value of the discriminant nematode variables according to the PCA analysis. Letters represent homogeneous groups based on protected least significant difference test (LSD) for each variable at (P < 0.001). Error lines on the bars represent the standard error. Provinces and genus codes are given in Tables 1 and 4.
in terms of soil patterns (Fig. 3B). The Belfaa province was shown to be significantly associated
with six soil characteristics, including electrical
conductivity (EC), organic matter: humic (HOM) and total (TOM), and some mineral content such as zinc (Zn) and nitrogen (N). By contrast, the Biougra province was strongly associated with sand content (San) of soil together with some minerals (Mg, K and Na). The remaining province Khmis Ait Amira was especially associated with clay (Cla) and silt (Sil) content of soil and to its pH parameter. As several nematodes persisted with red raspberry crop in the sampled polytunnels, it is natural for them to have an affiliation with the physico-chemical characteristics of soil. For this reason, an advanced heat map analysis was conducted to determine if this interaction exists (Fig. 3C). The analysis clearly
indicated that the majority of nematodes genera identified were positively correlated with soil texture (sand, clay or silt content); Helicotylenchus, Rotylenchus, Longidorus and Criconemoides genera were associated with clay content (Cla), whereas, Paratylenchus and Xiphinema were most likely associated with sandy soils. Except for the last two, all genera were moderately attracted to silt content. Concerning mineral characteristics, a few (Mn, Ca, Cu and Zn) were shown to have good association with some nematode genera such as Criconemoides, Meloidogyne and Ditylenchus while the others (K, N, Na, P and Mg) are not associated with those genera. Electrical conductivity, pH and total organic matter (TOM) had an impact on nematodes communities as they had a strong correlation with the majority of genera.
Fig. 3. Physico-chemical soil characteristics in all the surveyed provinces of red raspberry. A: PCA loading plot for the soil characteristics. B: Bi-plot of soil characteristics in interaction with the regions prospected. C: Advanced Heatmap of population structure of nematodes genera in red raspberry fields in different regions surveyed. Ward's clustering algorithm was applied to the Spearman dissimilarity matrix of nematode distribution in red raspberry fields in interaction with physico-chemical soil characteristics. Upper dendrogram represents soil patterns. Left dendrogram represents the nematode genera. The color key scale represents normalised nematode abundance (per 100 cm3 of soil). Provinces, soil and genus codes are given in Tables 1 and 4.
Diversity of plant associated nematodes communities of red raspberry. The diversity of nematodes on red raspberry from the surveyed fields was described in term of abundance and frequency of those pests (Fig. 4). Among 12 genera identified, Helicotylenchus, Pratylenchus, Meloidogyne and
Tylenchus were more abundant and frequent, while Paratylenchus, Tylenchorhynchus, Ditylenchus, Criconemoides and Xiphinema were shown to have a moderate abundance and frequency. Trichodorus, Rotylenchus and Longidorus had the lowest diversity.
Fig. 4. Distribution diagram (Abundance-Frequency) of nematode communities in red raspberry fields from all surveyed provinces. Genus codes are given in Table 4.
DISCUSSION
This study is the first to demonstrate the widespread occurrence, distribution and frequency of PPN in raspberry polytunnels in Morocco. The results indicated that 12 genera of both endoparasitic and ectoparasitic plant nematodes were identified in raspberry polytunnels in Souss-Massa region. Several studies reported that PPN are major pests of raspberry reducing yield and cane growth, and leading to economic losses in eastern Scotland and Canada, respectively (Trudgill, 1986; Belair, 1991). From all genera identified, species of Meloidogyne and Pratylenchus are known to be among the top PPN for scientific and economic importance (Jones et al., 2013). Other nematode genera reported in this study have been previously observed on raspberry fields from several regions of the world (Belair & Khanizadeh, 1994; Zasada et al, 2015; Mohamedova & Samaliev, 2018). Belair & Khanizadeh (1994)
identified six genera in raspberry fields from seven agricultural regions of the Quebec province and they concluded that the most commonly encountered nematode genus was Pratylenchus, with 46% occurrence. Poiras et al. (2014) reported 27 nematode species belonging to 19 genera associated with raspberry in Moldova. Similarly, Romanenko et al. (2014) described nine PPN genera in the rhizosphere of raspberries growing in Moscow region of Russia. The root-lesion nematode Pratylenchus spp. was one of the dominant nematode genera among PPN, found in 60, 53.8 and 62% of samples collected from Biougra, Khmis Ait Amira, Belfaa provinces, respectively. This widespread distribution of Pratylenchus spp. in all surveyed polytunnels is consistent with results from earlier surveys of cereal and saffron fields in Morocco (Mokrini et al., 2016, 2019). The impact of this genus on raspberry cultivation needs further study. Two species of Pratylenchus, viz. P. penetrans and P. thornei, were
Table 3. Densities of plant-parasitic nematodes associated with red raspberry in each polytunnel surveyed representing
three provinces of Souss-Massa region.
Plant-parasitic nematodes (PPN)
(numbers per 100 cm3 of soil)
Provinces Polytunnels surveyed Meloidogyne spp. Pratylenchus spp. Ditylenchus spp. Helicotylenchus spp. Paratylenchus spp. Tylenchus spp. Tylenchorhynchus spp. Longidorus spp. Xiphinema spp. Rotylenchus spp. Criconemoides spp. Trichodorus spp. Total
P1 0 0 0 4 0 2 0 0 0 0 0 0 6
P2 0 0 0 2 6 0 0 0 0 0 0 0 8
P3 0 0 0 1 2 0 0 0 0 0 0 0 3
03 P4 0 0 0 3 1 0 0 0 0 0 0 1 5
- a P5 5 0 0 4 3 3 0 0 0 0 0 0 15
P6 4 0 1 2 0 2 0 0 0 0 0 0 9
P7 6 2 0 7 0 30 0 0 0 0 0 45
'3 P8 0 4 0 2 3 9 2 0 0 3 2 0 25
s P9 5 17 0 2 0 1 0 0 0 0 0 2 27
P10 12 23 0 0 0 0 0 0 0 2 0 0 37
P11 0 2 4 1 7 2 2 3 0 1 1 1 24
P12 0 7 0 5 0 0 8 0 0 0 0 0 20
P13 0 1 0 0 0 0 0 0 0 0 4 0 5
P14 4 3 0 0 0 0 0 0 0 0 0 0 7
P15 2 2 0 0 2 1 0 0 0 0 0 0 7
P16 0 0 0 11 0 0 0 0 5 0 3 0 19
P17 0 0 0 0 0 8 0 0 0 0 0 0 8
P18 2 0 0 0 0 2 0 0 0 0 0 0 4
P19 1 0 0 9 0 3 6 0 0 0 0 0 19
P20 0 0 0 5 7 0 4 0 0 0 2 0 18
P21 5 7 0 2 0 0 0 0 0 0 0 2 16
03 P22 0 12 2 0 0 0 3 4 3 0 0 0 24
r M ^ P23 16 15 0 2 3 0 3 0 0 1 0 0 40
o CO P24 4 0 3 0 0 0 8 0 0 0 0 0 15
P25 12 2 0 1 0 6 0 0 1 0 0 0 22
P26 6 0 3 1 2 9 1 0 0 0 3 0 25
P27 0 3 2 5 0 2 0 0 0 0 0 0 12
P28 0 3 0 0 0 0 4 0 0 3 0 0 10
P29 2 8 0 9 1 1 0 0 0 0 0 3 24
P30 1 7 1 7 8 2 8 0 0 0 0 0 34
P31 11 3 6 0 0 7 0 1 2 0 1 0 31
P32 6 9 0 0 2 0 0 0 0 0 0 0 17
P33 0 3 0 0 0 1 1 0 0 0 0 0 5
P34 0 2 0 3 0 2 0 0 1 0 0 0 8
P35 3 7 0 2 0 1 0 0 0 0 1 0 14
P36 2 0 2 2 0 1 0 0 5 0 0 1 13
.8 it- P37 0 0 2 5 0 0 0 0 0 0 2 0 9
's CO P38 7 0 1 1 0 0 0 0 0 0 0 2 11
P39 12 1 0 2 0 0 0 0 0 0 0 0 15
P40 1 3 0 0 2 3 0 0 7 0 3 0 19
P41 0 3 2 0 0 0 0 0 0 0 0 0 5
Table 4. Physico-chemical soil characteristics and plant-parasitic nematode genera analysed in the PCA and heatmap
analyses, and their corresponding codes.
Soil characteristics Code Nematode genera Code
Granulometry
Clay Cla
Sand San Criconemoides CRI
Silt Sil Ditylenchus DIT
Organic matter OM
Total organic matter TOM Helicotylenchus HEL
Humic organic matter Nitrogen HOM N Longidorus LONG
pH H2O pH Meloidogyne MEL
Limestone Lim Paratylenchus PAR
Soil solution
Calcium CAL Pratylenchus PRA
Phosphorus Iron P Fe Rotylenchus ROT
Magnesium Mg Trichodorus TRI
Manganese Potassium Mn K Tylenchus TYE
Sodium Na Tylenchorhynchus TYL
Zinc Zn Xiphinema
Copper Cu XIP
Electrical Conductivity EC
detected in all surveyed provinces. Several studies have reported the presence of Pratylenchus spp. in the raspberry rhizosphere (Romanenko et al., 2014; Zasada et al., 2015). In the USA, according to McElroy (1977) and Kroese et al. (2016), one of the most important factors limiting the raspberry production is the presence of P. penetrans. Similarly, Zasada & Walters (2016) and Zasada et al. (2015) reported the presence of P. penetrans in non-bearing raspberry fields in the Pacific Northwest region of North America. In our study, population densities of Pratylenchus spp. ranged from seven (Belfaa province) to 23 (Khmit Ait Amira province) per 100 cm3 of soil. Other species of this genus are known to parasitise raspberry, such as P. crenatus and P. scribneri (Mohamedova & Samaliev, 2018), and P. pratensis, P. sonvallatiae and P. neglectus (Tsolova & Koleva, 2015). The root-knot nematodes Meloidogyne, particularly M. javanica and M. incognita, were encountered in 65%, 38% and 62.5% of the polytunnels sampled in Biougra, Khmis Ait Amira and Belfaa provinces, respectively. In Morocco, both species were reported recently in several crops including saffron (Mokrini et al., 2019) and vegetables (Janati et al., 2018). Mohamedova & Samaliev (2018) and Belair & Khanizadeh (1994) reported both M. hapla and M. arenaria as most abundant species of genus Meloidogyne in the raspberry fields in Bulgaria and Quebec, respectively. In our study, the absence of both species M. hapla and M. arenaria is related to the warm climate that characterises the Souss-Massa
region of Morocco. Several studies reported that the northern root-knot nematode M. hapla occurs in cold region of crop production (Taylor et al., 1978; Wu et al., 2018). Nematode vectors of plant viruses belonging to genera Xiphinema and Longidorus have been considered as the most damaging PPN to raspberry (Poiras et al., 2014; Romanenko et al., 2014). In the current study, both Xiphinema spp. and Longidorus spp. were detected in low densities, which varied in different provinces surveyed between 1 and 7 nematodes (100 cm3 soil)-1.
In addition, this study highlighted the possible interaction between nematode communities and soil physico-chemical proprieties of soil where the red raspberry is cultivated in Souss-Massa region of Morocco. This interaction led to an understanding of the effect of edaphic proprieties on PPN distribution in raspberry growing localities and it is a crucial step in their control, since this relationship can be complex and is influenced by environmental factors (Nielsen et al., 2014). The advanced heat map analysis showed strong correlations between nematodes and soil characteristics. Such relationships were indicated in previous studies (Robinson et al., 1987; Zoon et al., 1993). Our findings indicated that several PPN (Helicotylenchus spp., Rotylenchus spp., Longidorus spp., Criconemoides spp., Paratylenchus spp. and Xiphinema spp.) were identified have a strong relationship with some soil granulometry (total organic matter, silt, clay and sand) content based on
Table 5. Physico-chemical analyses of each red raspberry polytunnel
Location Sand (% ï Silt (%) Clay (%) Total Organic Matter (%) Humic Organic Matter (%) N (%) CAL (%) P (%) Na (%) K (%) Mg (%) Ca (%) Fe (%) Mn (%) Cu (%) Zn (%) pH (H2o) EC (|is/cm)
1 59.21 38.89 1.9 7.56 1.81 0.14 21.11 0.3 0.248 0.556 0.953 1.916 0.8 4.6 0.7 1.4 7.5 1172
2 62.23 37.62 0.15 5.58 1.1 0.05 9.7 0.259 0.178 0.463 1.054 2.505 1.2 2.4 0.8 1.6 7.6 909
3 60.42 39.48 0.1 3.19 0.68 0.07 10.77 0.102 0.149 0.44 0.577 1.474 0.6 3.7 0.7 2 7.93 251
4 70.19 29.66 0.15 3.87 0.71 0.08 9.75 0.075 0.188 0.973 0.758 7.516 0.4 3 1.2 1.2 7.53 738
5 46.57 37.33 16.1 4.33 1.49 0.07 6.48 0.102 0.053 0.181 0.447 1.326 1 8.8 2.2 1.3 7.81 125
6 48.01 37.94 14.05 5.55 1.3 0.09 5.11 0.075 0.056 0.042 0.52 1.768 1.3 7.2 1.6 1.1 7.96 393
7 52.63 34.77 12.6 4.16 0.73 0.06 7.96 0.123 0.062 0.025 0.318 1.621 1.2 8.2 2.7 1.2 8.06 150
8 27.94 56.81 15.25 6.86 1.45 0.11 15.62 0.082 0.007 0.044 0.888 3.537 1 5.5 2.8 2.1 7.98 289
9 82.42 12.98 4.6 2.73 0.57 0.05 11.74 0.136 0.059 0.019 0.491 1.474 1.2 4.3 1.1 0.8 7.78 131
10 62.77 31.13 6.1 3.93 0.88 0.07 7.37 0.286 0.03 0.209 1.472 2.8 0.8 3.6 1.1 1.4 7.41 330
11 61.02 37.48 1.5 2.39 0.26 0.05 18.43 0.075 0.069 0.139 0.419 2.505 1.2 4.3 1.2 1.5 7.67 124
12 46.50 51.6 1.9 3.04 0.66 0.07 19.2 0.082 0.089 0.116 0.548 1.326 0.6 5.1 1.5 1.2 8.01 173
13 66.00 32.6 1.4 2.36 0.29 0.06 27.24 0.082 0.109 0.139 0.346 1.179 1.2 6 0.9 1.4 7.62 137
14 51.33 41.36 7.3 3.04 0.33 0.05 27.44 0.068 0.119 0.232 1.508 1.474 1 8.2 0.8 1.6 7.48 492
15 55.42 30.98 13.6 3.76 0.77 0.08 18.47 0.109 0.099 0.185 0.397 1.179 0.8 7.1 1.2 1.7 7.82 214
16 38.58 52.17 9.25 3.39 0.33 0.07 6.22 0.027 0.035 0.114 0.606 1.474 1.3 7.3 0.8 0.9 7.91 216
17 55.59 40.56 3.85 2.95 0.35 0.06 8.19 0.014 0.03 0.107 0.346 7.074 1.3 6.4 0.9 1.5 8.01 145
18 30.57 55.83 13.6 5.31 0.98 0.1 15 0.041 0.06 0.197 0.462 3.095 0.8 4.5 1.2 0.9 7.8 203
19 47.06 45.04 7.9 2.96 0.35 0.06 12.48 0.007 0.045 0.153 0.274 5.453 1.3 7.7 1.4 0.9 7.99 174
20 14.38 65.47 20.15 5.54 0.8 0.09 15.86 0.048 0.069 0.199 0.433 10.611 1.2 7.3 2 1.7 7.92 281
Table 5. (continued) Physico-chemical analyses of each red raspberry polytunnel surveyed.
21 36.11 52.49 11.4 3.75 0.26 0.04 26.61 0.02 0.056 0.167 0.404 1.326 1.3 4.2 1.5 0.9 7.95 114
22 75.45 16.4 8.15 3.59 0.75 0.06 10.05 0.034 0.048 0.158 0.296 1.768 1.2 4.8 1.8 1.2 7.71 173
23 90.62 5.63 3.75 2.11 0.29 0.02 14.18 0.075 0.056 0.211 0.274 1.032 2.1 5.6 2.4 0.9 7.94 164
24 43.93 52.27 3.8 5.07 0.93 0.08 9.73 0.048 0.06 0.218 0.397 1.179 1.5 8 1.8 1.1 7.93 146
25 66.42 33.53 0.05 3.97 0.89 0.09 9.65 0.164 0.119 0.371 0.996 1.326 0.2 3.8 0.8 1.2 7.45 863
26 83.09 16.81 0.1 2.33 0.13 0.05 9.4 0.136 0.169 0.533 0.52 1.326 1 2.5 0.5 2.5 7.97 319
27 63.14 36.71 0.15 3.9 0.77 0.1 10.38 0.075 0.149 0.301 0.852 7.958 1.2 4.6 1.6 1.3 7.47 266
28 72.24 27.51 0.25 2.69 0.56 0.05 42.7 0.17 0.109 0.209 0.505 7.074 1.5 3.4 0.7 1 7.49 467
29 83.77 16.18 0.05 2.16 0.38 0.07 6.8 0.15 0.119 0.209 1.364 5.158 1.5 3.4 0.9 0.7 7.43 366
30 62.77 31.13 6.1 3.93 0.88 0.07 7.37 0.286 0.03 0.209 1.472 2.8 0.8 3.6 1.1 1.4 7.41 330
31 62.00 34.6 2.4 3.36 0.31 0.05 28.24 0.072 0.106 0.132 0.34 1.18 1.4 5 0.7 1.5 7.52 135
32 52.34 42.33 8.31 4.08 0.32 0.06 25.44 0.069 0.12 0.237 1.504 1.47 1 8.3 0.8 1.7 7.47 482
33 52.42 32.98 14.6 2.76 0.7 0.08 17.47 0.106 0.098 0.176 0.387 1.18 0.9 8.1 1.5 1.6 7.95 224
34 48.53 53.17 8.24 4.39 0.31 0.07 6.41 0.029 0.045 0.115 0.806 1.475 1.5 7.4 0.9 0.6 7.97 213
35 72.66 32.14 5.12 3.86 0.82 0.09 7.3 0.291 0.041 0.309 1.622 2.5 0.7 4.6 2.1 2.4 7.61 432
36 62.01 36.48 1.4 3.33 0.25 0.06 17.43 0.065 0.079 0.134 0.422 2.605 1.2 5.3 1.3 1.3 7.7 134
37 45.50 52.6 1.91 3.06 0.56 0.07 18.2 0.083 0.09 0.115 0.54 1.325 0.7 7.1 1.5 1.4 8.15 178
38 55.60 42.56 2.85 3 0.36 0.06 9.19 0.015 0.031 0.108 0.335 8.072 1.5 5.4 1 1.5 6.01 155
39 32.54 45.83 14.6 7.31 0.95 0.13 15.2 0.061 0.05 0.196 0.46 4.075 0.7 6.5 1.3 0.9 8.82 210
40 46.05 45 8.9 2.92 0.34 0.07 13.45 0.085 0.055 0.154 0.276 6.451 1.3 7.8 1.6 0.7 7.79 178
41 34.38 66.47 22.15 5.56 0.89 0.09 13.86 0.068 0.089 0.2 0.485 8.611 1.2 7.5 2 1.6 7.95 285
their degree of abundance. Prot & Van Gundy (1981) found that sandy soils seem to be the favoured habitat for nematodes, such as Meloidogyne spp. and Pratylenchus spp., as it can enhance their mobility. The same result was observed by Prasad & Rao (1980) with Tylenchorhynchus spp. Our study also reported the correlation of these pests with soil mineral content (Cal, Cu, K, Mn and Zn). Many studies have demonstrated the strong relationship between soil minerals and nematode species distribution in bulbous crops (particularly Fe, K, and Mg) (Ardakani et al., 2014; Fiscus & Neher, 2002; Yavuzaslanoglu et al., 2012). Francl (1993) reported a positive relationship between the density of Heterodera glycines and the level of Mg. Moreover, Mateille et al. (2014) detected a strong correlation between soil minerals and nematode communities and concluded that nematodes such as Hemicycliophora spp., Longidorus spp., and Merlinius spp. colonise carbonated and mineralised soils and they are more commonly found in coarse textured soils under oligotrophic conditions. Gaidashova et al. (2009) observed that P. goodeyi population densities were significantly and positively correlated with soil K in banana eco-regions. Low pH can also enhance nematode abundance (Cadet et al., 1994; Korthals et al., 1996; Norton, 1989), which was confirmed in our study. However, negative correlations were observed between nematode population densities and soil pH on P. brachyurus in pineapple (Sarah et al., 1991), and between Mn on H. dihystera and X. elongatum in sugarcane (Cadet et al., 2004). By contrast, positive correlations were demonstrated between nematode abundance and soil exchangeable bases (Mg and K) for root-knot nematodes (Meloidogyne spp.) in tobacco (Kincaid et al., 1970) and tomato (Dabire et al., 2007), and for Scutellonema spp. in maize/beans, Crotalaria, Tephrosia and Sesbania spp. cropping systems (Kandji et al., 2001). Cadet et al. (2004) mentioned that soil factors had the strongest relationship with nematode abundance (particularly Helicotylenchus spp. and to a lesser extent Xiphinema spp.) in sugarcane. Previous studies demonstrated that relationships between soil factors and nematode species could vary depending on the corresponding habitat (Noe & Barker, 1985; Francl, 1993). In terms of surveyed provinces, we found lower nematodes densities in Belfaa compared to others. This can be explained by the soil components and texture (Badra & Yousif, 1979). Belfaa has mostly sandy loam soil texture, which may not be ideal to assemble an appropriate habitat for nematodes. Manlay et al. (2000) reported that bulk content associated with clay texture can led to enhanced nematodes densities. The
strong presence of PPN in the Biougra and Khmiss Ait Amira provinces may be considered as indicative of some improvement in the chemical characteristics of the soil. Inorganic ions also were shown to have an impact on nematodes movement (Castro & Belser, 1990) and to influence the balance between species (Villenave & Cadet, 1999), which could explain why the variation of frequency and abundance of red raspberry nematodes on the surveyed provinces depended on the soil type. This suggests that soil properties play an important role in PPN communities.
In conclusion, this study provides general information on genera diversity, incidence and distribution of PPN in raspberry polytunnels of the Souss-Massa region in Morocco and reveals a high diversity of economically damaging PPN. This description of PPN assemblages and their relationship with soil physico-chemical properties provide a starting point from which appropriate nematode management strategies can be implemented. However, more intensive observation including yield loss estimate are required to have better understanding of the relative importance of PPN in Moroccan raspberry polytunnels.
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Fouad Mokrini, Salah-Eddine Laasli, Driss Iraqui, Ahmed Wifaya, Abdelaziz Mimouni, Gul Erginbas-Orakci, Mustafa Imren and Abdelfattah A. Dababat. Распространение и встречаемость паразитических нематод растений, связанных с малиной (Rubus idaeus) в регионе Сусс-Масса, Марокко: связь с физико-химическими свойствами почвы.
Резюме. Малина (Rubus idaeus), выращиваемая в парниках, была исследована с февраля по апрель 2018 года в регионе Соус-Масса, Марокко. Цель исследования - изучить разнообразие и частоту появления паразитических нематод, влияющих на урожай малины, и оценить влияние физико-химических свойств почвы на этих нематод. Двенадцать родов нематод были определены из образцов почвы и корней, собранных из 41 парника в трех провинциях (Belfaa, Biougra и Khmis Ait Aimra). Наиболее распространенными паразитическими нематодами были виды из родов Pratylenchus, Meloidogyne и Helicotylenchus. Что касается их численности и частоты встречаемости, то четыре рода (Pratylenchus, Meloidogyne, Helicotylenchus и Tylenchus) были многочисленными и частыми по всему региону. Несколько родов нематод были значительно связаны с текстурой почвы, органическим веществом и pH, что указывает на то, что свойства почвы играют важную роль в сообществах паразитических нематод растений. Это описание комплексов нематод, связанных с парниками, в которых возделывается красная малина в регионе Сусс-Масса, обеспечивает отправную точку, с которой будут проводиться дальнейшие исследования для других регионов выращивания малины в Марокко, а также для разработки эффективных стратегий управления.
