Summer Savory (Satureja hortensis L.) Oils

Hassanzadeh, M.; Najaran, Zahra Tayarani; Nasery, Maryam; Emami, Seyed Ahmad

doi:10.1016/b978-0-12-416641-7.00086-9

Cited by 10 publications

(4 citation statements)

References 13 publications

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“…Several review papers from the last decade present other activities of S. hortensis natural products such as antiviral properties (evaluated against HIV virus) [ 6 , 64 , 65 ], inhibitory effects of methanol extracts on adhesion of the activated human platelet to laminin-coated plates [ 3 , 30 ], antispasmodic and diuretic [ 27 ], anti-asthenic, anti-dysenteric, bronchidilatator and carminative [ 66 ], expectorant [ 67 ], emmenagogue, aphrodisiac and resolutive [ 68 ] or for stomach pain [ 69 ].…”

Section: Biological Activities Of Satureja Hortensis mentioning

confidence: 99%

Phytochemical Profile and Biological Activities of Satureja hortensis L.: A Review of the Last Decade

et al. 2018

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Satureja hortensis L. (summer savory) is an annual herbaceous crop, native to Europe and in our days spread and used all over the world. Although its use as spice and medicinal plant is known since ancient times, peer-reviewed studies presenting the scientific data are scarce. The natural products obtained from summer savory (extracts and essential oil) are dominated by polyphenols and flavonoids, responsible for their antioxidant, antimicrobial, antiparasitic, pesticidal, anti-inflammatory, analgesic, hepatoprotective and anticancer properties, among others. The current study presents the progress made in the last decade regarding the potential applications of summer savory, being the first review study focused on S. hortensis, in the same time suggesting future research opportunities, as they appear from the properties of other Satureja species. The available data presenting the properties of summer savory represents a scientific support for application in industry, for developing “clean label” food products.

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Section: Biological Activities Of Satureja Hortensis mentioning

confidence: 99%

Phytochemical Profile and Biological Activities of Satureja hortensis L.: A Review of the Last Decade

et al. 2018

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“…SHE is derived from S. hortensis (synonym Satureja postii Arzn. ), an aromatic plant from the Lamiaceae family [159]. The authors performed these simulations to understand the adsorption behaviour of Zn cation complexes with pigments on the surface of an Fe substrate.…”

Section: Molecular Dynamics Methods To Study Metal-pigment Interactionsmentioning

confidence: 99%

An Update in Computational Methods for Environmental Monitoring: Theoretical Evaluation of the Molecular and Electronic Structures of Natural Pigment–Metal Complexes

Maranata,

Megantara,

Hasanah

2024

Molecules

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Metals are beneficial to life, but the presence of these elements in excessive amounts can harm both organisms and the environment; therefore, detecting the presence of metals is essential. Currently, metal detection methods employ powerful instrumental techniques that require a lot of time and money. Hence, the development of efficient and effective metal indicators is essential. Several synthetic metal detectors have been made, but due to their risk of harm, the use of natural pigments is considered a potential alternative. Experiments are needed for their development, but they are expensive and time-consuming. This review explores various computational methods and approaches that can be used to investigate metal–pigment interactions because choosing the right methods and approaches will affect the reliability of the results. The results show that quantum mechanical methods (ab initio, density functional theory, and semiempirical approaches) and molecular dynamics simulations have been used. Among the available methods, the density functional theory approach with the B3LYP functional and the LANL2DZ ECP and basis set is the most promising combination due to its good accuracy and cost-effectiveness. Various experimental studies were also in good agreement with the results of computational methods. However, deeper analysis still needs to be carried out to find the best combination of functions and basis sets.

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“…Food contamination is one of the biggest issues among public health problems. Moreover, the spoilage and deterioration of food quality during storage is another challenge for both the food industry and environmental perspectives [22,23]. According to the world health organization (WHO) fact sheet, every year almost 600 million people fall ill after eating contaminated food.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Enabled Food Contamination Detection Using RFID and Internet of Things System

Sharif

Abbasi

Arshad

et al. 2021

JSAN

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This paper presents an approach based on radio frequency identification (RFID) and machine learning for contamination sensing of food items and drinks such as soft drinks, alcohol, baby formula milk, etc. We employ sticker-type inkjet printed ultra-high-frequency (UHF) RFID tags for contamination sensing experimentation. The RFID tag antenna was mounted on pure as well as contaminated food products with known contaminant quantity. The received signal strength indicator (RSSI), as well as the phase of the backscattered signal from the RFID tag mounted on the food item, are measured using the Tagformance Pro setup. We used a machine-learning algorithm XGBoost for further training of the model and improving the accuracy of sensing, which is about 90%. Therefore, this research study paves a way for ubiquitous contamination/content sensing using RFID and machine learning technologies that can enlighten their users about the health concerns and safety of their food.

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Summer Savory (Satureja hortensis L.) Oils

Cited by 10 publications

References 13 publications

Phytochemical Profile and Biological Activities of Satureja hortensis L.: A Review of the Last Decade

Phytochemical Profile and Biological Activities of Satureja hortensis L.: A Review of the Last Decade

An Update in Computational Methods for Environmental Monitoring: Theoretical Evaluation of the Molecular and Electronic Structures of Natural Pigment–Metal Complexes

Machine Learning Enabled Food Contamination Detection Using RFID and Internet of Things System

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