Application of Particle Swarm Optimization (PSO) Algorithm to Determine Dichlorvos Residue on the Surface of Navel Orange with Vis-NIR Spectroscopy

Xue, Long; Cai, Jianfei; Li, Jing; Liu, Muhua

doi:10.1016/j.proeng.2012.01.631

Cited by 34 publications

(16 citation statements)

References 9 publications

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“…The statistical performance of the PLSR models developed in this study was in agreement with the previous studies attempted to measure various pesticide residues in various matrixes such as diazinon in cucumber, pesticide level in oranges, chlorpyrifos in pesticide solutions and dichlofluanid fungicide on tomato surface …”

Section: Resultssupporting

confidence: 88%

“…It can also be used online in processing lines as a method that requires little or no sample preparation. Some research studies are available in the literature regarding the detection of pesticide residues on a variety of foodstuffs by NIRS, including pesticide residue determination in tomato, 22 green pepper, 23 longan fruit, 24 orange, 25 olive, 26 cucumber, 27 lettuce 28 and propolis samples. 29 These studies demonstrate the utility of NIRS to detect pesticide residues.…”

Section: Introductionmentioning

confidence: 99%

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Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

2020

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BACKGROUND In this study, an infrared‐based prediction method was developed for easy, fast and non‐destructive detection of pesticide residue levels measured by reference analysis in strawberry (Fragaria × ananassa Duch, cv. Albion) samples using near‐infrared spectroscopy and demonstrating its potential alternative or complementary use instead of traditional pesticide determination methods. Strawberries of Albion variety, which were supplied directly from greenhouses, were used as the study material. A total of 60 batch sample groups, each consisting of eight strawberries, was formed, and each group was treated with a commercial pesticide at different concentrations (26.7% boscalid + 6.7% pyraclostrobin) and varying residual levels were obtained in strawberry batches. The strawberry samples with pesticide residuals were used both to collect near‐infrared spectra and to determine reference pesticide levels, applying QuEChERS (quick, easy, cheap, rugged, safe) extraction, followed by liquid chromatographic–mass spectrometric analysis. RESULTS AND CONCLUSION Partial least squares regression (PLSR) models were developed for boscalid and pyraclostrobin active substances. During model development, the samples were randomly divided into two groups as calibration (n = 48) and validation (n = 12) sets. A calibration model was developed for each active substance, and then the models were validated using cross‐validation and external sets. Performance evaluation of the PLSR models was evaluated based on the residual predictive deviation (RPD) of each model. An RPD of 2.28 was obtained for boscalid, while it was 2.31 for pyraclostrobin. These results indicate that the developed models have reasonable predictive power. © 2019 Society of Chemical Industry

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Section: Resultssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

2020

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“…Typically, the detection of pesticides in complex matrices, such as agricultural products, involves a sample treatment using different methods such as solid-phase extraction, supercritical fluid extraction, microwave-assisted extraction, and accelerated solvent extraction [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…There are also some researches about detection or determination of pesticide residues in such products [1,2,[24][25][26][27]. All of these researches show the feasibility of using NIR spectroscopy for detection of pesticide residues.…”

Section: Introductionmentioning

confidence: 99%

Developing a Vis/NIR spectroscopic system for fast and non-destructive pesticide residue monitoring in agricultural product

Jamshidi

Mohajerani

Jamshidi³

2016

Measurement

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In this research, an optical system based on fibre optic Vis/NIR spectroscopy combined with chemometrics methods and software as a graphical user interface (GUI) was developed and presented for fast and non-destructive detection and determination of pesticide residues in agricultural products (a case study on diazinon in intact cucumbers). Vis/NIR spectra of cucumber samples without and with different concentrations of diazinon residue were analyzed at the range of 450-1000 nm. Partial least squares (PLS) regression models were developed based on chemical reference measurements and the spectral information of the samples after performing different pre-processing methods. Moreover, partial least squares-discriminant analysis (PLS-DA) models were developed based on different spectral pre-processing techniques to classify cucumbers with contents of diazinon below and above the maximum residue limits (MRL) as safe and unsafe samples, respectively. Finally, user-friendly software as a GUI was created based on the best PLS and PLS-DA models developed for prediction of diazinon contents in the samples and for classification of intact cucumbers by the absence/presence of diazinon residues, respectively. Evaluation of the system and software designed based on the best developed PLS and PLS-DA models indicated good performance for measuring and detection of

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“…Although biosensors can provide rapid detection with satisfactory accuracy, they cannot satisfy the meat industry's need because of their destructive nature. Meanwhile, optical technologies have received wide attention in the research community because of their rapid, nondestructive, real-time, and precise detection ability (Gomez et al, 2006;Jamshidi et al, 2012;Lu and Peng, 2006;Pan et al, 2015;Peng and Lu, 2007;Qin et al, 2013;Xue et al, 2012;Zhang et al, 2014). Consequently, optical technologies are gaining importance in industrial automation (Li et al, 2011a;Mehta and Burks, 2014;Tong et al, 2013).…”

mentioning

confidence: 99%

Optical Methods and Techniques for Meat Quality Inspection

Peng¹,

Dhakal²

2015

Trans.ASABE

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Application of Particle Swarm Optimization (PSO) Algorithm to Determine Dichlorvos Residue on the Surface of Navel Orange with Vis-NIR Spectroscopy

Cited by 34 publications

References 9 publications

Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

Developing a Vis/NIR spectroscopic system for fast and non-destructive pesticide residue monitoring in agricultural product

Optical Methods and Techniques for Meat Quality Inspection

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