Indicative extent of humic and fulvic acids in soils determined by electronic nose

Lavanya, S.; Deepika, B; Narayanan, Shruthi; Murthy, V. Krishna; Uma, M.V.

doi:10.1016/j.compag.2017.05.025

Cited by 13 publications

(7 citation statements)

References 19 publications

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“…The results indicated that this procedure enables to detect similar samples (Rodríguez, Barletta, Wilderjans, & Bernik, 2014). Similar research were conducted by (Shen et al, 2016) for orange juices; (Hong, Wang, & Qi, 2014) for tomato juices; (Lavanya, Deepika, Narayanan, Murthy, & Uma, 2017) for detection of hemic and folic acids in soils; (Liang et al, 2017) and for bacteria detection and soil gas emissions (Pineda & P erez, 2017).…”

Section: Introductionsupporting

confidence: 65%

Using an E‐nose machine for detection the adulteration of margarine in cow ghee

Ayari

Mirzaee‐Ghaleh

Rabbani

et al. 2018

J Food Process Engineering

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Diagnosis of adulteration in cow ghee is one of the key concerns of recent years. In this study, the aroma fingerprints of cow ghee were detected. For this purpose, an electronic nose system was developed and its ability for detection of different amounts of margarine mixed with pure cow ghee (10, 20, 30, 40, and 50% levels) was investigated. The system was equipped with eight sensors (MOS type), that each of them reacts to specific volatile compounds in the samples. The features of the signals were considered for data analysis. In this research, principal components analysis (PCA) and artificial neural networks (ANN) methods were used for data analyzing. According to the results, the PCA analysis explained 98% of the variance in the data set. Also, ANN analysis identified 85.6 and 97.2% of pure cow ghee from the adulteration ones when samples were classified in 7 and 2 classes, respectively. Practical applications Diagnosis and estimation of adulteration in cow ghee is one of the key concerns for consumers. Electronic nose is a new method that can be used for detection of products quality. We show that electronic nose system is a valuable tool for detection of margarine as a one of common adulteration in cow ghee.

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Section: Introductionsupporting

confidence: 65%

Using an E‐nose machine for detection the adulteration of margarine in cow ghee

Ayari

Mirzaee‐Ghaleh

Rabbani

et al. 2018

J Food Process Engineering

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show abstract

“…The soil samples were slowly dried out naturally since the beginning of the measurements. According to Lavanya et al [ 32 ], the moist soil samples are characterized by a more intensive smell profile than the dry samples. After spitting fuel into the soil samples, the concentration of pollutant fumes in the gaseous phase increased, which was found during the subsequent measurement session.…”

Section: Resultsmentioning

confidence: 99%

“…E-nose systems are not only suitable for the detection of contaminant compounds. The results obtained by Lavanya et al support the utility of the device as a screening tool for the presence and also content of humic and fulvic acids, which are the fertility components of soil [ 32 ]. Pobkrut and Kerdcharoen proposed an interesting application of an e-nose [ 33 ].…”

Section: Introductionmentioning

confidence: 87%

Evaluation of Hydrocarbon Soil Pollution Using E-Nose

Bieganowski

Józefaciuk

Bandura

et al. 2018

Sensors

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The possibility of detecting low levels of soil pollution by petroleum fuel using an electronic nose (e-nose) was studied. An attempt to distinguish between pollution caused by petrol and diesel oil, and its relation to the time elapsed since the pollution event was simultaneously performed. Ten arable soils, belonging to various soil groups from the World Reference Base (WRB), were investigated. The measurements were performed on soils that were moistened to field capacity, polluted separately with both hydrocarbons, and then allowed to dry slowly over a period of 180 days. The volatile fingerprints differed throughout the course of the experiment, and, by its end, they were similar to those of the unpolluted soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that the e-nose results could be used to detect soil contamination and distinguish between pollutants and contamination levels.

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“…[11] In the recent years, different research have been done about using of e-nose in the field of food control such as meat [12,13] , fish [14] , milk [15] , oils [16,17] , Saffron [18,19] , Chinese pecan [20] , honey [21] , rapeseed [22] and orange juice [23] and soil. [24] Several methods have been developed for the detection of the adulteration in cow ghee. These methods were mostly based on chemical parameters like the fatty acid composition and the physicochemical analysis.…”

Section: Introductionmentioning

confidence: 99%

Detection of the adulteration in pure cow ghee by electronic nose method (case study: sunflower oil and cow body fat)

Ayari

Mirzaee‐Ghaleh

Rabbani

et al. 2018

International Journal of Food Properties

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Cow ghee is very used in some regions of Iran, such as Kermanshah province. Cow ghee is a natural source that contains high-quality nutrients which are needed for the human body. Adulteration in dairy products is not only a serious threat to human health but also it causes economic losses. Diagnosis of foodstuff cheating and its estimation is one of the key concerns in recent years. The aim of this study was the detection of the adulteration in cow ghee by olfactory machine system. Therefore, an electronic nose system was used for the different levels of sunflower oil and cow body fat mixed with pure cow ghee (10%, 20%, 30%, 40%, and 50%). The principal components analysis (PCA) and artificial neural networks (ANNs) methods were used to achieve this goal. Based on the results, the accuracy of the principal components analysis of sunflower oil and cow body fat were 96% and 97% of the data variance, respectively. According to the results, artificial neural networks identified the adulteration with sunflower oil and cow body fat with an accuracy of 91.3% and 82.5%, respectively.

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Indicative extent of humic and fulvic acids in soils determined by electronic nose

Cited by 13 publications

References 19 publications

Using an E‐nose machine for detection the adulteration of margarine in cow ghee

Using an E‐nose machine for detection the adulteration of margarine in cow ghee

Evaluation of Hydrocarbon Soil Pollution Using E-Nose

Detection of the adulteration in pure cow ghee by electronic nose method (case study: sunflower oil and cow body fat)

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