scholarly journals Factors Influencing the Occurrence of Foliar Pathogens in Commercial Watermelon Fields in South Carolina Based on Stratified Cluster Sampling

Plant Disease ◽  
2019 ◽  
Vol 103 (3) ◽  
pp. 484-494 ◽  
Author(s):  
Gabriel Rennberger ◽  
Patrick Gerard ◽  
Anthony P. Keinath
Keyword(s):  
South Carolina ◽  
Fungal Pathogens ◽  
Sampling Design ◽  
Field Size ◽  
Lower Probability ◽  
Cluster Sampling ◽  
Probability Of Occurrence ◽  
Commercial Farms ◽  
Pathogen Occurrence ◽  
Foliar Pathogens

The influence of environmental and management factors on the occurrence of foliar pathogens of watermelon was analyzed using survey-sampling data collected from commercial farms in South Carolina in spring 2015 and spring and fall 2016. A stratified two-stage cluster sampling design was used to sample symptomatic watermelon leaves from 56 fields of 27 growers in seven counties representing the main watermelon-producing areas in the state. In the sampling design, counties corresponded to strata, growers to first-stage clusters, and fields to second-stage clusters. Pathogens were identified on 100 leaves collected per field based on reproductive structures that formed on the leaves. Information about previous crops, fruit type, field size, transplanting date, first harvest date, and fungicides applied within 7 days and within 7 to 14 days prior to sampling was obtained from growers. Field alignment was determined with a compass. Survey-specific logistic regression procedures were used to analyze the effect of these factors on the probabilities of pathogen occurrence. Five fungal pathogens, Stagonosporopsis spp., Podosphaera xanthii, Cercospora citrullina, Colletotrichum orbiculare, and Myrothecium sensu lato (s.l.), and the oomycete Pseudoperonospora cubensis were included in the analyses. Among the factors we analyzed, there was a consistent increased probability of occurrence of Stagonosporopsis spp. in fields with a previous cucurbit crop, increasing probabilities of pathogen occurrence with increasing plant age, a lower probability of occurrence of some pathogens on triploid cultivars compared with diploid cultivars, and a decrease in probability of pathogen occurrence in fields aligned toward southwest or west. Application of fungicides significantly reduced the probability of observing C. citrullina, P. cubensis, and Stagonosporopsis spp. in 2015 and P. xanthii in spring 2016. This study emphasizes the importance of crop rotation and fungicide applications to manage foliar diseases of watermelon, particularly gummy stem blight, powdery mildew, and downy mildew. Crop age, cultivar type, and field alignment also were found to significantly influence the probability of pathogen occurrence. To the best of our knowledge, this is the first study examining the influence of various factors on foliar pathogens of watermelon with data collected from commercial fields.

scholarly journals Occurrence of Foliar Pathogens of Watermelon on Commercial Farms in South Carolina Estimated with Stratified Cluster Sampling

Plant Disease ◽  
2018 ◽  
Vol 102 (11) ◽  
pp. 2285-2295 ◽  
Author(s):  
Gabriel Rennberger ◽  
Patrick Gerard ◽  
Anthony P. Keinath
Keyword(s):  
South Carolina ◽  
Fungal Pathogens ◽  
Positive Association ◽  
Cluster Sampling ◽  
Corynespora Cassiicola ◽  
Two Stage ◽  
Common Pathogen ◽  
Commercial Farms ◽  
Pathogen Occurrence ◽  
Foliar Pathogens

A survey of foliar pathogens of watermelon based on two-stage cluster sampling was conducted on commercial farms in South Carolina in spring 2015, spring and fall 2016, and fall 2017. In total, 60 fields from 27 different growers in seven counties representing the main watermelon-producing areas in the state were sampled, using a stratified two-stage cluster sampling approach. In the sampling design, counties corresponded to strata, growers to first-stage clusters, and fields to second-stage clusters. In each field, 100 symptomatic leaves were collected at five equidistant sampling points along four transects encompassing a square shape of 2,500 m2. After collection, pathogens were identified based on reproductive structures formed on leaves during >12 h incubation. Estimates were obtained for the statewide probability of pathogen occurrence and associations between pathogen pairs. Six fungal pathogens, Stagonosporopsis spp., Podosphaera xanthii, Cercospora citrullina, Colletotrichum orbiculare, Myrothecium sensu lato (s.l.), and Corynespora cassiicola; the oomycete Pseudoperonospora cubensis; and three viral pathogens were identified on the examined leaves. With the exception of fall 2017, Stagonosporopsis spp. was the most prevalent pathogen in every season, followed by P. xanthii. The highest occurrence of P. cubensis was in spring 2015; it did not occur in 2016. The highest occurrence of C. orbiculare was in spring 2016; it did not occur in spring 2015. Myrothecium s.l. was the most common pathogen in fall 2017 and the second most common pathogen occurring by itself in fall 2016. The third most common pathogen in fall 2017, Corynespora cassiicola, was not observed in any other season. Eight of the 80 isolates of Stagonosporopsis spp. collected were identified as S. caricae, the rest as S. citrulli. All isolates of S. caricae were found in spring 2015 and originated from two fields in different counties. A total of three positive and five negative associations were found between pathogen pairs co-occurring on the same leaf. A positive association between Stagonosporopsis spp. and C. citrullina was the only significant association between pathogens found in two seasons, spring 2015 and spring 2016. Based on estimates of probability of pathogen occurrence across seasons, Stagonosporopsis spp. and P. xanthii are the most common pathogens on watermelons in South Carolina. This is the first report of C. cassiicola, S. caricae, and Myrothecium s.l. on watermelon in South Carolina.

scholarly journals Investigation of Fungi Causing Twig Blight Diseases on Peach Trees in South Carolina

Plant Disease ◽  
2019 ◽  
Vol 103 (4) ◽  
pp. 705-710 ◽  
Author(s):  
Martha H. Froelich ◽  
Guido Schnabel
Keyword(s):  
South Carolina ◽  
Fungal Pathogens ◽  
Management Strategies ◽  
Brown Rot ◽  
Cambium Layer ◽  
Twig Blight ◽  
Botryosphaeria Obtusa ◽  
Peach Trees ◽  
Moderately Resistant ◽  
Prevalent Species

A survey of fungal pathogens causing twig blight on commercial peach trees was conducted in South Carolina in the fall of 2016. Shoots with cankers, pycnidia, and dieback were collected from six locations around the state. Isolates obtained from these samples were identified as Botryosphaeria obtusa, Phomopsis amygdali, Leucostoma persoonii, and Cytospora sp., based on colony morphology, conidia size and shape, and ribosomal DNA sequence analysis. L. persoonii was the most prevalent species and was isolated in five of the six locations, followed by P. amygdali and B. obtusa. The sensitivity of representative isolates of B. obtusa, P. amygdali, and L. persoonii to fungicides of different FRAC codes was evaluated. All species tested were sensitive to thiophanate-methyl (FRAC 1) and pyraclostrobin and azoxystrobin (both FRAC 11), whereas all species were resistant to boscalid and fluopyram (both FRAC 7). P. amygdali and B. obtusa were sensitive to difenoconazole and propiconazole (both FRAC 3), whereas L. persoonii was moderately resistant. L. persoonii was the most virulent species based on expansion of mycelium in the cambium layer of 2-year-old, detached twig pieces. Bacterial spot (BS)-sensitive cultivar ‘O’Henry’ was most susceptible to B. obtusa compared with BS-sensitive ‘Summerprince’, brown rot (BR)-resistant ‘Contender’, and BR-sensitive ‘Coronet’ but was least susceptible to L. persoonii. Coronet was most susceptible to L. persoonii. There were no significant differences between susceptibility of the cultivars to P. amygdali. This study established that L. persoonii is currently the most frequent twig blight pathogen in South Carolina, perhaps owing to its superior fitness. Some fungicides were effective in controlling all twig blight pathogens and may therefore be useful for chemical management strategies. Our study also provides the first evidence that the genetic basis of resistance to BS and BR in peach trees is not necessarily linked to tolerance to wood pathogens.

An optimal multivariate cluster sampling design

2019 ◽  
Vol 49 (24) ◽  
pp. 6121-6128
Author(s):  
M. G. M. Khan ◽  
Mahmood A. Rashid ◽  
Sushita Sharma
Keyword(s):  
Sampling Design ◽  
Cluster Sampling ◽  
Multivariate Cluster

Cessation of E-Cigarette Use Among Adolescents and Its Associated Factors

2019 ◽  
Vol 31 (7_suppl) ◽  
pp. 53S-60S ◽  
Author(s):  
Thamil Arasu Saminathan ◽  
Wan Shakira Rodzlan Hasani ◽  
Tania Gayle Robert Lourdes ◽  
Muhammad Fadhli Mohd Yusoff ◽  
Hasimah Ismail ◽  
...  
Keyword(s):  
Associated Factors ◽  
Sampling Design ◽  
Multiple Logistic Regression Analysis ◽  
Cross Sectional Study ◽  
Cluster Sampling ◽  
Cigarette Use ◽  
Sectional Study ◽  
Cross Sectional ◽  
Complex Sampling ◽  
Complex Sampling Design

We assessed the prevalence of cessation of e-cigarette and its associated factors among adolescents in Malaysia. This study analyzed data from the Tobacco and E-Cigarette Survey among Malaysian Adolescent (TECMA) in 2016, a cross-sectional study with 2-stage stratification cluster sampling. A total of 14 832 school-going adolescents aged 10 to 19 years participated in this survey. A complex sampling design and multiple logistic regression analysis were applied. Nearly half of the adolescents (49.9%; 95% confidence interval [CI] = 44.9-55.0) who had ever used e-cigarette ceased the usage. Based on multivariate analysis, adolescents were more likely to quit e-cigarette because they could not afford the e-cigarette (adjusted odds ratio [aOR] = 2.39, 95% CI = 1.78-3.20), if they are aged 13 year and older (aOR = 1.80, 95% CI = 1.25-2.61), and those who claimed their e-cigarette does not contain nicotine (aOR = 1.35, 95% CI = 1.03-1.78). E-cigarette prevention efforts among adolescents could consider the cessation factors described in this study.

scholarly journals A National Baseline Prevalence Survey of Schistosomiasis in the Philippines Using Stratified Two-Step Systematic Cluster Sampling Design

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Lydia Leonardo ◽  
Pilarita Rivera ◽  
Ofelia Saniel ◽  
Elena Villacorte ◽  
May Antonnette Lebanan ◽  
...  
Keyword(s):  
Intervention Program ◽  
Sampling Design ◽  
National Level ◽  
The Philippines ◽  
Cluster Sampling ◽  
Prevalence Survey ◽  
Food Borne ◽  
Two Phases ◽  
Low Prevalence ◽  
Systematic Cluster

For the first time in the country, a national baseline prevalence survey using a well-defined sampling design such as a stratified two-step systematic cluster sampling was conducted in 2005 to 2008. The purpose of the survey was to stratify the provinces according to prevalence of schistosomiasis such as high, moderate, and low prevalence which in turn would be used as basis for the intervention program to be implemented. The national survey was divided into four phases. Results of the first two phases conducted in Mindanao and the Visayas were published in 2008. Data from the last two phases showed three provinces with prevalence rates higher than endemic provinces surveyed in the first two phases thus changing the overall ranking of endemic provinces at the national level. Age and sex distribution of schistosomiasis remained the same in Luzon and Maguindanao. Soil-transmitted and food-borne helminthes were also recorded in these surveys. This paper deals with the results of the last 2 phases done in Luzon and Maguindanao and integrates all four phases in the discussion.

A Test of Cluster Sampling in Forest Inventories

1975 ◽  
Vol 5 (2) ◽  
pp. 269-272 ◽  
Author(s):  
G. M. Bonnor
Keyword(s):  
Random Sampling ◽  
Sampling Design ◽  
Simple Random Sampling ◽  
Cluster Sampling ◽  
Field Sampling ◽  
Forest Inventories ◽  
Straight Line ◽  
Time Required ◽  
Variance Estimates ◽  
The Given

During a recent pilot survey in Newfoundland, forest data were collected using a stratified, one-stage cluster-sampling design. The data were analyzed to determine if, within the stratified framework, cluster sampling would be more efficient than simple random sampling. Each cluster consisted of five point-samples located in a straight line. For the analysis, volume and variance estimates were determined from clusters of 1,2,3,4 and 5 points. During the survey, records were kept of the time required to complete various field-sampling tasks. These were used in lieu of cost data in the analysis. Results indicated that, for the given conditions, simple random sampling was more efficient than cluster sampling. However, relatively small changes in the conditions would make cluster sampling more efficient.

scholarly journals On Using Adaptive Cluster Sampling Design in Forest Inventory: It's Implication to Forest Biodiversity Status Reporting

2009 ◽  
Vol 9 (1) ◽  
pp. 56-66
Author(s):  
Dennis Peque ◽  
Keyword(s):  
Sampling Design ◽  
Systematic Sampling ◽  
Cluster Sampling ◽  
Forest Biodiversity ◽  
Adaptive Cluster Sampling ◽  
State University ◽  
Statistical Efficiency ◽  
Forest Reserve ◽  
Sparse Population ◽  
Combined Data

This paper presents adaptive cluster sampling (ACS) as a method of assessing forest biodiversity. In this study, ACS was used to estimate the abundance of ecologically sparse population of Diospyros philippinensis (Desrousseaux) within the Visayas State University Forest Reserve. Its statistical efficiency were analyzed by comparing them to the conventional systematic sampling (Syst) estimator. Results indicated that adaptive cluster sampling (ACS) plots captured more trees into the sample compared to systematic sampling (Syst) plots. In addition, ACS estimates for mean and total numbers of individuals per ha was higher than systematic sampling estimates and in terms of variance ACS gave substantially lower variance than systematic sampling. However, the ratio of the adjusted SE of ACS to the adjusted SE of systematic sampling for each species and the combined data of the two species was generally lesser than 1 which means that ACS was not a better design than systematic sampling.

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