scholarly journals CYANTRANILIPROLE AND SPINOSAD RESIDUES IN FLUE-CURED TOBACCO

2017 ◽  
Vol 54 (1) ◽  
pp. 1-3
Author(s):  
M.C. Vann ◽  
L.R. Fisher ◽  
D.S. Whitley
Keyword(s):  
Detection Techniques ◽  
Chemical Residues ◽  
Residue Levels

From 2013 to 2015, research was conducted to estimate the maximum expected residue levels for the insecticides cyantraniliprole and spinosad following application to flue-cured tobacco. Data were generated in order to assist industry in establishing Guidance Residue Limits for both compounds. The insecticides were applied to fields of tobacco at maximum rates in accordance with the labeled rates and the harvested/cured leaf was analyzed in a lab for chemical residues. The findings indicated that the expected residues on cured leaf would be low or not quantifiable under existing detection techniques.

Monitoring Pesticide Residues in Fruits and Vegetables at Two of the Biggest Fresh Produce Markets in Africa

2016 ◽  
Vol 79 (11) ◽  
pp. 1938-1945 ◽  
Author(s):  
MBULAHENI T. MUTENGWE ◽  
LIZYBEN CHIDAMBA ◽  
LISE KORSTEN
Keyword(s):  
Pesticide Residue ◽  
Fruits And Vegetables ◽  
Fresh Produce ◽  
Monitoring Program ◽  
Agricultural Practices ◽  
Perceived Safety ◽  
Pesticide Monitoring ◽  
Chemical Residues ◽  
Maximum Residue Levels ◽  
Residue Levels

ABSTRACTIn most countries, fresh produce sold at local markets is usually not analyzed for agricultural chemical residues as export products are, which raises concerns about the perceived safety levels of local food supplies in contrast with exported products. The aim of this study was to determine pesticide residue levels in fruits and vegetables sold at two of the biggest fresh produce markets in Africa. A total of 199 fruit and vegetable samples were collected between 2012 and 2014 and analyzed for 74 pesticides commonly used in the horticultural sector. Of the samples analyzed, 91% were compliant with set maximum residue levels (MRLs). The remaining samples either contained unregistered chemicals (8%) or exceeded set MRL values (1%). Products containing more than one pesticide residue constituted 4.02% of all samples tested. Imazalil and iprodione were found to be the most frequently detected pesticides (12 samples each). Boscalid, endosulfan, profenofos, and procymidone were associated with the most noncompliance, including exceeding MRL values or being unregistered for the specific crop. The establishment of a national pesticide monitoring program is essential for the country and would ensure that pesticides are used in accordance with good agricultural practices.

ION DETECTION TECHNIQUES APPLIED TO RYDBERG ATOMS IN EXTERNAL FIELDS

1983 ◽  
Vol 44 (C7) ◽  
pp. C7-193-C7-208 ◽  
Author(s):  
F. Penent ◽  
C. Chardonnet ◽  
D. Delande ◽  
F. Biraben ◽  
J. C. Gay
Keyword(s):  
Rydberg Atoms ◽  
External Fields ◽  
Ion Detection ◽  
Detection Techniques

Comparative quantification of phosphatidylcholine in sea urchins eggs by instrumental TLC with various detection techniques

Planta Medica ◽  
2010 ◽  
Vol 76 (12) ◽  
Author(s):  
S Ivanova ◽  
I Urakova ◽  
O Pozharitskaya ◽  
A Shikov ◽  
V Makarov
Keyword(s):  
Sea Urchins ◽  
Detection Techniques

Advances in profiling of natural products by triple detection techniques combined with super critical CO2 mobile phases and Sub-2 µm stationary phases

Planta Medica ◽  
2015 ◽  
Vol 81 (16) ◽  
Author(s):  
D Rodriguez Cabaleiro ◽  
P Hong ◽  
G Isaac ◽  
J Yuk ◽  
K Yu ◽  
...  
Keyword(s):  
Natural Products ◽  
Stationary Phases ◽  
Detection Techniques ◽  
Mobile Phases

Conflict Detection Techniques for Preserving Privacy in Social Media

2018 ◽  
pp. 78-85
Author(s):  
Fulpagare Priya K. ◽  
Nitin N. Patil
Keyword(s):  
Social Media ◽  
Privacy Management ◽  
Crucial Importance ◽  
Network Integration ◽  
Critical Problem ◽  
Detection Techniques ◽  
Privacy Preferences ◽  
Content Sharing ◽  
Privacy Settings ◽  
Relationship Network

Social Network is an emerging e-service for Content Sharing Sites (CSS). It is an emerging service which provides reliable communication. Some users over CSS affect user’s privacy on their personal contents, where some users keep on sending annoying comments and messages by taking advantage of the user’s inherent trust in their relationship network. Integration of multiple user’s privacy preferences is very difficult task, because privacy preferences may create conflict. The techniques to resolve conflicts are essentially required. Moreover, these methods need to consider how users would actually reach an agreement about a solution to the conflict in order to offer solutions acceptable by all of the concerned users. The first mechanism to resolve conflicts for multi-party privacy management in social media that is able to adapt to different situations by displaying the enterprises that users make to reach a result to the conflicts. Billions of items that are uploaded to social media are co-owned by multiple users. Only the user that uploads the item is allowed to set its privacy settings (i.e. who can access the item). This is a critical problem as users’ privacy preferences for co-owned items can conflict. Multi-party privacy management is therefore of crucial importance for users to appropriately reserve their privacy in social media.

GNSS Spoofing Detection Techniques by Cellular Network Cross-check in Smartphones

2019 ◽  
Author(s):  
Francesco Formaggio ◽  
Silvia Ceccato ◽  
Francesco Basana ◽  
Nicola Laurenti ◽  
Stefano Tomasin
Keyword(s):  
Cellular Network ◽  
Detection Techniques ◽  
Spoofing Detection

A Review on Heart Disease Detection Techniques

2017 ◽  
Vol 7 (7) ◽  
pp. 395
Author(s):  
. Anika ◽  
Navpreet Kaur
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Review Paper ◽  
Vascular Diseases ◽  
Disease Detection ◽  
Automated Classification ◽  
Feature Extraction Method ◽  
Detection Techniques ◽  
Cardio Vascular ◽  
Public Domain Software

The paper exhibits a formal audit on early detection of heart disease which are the major cause of death. Computational science has potential to detect disease in prior stages automatically. With this review paper we describe machine learning for disease detection. Machine learning is a method of data analysis that automates analytical model building.Various techniques develop to predict cardiac disease based on cases through MRI was developed. Automated classification using machine learning. Feature extraction method using Cell Profiler and GLCM. Cell Profiler a public domain software, freely available is flourished by the Broad Institute's Imaging Platform and Glcm is a statistical method of examining texture .Various techniques to detect cardio vascular diseases.

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Analysis of various Plant Disease detection Techniques

2019 ◽  
Vol 7 (7) ◽  
pp. 308-311
Author(s):  
Gazzal Thukral ◽  
Lal Chand
Keyword(s):  
Plant Disease ◽  
Disease Detection ◽  
Detection Techniques

A Theoretical Feature-wise Study of Malware Detection Techniques

2018 ◽  
Vol 6 (12) ◽  
pp. 879-887
Author(s):  
Om Prakash Samantray ◽  
Satya Narayana Tripathy ◽  
Susant Kumar Das
Keyword(s):  
Malware Detection ◽  
Detection Techniques
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