Economic injury levels and sequential sampling plans for control decision-making systems ofBemisia tabacibiotype B adults in watermelon crops

2018 ◽  
Vol 75 (4) ◽  
pp. 998-1005 ◽  
Author(s):  
Carlos H de O Lima ◽  
Renato A Sarmento ◽  
Poliana S Pereira ◽  
Arthur V Ribeiro ◽  
Danival J Souza ◽  
...  
Keyword(s):  
Decision Making ◽  
Sequential Sampling ◽  
Sampling Plans ◽  
Economic Injury ◽  
Control Decision

Economic injury levels and sequential sampling plans forFrankliniella schultzeiin watermelon crops

2016 ◽  
Vol 73 (7) ◽  
pp. 1438-1445 ◽  
Author(s):  
Poliana S Pereira ◽  
Renato A Sarmento ◽  
Tarcísio VS Galdino ◽  
Carlos HO Lima ◽  
Fábio A dos Santos ◽  
...  
Keyword(s):  
Sequential Sampling ◽  
Sampling Plans ◽  
Economic Injury

scholarly journals Sequential sampling of Bemisia tuberculata (Bondar, 1923) (Hemiptera: Aleyrodidae) on cassava crop

2014 ◽  
Vol 86 (2) ◽  
pp. 889-896 ◽  
Author(s):  
ANTONIO S. SILVA ◽  
THIAGO A. MOTA ◽  
MARCOS G. FERNANDES ◽  
SAMIR O. KASSAB
Keyword(s):  
Decision Making ◽  
Pest Control ◽  
Chemical Control ◽  
Negative Binomial ◽  
Population Control ◽  
Sequential Sampling ◽  
Distribution Model ◽  
Sampling Plans ◽  
Three Samples ◽  
Cassava Crop

Estimate efficiently of the whitefly population (Bemisia tuberculata Bondar) in cassava, to assist in decision making of pest control is one of the advantages of sequential sampling plans. Therefore, the objective of this study was to determine a sequential sampling plan according to two methods of pest management, using biological and/or chemical control. Samples were obtained in a commercial field of 2.500,00 m2, divided into 100 plots. The visualization method was used for sampling of the upper leaves by counting the number of adults. In total 15 samples were taken weekly from January to April 2012. The spatial distribution model which best fit to the behavior of B. tuberculata adults was the negative binomial distribution. Levels adapted for biological and chemical control were five and twenty adults per plant, respectively. Sampling plans resulted in two decisions for each proposed method. Thus, for population control the upper limit was defined as S1 = 4.2056 + 2.1540n (biological) and S1 = 20.219 + 10.4306n (chemical); and the lower limit where the pest control is not recommended was defined by S0 = -4.2056 + 2.1540n (biological) and S0 = -20.219 + 10.4306n (chemical). Sequential sampling estimated the maximum number of sample units necessary for decision-making of three samples with 1.34 adults for biological control and 3.85 sample units with 7.39 adult pests for chemical control.

Economic injury levels and sequential sampling plans for Bemisia tabaci (Hemiptera: Aleyrodidae) biotype B on open-field melon crops

2019 ◽  
Vol 125 ◽  
pp. 104887 ◽  
Author(s):  
Thiago L. Costa ◽  
Renato A. Sarmento ◽  
Tamíris A. de Araújo ◽  
Poliana S. Pereira ◽  
Ricardo S. Silva ◽  
...  
Keyword(s):  
Open Field ◽  
Bemisia Tabaci ◽  
Sequential Sampling ◽  
Sampling Plans ◽  
Economic Injury ◽  
Biotype B

scholarly journals Sequential sampling plans and economic injury levels forEmpoasca kraemerion common bean crops at different technological levels

2017 ◽  
Vol 74 (2) ◽  
pp. 398-405 ◽  
Author(s):  
Marcelo Fialho de Moura ◽  
Mayara Cristina Lopes ◽  
Renata Ramos Pereira ◽  
Jorgiane Benevenute Parish ◽  
Mateus Chediak ◽  
...  
Keyword(s):  
Common Bean ◽  
Sequential Sampling ◽  
Sampling Plans ◽  
Economic Injury

scholarly journals Competing interests, clashing ideas and institutionalizing influence: insights into the political economy of malaria control from seven African countries

2020 ◽  
Author(s):  
Justin Parkhurst ◽  
Ludovica Ghilardi ◽  
Jayne Webster ◽  
Robert W Snow ◽  
Caroline A Lynch
Keyword(s):  
Decision Making ◽  
Malaria Control ◽  
Qualitative Interviews ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Health Community ◽  
Control Programmes ◽  
Control Decision ◽  
Sub Saharan ◽  
Economic Considerations

Abstract This article explores how malaria control in sub-Saharan Africa is shaped in important ways by political and economic considerations within the contexts of aid-recipient nations and the global health community. Malaria control is often assumed to be a technically driven exercise: the remit of public health experts and epidemiologists who utilize available data to select the most effective package of activities given available resources. Yet research conducted with national and international stakeholders shows how the realities of malaria control decision-making are often more nuanced. Hegemonic ideas and interests of global actors, as well as the national and global institutional arrangements through which malaria control is funded and implemented, can all influence how national actors respond to malaria. Results from qualitative interviews in seven malaria-endemic countries indicate that malaria decision-making is constrained or directed by multiple competing objectives, including a need to balance overarching global goals with local realities, as well as a need for National Malaria Control Programmes to manage and coordinate a range of non-state stakeholders who may divide up regions and tasks within countries. Finally, beyond the influence that political and economic concerns have over programmatic decisions and action, our analysis further finds that malaria control efforts have institutionalized systems, structures and processes that may have implications for local capacity development.

Sign in / Sign up

Export Citation Format

Share Document