Quantity and chemical composition of essential oil of peppermint (<i>Mentha × piperita</i> L.) leaves under different drying methods

Beigi, Mohsen; Torki-Harchegani, Mehdi; Pirbalouti, Abdollah Ghasemi

doi:10.1080/10942912.2018.1453839

Cited by 96 publications

(49 citation statements)

References 24 publications

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“…M . × piperita is reported for its therapeutic use in Chinese traditional medicine and its dried leaves were found in Egyptian pyramids (Beigi, Torki‐Harchegani, & Pirbalouti, ). In the Arab region and northern African, Peppermint common use as an aromas and flavoring ingredient in a famous drink “Touareg tea” (Singh et al, ; Singh, Pandey, & Tripathi, ).…”

Section: Traditional Uses and Ethnopharmacologymentioning

confidence: 99%

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Ethnomedicinal, phytochemical and pharmacological updates on Peppermint (Mentha × piperita L.)—A review

Mahendran

Rahman

2020

Phytotherapy Research

127

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Peppermint (Mentha × piperita L) is a perennial, glabrous and strongly scented herb belongs to the family Lamiaceae. It is cultivated in a temperate region of Europe, Asia, United States, India and Mediterranean countries due to their commercial value and distinct aroma. In addition to traditional food flavouring uses, M. × piperita is well recognized for their traditional use to treat fever, cold, digestive, anti‐viral, anti‐fungal and oral mucosa and throat inflammation. The scientific studies provide awareness on the use of M. × piperita for biological effects such as anti‐oxidant, anti‐microbial, anti‐viral, anti‐inflammatory, biopesticidal, larvicidal, anticancer, radioprotective effect, genotoxicity and anti‐diabetic activity have been ascribed. A wide spectrum of bioactive phytochemicals such as flavonoids, phenolics lignans and stilbenes and essential oils are expected to be responsible for the aroma effects. In this sense, this present review provides an extensive overview of the traditional medicinal, phytochemical and multiple biological activities of this “Peppermint.”

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Section: Traditional Uses and Ethnopharmacologymentioning

confidence: 99%

“…× piperita leaf is strong and contains large quantities of volatile oil (Beigi et al, ). Volatile oil peppermint is yellow transparent oil with a special menthol rich fragrance (Beigi et al, ). More than 300 compounds have been isolated and identified from peppermint.…”

Section: Therapeutically Active Phytochemical Constituents Present Inmentioning

confidence: 99%

Ethnomedicinal, phytochemical and pharmacological updates on Peppermint (Mentha × piperita L.)—A review

Mahendran

Rahman

2020

Phytotherapy Research

127

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“…In contrast, peppermint herbs fed at dosages of 50 g/kg DM to lactating Holstein cows (Hosoda et al, 2005) or at 200 g/d in steers (Ando et al, 2003) had no effect on the total concentration and molar proportions of SCFA. Assuming a menthol content of the applied peppermint supplements of ∼1% (Beigi et al, 2018), the menthol doses used in the latter in vivo studies were far lower than those used in vitro , however, they were yet higher than the doses that can be used economically and safely in routine practical feeding. Regarding safety, current EU regulations acknowledge that menthol supplementation is safe up to a concentration of 25 mg/kg complete feeding stuff and require detailed labeling where this concentration is exceeded (The European Commission, 2018).…”

Section: Introductionmentioning

confidence: 99%

Dietary Bioactive Lipid Compounds Rich in Menthol Alter Interactions Among Members of Ruminal Microbiota in Sheep

Patra

Park

Braun³

et al. 2019

Front. Microbiol.

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This study aimed to investigate the effects of two practically relevant doses of menthol-rich plant bioactive lipid compounds (PBLC) on fermentation, microbial community composition, and their interactions in sheep rumen. Twenty-four growing Suffolk sheep were divided into three treatments and were fed hay ad libitum plus 600 g/d of concentrate containing no PBLC (Control) or PBLC at low dose (80 mg/d; PBLC-L) or high dose (160 mg/d; PBLC-H). After 4 weeks on the diets, samples of ruminal digesta were collected and analyzed for short-chain fatty acid (SCFA), ammonia, and microbiota; microbiota being analyzed in the solid and the liquid digesta fractions separately. Ruminal SCFA and ammonia concentrations were not affected by the PBLC treatments. The microbiota in the solid fraction was more diverse than that in the liquid fraction, and the relative abundance of most taxa differed between these two fractions. In the solid fraction, phylogenetic diversity increased linearly with increased PBLC doses, whereas evenness (lowest in PBLC-L) and Simpson diversity index (greatest in PBLC-H) changed quadratically. In the liquid fraction, however, the PBLC supplementation did not affect any of the microbial diversity measurements. Among phyla, Chloroflexi (highest in PBLC-L) and unclassified_bacteria (lowest in PBLC-L) were altered quadratically by PBLC. Lachnospiraceae, Bacteroidaceae (increased linearly), BS11 (increased in PBLC-L), Christensenellaceae (decreased in PBLC treatments), and Porphyromonadaceae (increased in PBLC treatments) were affected at the family level. Among genera, Butyrivibrio increased linearly in the solid fraction, YRC22 increased linearly in the liquid fraction, whereas Paludibacter increased and BF311 increased linearly with increasing doses of PBLC in both fractions. The PBLC treatments also lowered methanogens within the classes Thermoplasmata and Euryarchaeota. Correlation network analysis revealed positive and negative correlations among many microbial taxa. Differential network analysis showed that PBLC supplementation changed the correlation between some microbial taxa and SCFA. The majority of the predicted functional features were different between the solid and the liquid digesta fractions, whereas the PBLC treatments altered few of the predicted functional gene categories. Overall, dietary PBLC treatments had little influence on the ruminal fermentation and microbiota but affected the associations among some microbial taxa and SCFA.

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“…Some of the convective drying methods like hot air and fluidized-bed drying are identified because of its monotonic and faster drying process and higher thermal efficiency as compared to traditional method, because the transfer of heat and mass is raised in the fluidizedbed drying when the sample suspended in the air by fluidization because of increase in sample surface area (Kumar & Karim, 2019). To improve MCD drying, several research have been performed to evaluate the effects of different levels of drying temperature, microwave power, and air velocity (Ashtiani, Sturm, & Nasirahmadi, 2018;Beigi, Torki-Harchegani, & Pirbalouti, 2018;Darvishi, Khoshtaghaza, Najafi, & Nargesi, 2013;Junqueira, Correa, & Ernesto, 2017;Omari, Behroozi-Khazaei, & Sharifian, 2018).…”

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confidence: 99%

Use of artificial intelligence for the estimation of effective moisture diffusivity, specific energy consumption, color and shrinkage in quince drying

Taghinezhad

Kaveh

Jahanbakhshi

et al. 2020

J Food Process Engineering

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In the study, drying process of quince fruit was accomplished in a microwave‐convective dryer (MCD). The experiments were carried out at microwave power levels of 100, 200, and 300 W, air temperatures of 40, 55, and 70°C, and air velocities of 0.5, 1, and 1.5 m/s. Nevertheless, three artificial intelligence techniques consisted of artificial neural networks (ANNs), particle swarm optimizer (PSO), and grey wolf optimizer (GWO) were evaluated to predict the parameters of Deff, SEC, ΔE, and Sb. In the evaluation the data by ANNs, input parameters of networks consisted the values of air temperature, microwave power, and air velocity. According to the results, the maximum values of effective moisture diffusivity ( Deff) and specific energy consumption (SEC) were 1.71 × 10−9 m2/s and 126.07 kWh/kg, respectively. In addition, minimum values of total change in color (ΔE) and shrinkage ( Sb) of quince achieved 10.85 and 33.85%, respectively. For predicting all parameters, three models used in the study represented good predictive capability with R2 > 0.97. The obtained results showed that the GWO model had better predictive performance than the ANN and PSO models. Practical Application Drying food and agricultural products by application of microwave‐hot air blend dryers can be a good alternative to hot air and microwave dryers. Microwave energy infiltrates the product and facilitates heat release from the product and thus reduces drying time compared to single dryers. The main aim of applying such different models, mathematical simulation or modeling in the drying technology of agricultural products is to transform physical qualities and their interactions into numerical quantities and mathematical relationships.

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Quantity and chemical composition of essential oil of peppermint (Mentha × piperita L.) leaves under different drying methods

Abstract: View related articles View Crossmark data Citing articles: 8 View citing articles Quantity and chemical composition of essential oil of peppermint (Mentha × piperita L.) leaves under different drying methods

Cited by 96 publications

References 24 publications

Ethnomedicinal, phytochemical and pharmacological updates on Peppermint (Mentha × piperita L.)—A review

Ethnomedicinal, phytochemical and pharmacological updates on Peppermint (Mentha × piperita L.)—A review

Dietary Bioactive Lipid Compounds Rich in Menthol Alter Interactions Among Members of Ruminal Microbiota in Sheep

Use of artificial intelligence for the estimation of effective moisture diffusivity, specific energy consumption, color and shrinkage in quince drying

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