<i>Risk estimation of pesticide residues in apple in Shanxi province in 2017</i>

2018 ◽  
Author(s):  
Xinxin / Jin ◽  
Wenshen / Jia ◽  
Ligang / Pan ◽  
An / Li ◽  
Gang / Liang ◽  
...  
Keyword(s):  
Pesticide Residues ◽  
Risk Estimation ◽  
Shanxi Province ◽  
Estimation Of Pesticide

Frequency and severity estimation of pesticide residues from organically cultivated olives and olive tree leafs in Greece, during 2008

2010 ◽  
Vol 196 ◽  
pp. S336 ◽  
Author(s):  
I. Tsakiris ◽  
C. Favas ◽  
A. Tsatsakis ◽  
A. Alegkakis ◽  
P. Mitliagka ◽  
...  
Keyword(s):  
Pesticide Residues ◽  
Olive Tree ◽  
Severity Estimation ◽  
Estimation Of Pesticide

Occurrence and estimation of pesticide residues in edible minor crops in southeastern Poland in 2013–2014

2016 ◽  
Vol 188 (7) ◽  
Author(s):  
Magdalena Podbielska ◽  
Ewa Szpyrka ◽  
Aneta Matyaszek ◽  
Magdalena Słowik-Borowiec ◽  
Julian Rupar ◽  
...  
Keyword(s):  
Pesticide Residues ◽  
Minor Crops ◽  
Estimation Of Pesticide

scholarly journals Estimation of Pesticide Residues in Selected Products of Plant Origin from Poland with the Use of the HPLC-MS/MS Technique

Agriculture ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 192 ◽  
Author(s):  
Grażyna Kowalska ◽  
Urszula Pankiewicz ◽  
Radosław Kowalski
Keyword(s):  
Pesticide Residues ◽  
High Performance ◽  
Mass Spectrometry Analysis ◽  
Tandem Mass ◽  
Plant Origin ◽  
Spectrometry Analysis ◽  
Tandem Mass Spectrometry Analysis ◽  
Maximum Residue Levels ◽  
Residue Levels ◽  
Estimation Of Pesticide

The purpose of this work was to compare the content of pesticide residues (250) in unprocessed plant products from farms situated in the eastern part of Poland. The content of pesticide residues in the analysed samples was assayed with the use of the QuEChERS (Quick Easy Cheap Effective Rugged Safe) method combined with HPLC-MS/MS (high performance liquid chromatography with tandem mass spectrometry) analysis. The analyses revealed that among 160 analysed samples, pesticide residues were detected in 83 samples (approximately 52%), while in 77 samples (approximately 48%), no presence of those substances was noted. In all the samples in which the presence of the sought compounds was identified, their levels did not exceed the Maximum Residue Levels (MRL). The most often identified ones were azoxystrobin—detected in 36 samples (22.5%), linuron—assayed in 33 samples (20.6%), chlorpyrifos and carbendazim—each detected in 13 samples (8.1%), metalaxyl and metalaxyl M—in 11 samples (6.9%), and acetamiprid—in 7 samples (4.4%).

scholarly journals Estimation of Pesticide Residues on Leafy Vegetables Using a Developed Handheld Spectrometer

2021 ◽  
Vol 12 (6) ◽  
pp. 8163-8173
Keyword(s):  
Pesticide Residues ◽  
Agricultural Products ◽  
Leafy Vegetables ◽  
Stepwise Multiple Linear Regression ◽  
Detection Model ◽  
Vegetable Samples ◽  
Reference Measurements ◽  
Non Destructive ◽  
Oriental Mustard ◽  
Estimation Of Pesticide

In this study, a rapid and non-destructive detection model for pesticide residues on leafy vegetables was presented using a developed portable spectrometer. VIS/NIR spectra of three vegetable samples, including lettuce, oriental mustard, and bok choy, were analyzed at the range of 380 – 840 nm. Stepwise multiple linear regression (SMLR) models were developed based on chemical reference measurements and the spectral information of the leaf samples after performing the pre-processing method. Furthermore, a data acquisition interface was developed by Matlab GUI. Results of SMLR procedure indicated good performance for detection of indoxacarb and chlorantraniliprole with R2 ≥ 0.90. A fairly good model (0.90 > R2 > 0.80) was obtained for carbendazim in lettuce, whereas a poor model was found for emamectin-benzoate with R2 ≤ 0.80. It was concluded that pesticide residues on leafy vegetables could be predicted using our developed handheld spectrometer. It can also be generalized for the prediction of other pesticide components in agricultural products.

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