جستجوی مقالات مرتبط با کلیدواژه « پراکنش فضایی » در نشریات گروه « گیاهپزشکی »

The black bean aphid, Aphis fabae Scopoli (Hemiptera: Aphididae) is an important pest of sugar beet fields in Khuzestan province. Knowledge about economic and precise sampling program can play critical role for developing integrated pest management (IPM) program of this pest. In this study, the spatial distribution of the pest was investigated in a research sugar, 1 ha, beet field of Shush district, and a fixed-precision sequential sampling program for estimating the aphid density was developed. Samplings were performed every 3 days and spatial distribution of this pest on sugar beet plants was evaluated using two models, Taylor's power law and Iwao's patchiness. The pest distribution on sugar beet plant was aggregated and Taylor's power law provided better fitness to the spatial distribution data of this aphid on sugar beet plants. Therefore, The Green's model was used for developing fixed-precision sequential sampling of the aphid. Based on the pest density, the optimum sample size ranged from 99-130 plants or 16-21 plants at desired precision level 0.1 or 0.25, respectively. Calculated stop lines implicated that the sampling has to be continued till the aphid cumulative number per sugar beet plant reach to 10 at precision level 0.25. The stop line was 25 aphids at precision 0.1.

Oak thrips, Liothrips pragensis Uzel is found on oak trees in Zagros forests. In this study, population fluctuation and spatial distribution of this species were investigated in oak forests of Javanrud county (Kermanshah province), in 2021. Oak leaves were selected as the sampling unit. Sampling was performed every week from five different areas, so leaves were shaken on a white plastic tray and thrips specimens with a soft brush were transferred into Eppendorf tubes containing 75% alcohol. The results showed that the activity of oak thrips in all five studied areas was occurred on May and their activity and density gradually decreased until it reached its lowest level in September. The highest population density of oak thrips was observed on May with an average of 2.93 ± 0.56, 2.23 ± 0.47, 2.23 ± 0.34, and 0.90 ± 0.28 thrips per sample unit, in Sefid Barg, Bileei, Cheshme Miran and Helanie areas, respectively. However, the highest density was obtained in Hori Abad region in June with an average of 2.06 ± 0.43 thrips per sampling unit. The results of spatial distribution showed that the spatial distribution of oak thrips based on Taylor’s power law and Iwao’s methods was random and aggregated, respectively. Furthermore, based on goodness of fit, the Iwao’s patchiness method was more suitable than the Taylor’s power law method for estimating the spatial distribution of the pest.

In this research, barley aphids in Mahidasht region of Kermanshah province were identified. Spatial distribution type and statistics for corn leaf aphid, Rhopalosiphum maidis (Fitch) were also studied and sequential sampling models were developed. Regular weekly sampling was carried out in 2015, 2016 and 2017. Each sampling date, 100 tillers were randomly visited and aphids were transferred to the laboratory for counting and identification. Taylor’s power law was used to determine spatial distribution type and statistics and sequential sampling models were developed according to Green (1970). Results revealed feeding of five species of aphids on barley including greenbug, Schizaphia graminum, rose-grain aphid, Metopolophium dirhodum, the English grain aphid, Sitobion avenae,corn leaf aphid, R. maidis and bird cherry-oat aphid, R. padi. Corn leaf aphid was more abundant during the season with 93.8%, 94.2% and 93.2% of aphids collected in 2015, 2016 and 2017, respectively. Low populations density of the other four species was observed every three years. Spatial distribution type of corn leaf aphid in barley field was determined as cumulative (b = 1.45). Sample size required in models with precision levels of 0.1 and 0.25 at mean aphid densities observed in the barley field (1.02 - 44.32 aphids per tiller) was 70 -524 and 11-84 tillers, respectively. In conclusion, sequential sampling model developed at the precision level of 0.1 was evaluated time consuming due to large sample size required, but the model at pest management precision level (0.25) was recommended for monitoring leaf corn aphid in barley fields.

In order to study the population fluctuations and spatial distribution of onion thrips, Thrips tabaci (Lindeman) (Thysanoptera: Thripidae) in alfalfa fields of Eyvan city (Ilam province), sampling were done weekly in different growth stages of alfalfa from the beginning of April to late September 2017. The results of population fluctuations showed that the highest population of adult and immature thrips stages were average 6.20 ± 0.85 and 1.35 ± 0.44 in 20 plants in August and September, during the 3th cutting of alfalfa. The study of the relationship between the population dynamics of adult and immature stages with temperature showed that there was a significant and positive correlation between population changes and temperature. Based on Taylor’s power law, the spatial distribution for both adult and immature stages was randomized, but the total stages were aggregated. Whereas, based on Iwao's patchiness, regression between Log S2 and Log m in immature stage was not statistically significant (P> 0.05). The spatial distribution pattern of adult stages was randomized and for both adult and immature stages was aggregated. The parameters derived from population fluctuations and the spatial distribution pattern of this species can be used in the sampling program and estimates of population density of this pest in alfalfa fields.

Wheat thrips, Haplothrips tritici (Kurdjumov) (Thysanoptera: Phlaeothripidae) is one of the most important pests in wheat fields in Ilam Province. In order to study the population fluctuations and spatial distribution of wheat thrips in wheat fields of Eyvan city, sampling was weekly carried out during different growing stages of wheat from April to the end of June 2016. Spatial distribution of immature as well as adults of wheat thrips was estimated using Taylor’s power law and Iwao’s patchiness regression methods. The population peaks in both of the irrigated and rainfed wheat fields occurred in middle of May. Based on R2 and F values of regression analysis, in irrigated wheat fields, Iwao's patchiness provided a more adequate description of spatial distribution than Taylor’s power law for wheat thrips. The spatial distribution for adults was randomized but for larval stages and the total stages (larvae and adults) was aggregated. Whereas, in rainfed fields, Taylor’s power law provided a more adequate description of spatial distribution than Iwao's patchiness. The spatial distribution for both larval and adult stages was clumped and for the total was randomized.

The false chinch bugs, Nysius cymoides appears in many canola fields of the country at harvesting time. Spatial distributions of different stages of the bug were studied in canola fields of the Broojerd Agricultural Research Station during years 2006-2007. Twenty to twenty five samples were randomly taken via an aspirator from a 25 cm2 rimmed-quadrate twice a week. Each sample was kept in alcohol and carried to the laboratory for counting number of eggs, different nymphal instars and adult females and males. Spatial distribution pattern of each stage was determined by both Taylor’s power law and Iwao’s regression method. Aggregated pattern was detected by both models for most immature stages and adults. However, the data showed a better fit to Taylor’s model. Both methods demonstrated different patterns for variance-mean model. Iwao’s method predicted larger or negative sample size for low densities of the bug, which is inapplicable. Overall, Taylor’s power law had a better estimation of spatial distribution parameters and predicted smaller sample size than those of Iwao’s regression method for N. cymoides.

Aphids are secondary pests in cereal fields but sometimes they outbreak and cause considerable damage to wheat and barley. Integrated pest management is one of the most important strategy in insect ecology and estimating population can be used to employ the strategy. Sampling of population is the most basic outdoor activities in ecology and as time goes need to fast and reliable sampling methods be felt more. Dispersion can be quantified by the comparison of observed frequency distribution data (based on a common sample unit) with mathematical models used to describe possible spatial distributions. Knowledge about dispersion pattern of an organism is required for understanding population biology, resource exploitation and dynamics of biological control agents. Moreover determination the dispersion pattern of a species is essential for developing an effective pest management program. . The degree of aggregation can be expressed by several indices of dispersion. Taylor's power law and Iwao's patchiness regression are two main models that also depend on the relationship between the sample mean and the variance of insect numbers per sampling unit. The slope of the regression model is used as an index of aggregation. Usually, sampling of insects is from the estimatation of some population parameter for research purposes or to make a pest control decision. However, the often large, fixed sample size necessary for research may be inappropriate where frequent and rapid monitoring is required to make a control decision. In such cases the sequential sampling method may be a better alternative as it characteristically has a variable sample number and can serve to classify a population in relation to a treatment level rather than provide actual estimates of population density. Designing sampling plans based on these indicators has been reported to reduce sampling effort, cost and minimize variation of sampling precision. As there were no any information about the spatial distribution and sequential sampling program of cereal aphids in Khuzestan province, this study was undertaken to determine dispersion pattern of cereal aphids in order to develop a suitable sampling plan for these pests.
Material and In order to assess the distribution pattern and density of aphid species on wheat the mixed population of aphids was sampled during 2012-2013 at three pesticide-free wheat fields (two wheat fields in Ahvaz and one in Mollasani) in Khuzestan province, southwestern of Iran. Each field was sampled twice a week throughout the growing season from initiation of tillering to grain ripening stage. Each sample included 25 plant, which were chosen randomly and the number of aphids was counted. Tillers were collected by traveling an X-shaped procedure. Spatial distribution of different developmental stages of wheat aphids were described by calculating dispersion indices (Taylor’s and Iwao’s indices of dispersion). A sequential sampling plan was also developed using the fixed precision method of Green for estimating the density of adults, Nymphs and total population.
Result and Analysis of spatial distribution pattern using Taylor’s power law and Iwao’s regression model showed that Taylor's power law provides a better description of the aphids spatial distribution and based on this model dispersion pattern of wheat aphids population was aggregated for nymph and the total of life stage, but was random for adult life stage. Green’s fixed precision sequential sampling plan at precision levels of 0.25 and 0.10 was designed for estimating the density of the adult, nymph and total population. The results showed that the required sample size increased dramatically with increasing levels of precision, and generally ranged from 1 to 34 and 8 to 210 tillers at the precision levels of 0.25 and 0.10 respectively, and the optimum sample size for the estimation of mean aphid density decreased approximately between 44% - 83%.

Between 2010 and 2011, spatial distribution and fixed precision sequential sampling plans were determined for two aphids, Rhopalosiphum maidis F. and Schizaphis graminum R., in wheat fields in Badjgah countryside of Iranian Fars province. For this purpose, two fields of two hectares each were selected and sampled on weekly basis. Each sample consisted of 200 randomly selected wheat plants along with the total number of counted aphids. Based on RV, the best sample unit was four stems. This data was used to describe spatial distribution pattern of R. maidis and S. graminum by Taylor’s power law (TPL) and Iwao’s patchiness regression methods. The results indicated aggregated spatial distribution of aphid's populations in wheat fields, based on the mentioned methods. The TPL provided a better description of the aphid's spatial distribution. Since regression line slopes were not significantly different for S. graminum and R. maidis, the same Green model was proposed for both species. In this model, minimum numbers of samples were 20, 12 and 9 for precision levels of 0.15, 0.25 and 0.3, respectively. Comparing Green and conventional methods in 0.15, 0.25 and 0.3 precision levels showed that the number of required samples were reduced 77.8 ± 1.05, 78.3 ± 0.91 and 81.4 ± 0.81 percent, respectively. Based on Wilson and Room's model, when the mean populations of aphids were 1.6, 3.86 and 5.62, the proportion of infestation in the field were 0.5, 0.75 and 0.85, respectively. Therefore, by increasing the infestation percentage of the samples, the number of required samples will be reduced.

Sitobion avenae (F.) is an important species infesting wheat spikes in region Dehloran, Iran. To evaluate the spatial distribution of O. avenae on wheat, weekly samplings were carried out from five winter wheat fields around Dehloran throughout 2010-2011. Spatial distribution of different developmental stages and morphs of the aphid were described by fitting data to Poisson (random) and negative binomial (clumped) distributions. Based on R2 and F of regression analysis, Taylor’s power law provided a more adequate description of variance/mean relationships than Iwao’s patchiness regression model, and the b values ranged from 1.102 (alate adults) to 1.463 (apterous adults). Other distribution indexes and spatial distribution models showed the cumulative distribution of aphid population on clusters and fitting to negative binominal distribution in many section of season. Mature winged aphids were more likely to show a random distribution compared to other developmental stages.

Black bean aphid، Aphis fabae Scopoli، is the most important pest of faba bean that causes economic damage on this crop. Spatial dispersion of the aphid using Taylor power law and Iwao patchiness indices was studied by weekly sampling in faba bean fields of Veis region، Ahwaz، during 2010-2012. Taylor''s power law and Iwao patchiness were used to investigate spatial dispersion of A. fabae and a resampling for validation of sampling technique (RVSP) was used to develop a Green''s fixed precision sequential sampling for this aphid population at precision levels of 0. 25 and 0. 1. Results showed that A. fabae had aggregation dispersion on faba bean and Taylor''s power law had more fitness to the obtained data. The Optimum sample size to estimate the population density of A. fabae ranged from 25 to 2 and 73 to 10 samples depending on population densities at precision levels of 0. 25 and 0. 1، respectively.

tomato pests, such as tomato fruitworm, Helicoverpa armigera Hünber (Hym.Eurytomidae), cause high reduction in tomato production, but no sampling program for population estimate and management of them has been developed. Spatial distribution of immature stages of the tomato Fruit-worm was determined by fitting data to either taylor’s, iwao’s, mean_variance ratio, k and morisita calculating dispersion indices, during 2008 and 2009 growing seasons in tomato fields of Gorgan, Spatial distribution immature (egg and larvae) is a random. Based on R2 and p-values of regression analysis, for most of the natural enemy groups, Taylor’s power law generally provided a more adequate description of variance/mean relationships than Iwao’s patchiness regression model. The median part of plant were fitted most value of Taylor’s b index. Percentage fit of immature stages the dispersion more random ratio bionominal value of morisita, k and mean-variance.

Sugarcane pink stem borers, Sesamia spp., are the key pests of sugarcane in the south of Khuzestan province, Iran. These pests damage heavily the sugarcane crop and sugar product every year. In this research, spatial dispersionof the stem borers populations were studied in three sugarcane fields (25 hectare each, Cp69-1062 cultivar) in 2008. Sampling was carried out monthly in seven stages. External symptoms of pest damage were used as a population indicator and the number of infested stems and internodes of sugarcane were recorded in each sampling station. In order to determine the type of pest spatial dispersionin these three fields, various classical statistics indices were used. In all sampling stages, values of the variance to mean proportion index, index of Patchiness and Morisita’s index were significantly higher than one, and values of 1/k index and Green’s index were higher than zero. The obtained results of all indices indicated that spatial dispersionof Sesamia spp. was aggregated. The regression coefficients of Taylor’s power law b and Iwao’s β were determined 1.45±0.065 and 1.18±0.031, respectively. Thus, they had significant difference from one, and both indicated the aggregated spatial dispersionfor the pest life. Based on R2 and P-values of regression analysis, Iwao’s patchiness showed a better fitness for pest spatial dispersiondata in comparison with Taylor’s power law.

In order to investigate density fluctuation and spatial distribution of the main aphidophagous predators and develop a fixed-precision sequential sampling plan, a weekly sweepnet sampling was conducted at five winter wheat fields in Gorgan region in northern Iran, during two growing seasons of 2006 and 2007. Spatial distribution of the predators was described by fitting data to Poisson (random) distribution, as well as by calculating three dispersion indices. A sequential sampling plan was also developed using the fixed-precision method of Green for estimating the mean density of predator's population. Four species of Coccinella septempunctata L., Propylea quatuordecimpunctata L., Eupeodes corollae (Fabricius) and Episyrphus balteatus (De Geer) comprised 18.75, 14.25, 41.54 and 6.02 percent of the predator's community, respectively. For all predators, with the exception of E. corollae, the parameters b of Taylor’s power law did not differ significantly from one, indicating that populations of them exhibited random spatial distribution. Fitting population’s frequency data to distribution models also showed that Poisson (random) distribution provided a good fit to the population frequencies during most of the wheat growing season. Sequential sampling results showed that the number of sample units required to stop sampling was depended upon mean population abundance and desired level of precision. So that, for C. septempunctata, at density of 0.033-0.6 adult/10 sweepnet and precision level of 0.25, the required sample size ranged from 400 to 41 sweepnets. At the same time, for P. quatuordecimpunctata, at density of 0.02-1.8 adult/10 sweepnets, the required sample size ranged from 775 to 10 sweepnets. For E. corollae and E. balteatus, required sample size ranged from 4 to 400 and 57 to 175 sweepnets, respectively. Regarding number of sample units, at high density of predators, sweepnet sampling was a cost-effective method to estimate predator's population density, whereas at low population levels, sweepnet sampling was a time-consuming method and a quite large sample was required to achieve the desired precision of 0.25. Therefore, we recommend the comparison of precision and efficiency of sweepnet with other sampling procedures to determine the best sampling method for estimating population density of predators in wheat fields.

Spatial distribution of different natural enemies of the cotton aphid, Aphis gossypii Glover, was determined by fitting data to either Poisson (random) or negative binomial (aggregated) distributions and calculating dispersion indices, during 2002 and 2003 growing seasons in cotton fields of Gorgan, northern Iran. Based on R2 and p-values of regression analysis, for most of the natural enemy groups, Taylor’s power law generally provided a more adequate description of variance/mean relationships than Iwao’s patchiness regression model. Natural enemy populations, especially parasitoids, cecidomyiid species and coccinellid eggs, were aggregated during most of the growing season, and negative binomial models generally fitted the data sets better than the Poisson series in cotton fields. Percentage fit for some species such as larva and adult stages of chrysopids, adult stages of Coccinella septempunctata L. and Scymnus spp., and spider species, showed a distinct tendency to the Poisson distribution and low values of Taylor’s b index. There were no significant relationships between k (a measure of the amount of clumping in negative binomial distribution) and mean values, indicating the existence of a common k for the most of the natural enemy groups. These results can provide a reliable basis to develop proper sampling plans for estimating or classifying natural enemy populations in cotton fields of Gorgan.