جستجوی مقالات مرتبط با کلیدواژه « taylor's power law » 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.

Grape leafhopper, Arboridia kermanshah (Hemiptera: Cicadellidae) is one of the important pests of grapevine in Iran. In this research, the spatial distribution of A. kermanshah immature stages was investigated in a vineyard of the Kermanshah region, during 2017 and 2018. Grape leaf selected as sampling unit and sampling process carried out every week. The spatial distribution of eggs and immature stages of this pest calculated using: Index of dispersion, Morisita, Lloyd’s mean crowding index, Iwao’s patchiness regression and Taylor’s power law Indexes. Most used methods revealed an aggregated spatial distribution for the pest (b>1). According to the Iwao’s method in first sampling year, regression for 4th and 5th nymphal instars, was not significant (P-value>0.05). In Taylor method for both sampling years and Iwao’s method for second sampling year, distribution calculated random for 4th and 5th nymphal stages. Also, using the Morisita’s index in both sampling seasons and most (10) sampling dates, for the 4th and 5th nymphal stages, random distribution calculated. In both sampling seasons, Taylor’s power law method found to be more accurate than other methods in determination of the spatial distribution for this pest. Additionally, the lowest optimum sample sizes calculated using Taylor’s coefficients that were more affordable in comparison with other methods. Knowledge of the spatial distribution of this pest can be useful in designation of suitable sampling programs. Estimation of optimum sample sizes can also be useful in decreasing of sampling costs in both research and management programs.

Wheat is one of the most important field crops in Kermanshah province. Although aphids are not among the key pests of wheat, their population and damage can increase in suitable conditions. Sequential sampling methods for estimating the population of aphids in wheat fields can be useful in pest management as they promote effective use of time to estimate population density. In this study, spatial dispersion and a fixed precision sequential sampling program were investigated for Sitobion avenae (Hom.: Aphididae) population in wheat fields of SarPol-e Zahab, Kermanshah province.
A systematic weekly sampling was conducted in two selected wheat fields in SarPol-e Zahab region during years 2015 and 2016. Samples were collected by X-shaped movement in the field and totally 30 plants were selected randomly in each occasion. Taylor power law and Iwao’s patchiness indices were used to assess the spatial dispersion of the aphid population. A sequential sampling plan was also developed using the fixed-precision method of Green for estimating the density of adults, nymphs, and total population.
The results showed that Taylor power law fitted better to data than Iwao’s patchiness regression. The sample size increased with increasing precision level from 0.25 to 0.1 and it also increased when the population density decreased. At precision level of 0.1, average sample number for estimating the total population of aphids was different from 150 spikes in a density of 15 aphids/spike to 200 spikes in a density of 0.1 aphids/spike. At precision level of 0.25, the required sample for population estimation ranged from 25 spikes for a density of 15 aphids/spike to 30 spikes in a density of 0.1 aphid/spike.
According to the results, sequential model at the precision level of 0.25 is recommended to sample S. avenae population, because of reducing the cost and sampling time. The results obtained from this study can be useful to population management of aphids in wheat fields of SarPol-e Zahab region.

Spatial distribution of Sipha elegans as well as sequential and binomial sampling plans for estimating its population were studied in Miyaneh wheat fields, northwest of Iran. Sampling was carried out every three days by visiting 100 wheat stems and counting the aphids. Mean and variance of aphid population at sampling dates were used to estimate spatial distribution parameters. Regarding to better description of the data by Taylor's power law, parameters of this method were used to develop sequential and binomial sampling plans at both research and Integrated Pest Management (IPM) precision levels (0.1 and 0.25, respectively). S. elegans was observed in the field from early June to early July with aggregated spatial distribution. In sequential sampling model, sample size required to determine aphid mean population was decreased by increasing density and precision level from 0.1 to 0.25, for example, sample size required in mean density of one aphid per stem was decreased from 2138 stems at 0.1 to 324 stems at 0.25 precision level. Sample size was also smaller (342 stems) in binomial model than enumerative one (431 stems) at 0.25 precision level in the mentioned above aphid density. According to the results, sample size was enormous in both sequential and binomial models and at research precision level, but sequential and binomial sampling models at IPM precision level were recommended for determining S. elegans mean population because they reduce sampling time and cost in aphid’s integrated pest management programs.

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.

Crowds of the false chinch bugs Nysius cymoides appear in many canola fields of the country at pod ripening stage. To develop sequential sampling plans for eggs, immature stages and adults of the bug, samples were taken during two years from a canola field in the Broojerd Agricultural Research Station. Samples were randomly collected twice a week using a 5 × 5 cm quadrat and an aspirator. Then, the specimens were carried to the lab in alcohol tubes for counting the different stages. Taylor’s power law parameters were used to create Green’s sequential sampling plans at 10, 15 and 25 percent precision levels. The results showed that sample size for eggs was larger than nymphs and adults for different levels of precision. Sample sizes were dramatically reduced by increasing population density in different sequential models. Generally, sequential sampling models at 25 percent precision level are recommended for monitoring N. cymides populations due to reducing sample sizes to less than half, compared with those at 15 percent precision level. However, the 10 percent precision level models were not applicable because of large sample size estimations.

The distribution pattern of pest population is one of the factors not only effects on sampling program and data analysis method, but also can be used to measure the density of pests and their natural enemies. Thus, the spatial distribution pattern of the pea aphid, Acyrthosiphon pisum Harris (Hem.: Aphididae) and its two major predators, Hippodamia variegata Goeze (Col.: Coccinellidae) and Coccinella septempunctata (Linnaeus, 1758) (Col.: Coccinellidae) was investigated by different dispersion indices through 2012 and 2013 growing seasons. Dispersion pattern was determined by using Taylor's power law, Iwao's patchiness regression method and variance to mean ration test. Obtained results showed an aggregated distribution pattern of pea aphid and lady beetles. Based on R2 and p-value of regression analysis, Iwao's patchiness regression model provided a slightly more adequate description of variance/mean relationships than Taylor's power law. Among the species studied, the pea aphid adults and H. variegata showed the highest and C. septempunctata showed the smallest coefficients of Taylor's power law respectively. These results provide a reliable basis to develop efficient sampling plans for estimating aphid and their natural enemies populations