Prediction of hypericin content in Hypericum perforatum L. in different ecological habitat using artificial neural networks

Saffariha, Maryam; Jahani, Ali; Jahani, Reza; Latif, Sajid

doi:10.1186/s13007-021-00710-z

Cited by 30 publications

(10 citation statements)

References 38 publications

(43 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this process, BP adjusts the weights of neurons and layers based on the output of the MLP. The weights are optimized until the most appropriate weights are achieved and the MLP network learning process will be ended [27 , 28] .…”

Section: Methods Detailsmentioning

confidence: 99%

A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach

Aboufazeli

Jahani²,

Farahpour

2021

MethodsX

Self Cite

View full text Add to dashboard Cite

This work presents a simplified method for the application of the Multi-Layer Perceptron (MLP) model that aims to predict the aesthetic quality of the landscape designed by water and plants in different forms and volume. The MLP was prepared by (Rosenblat) in the field of computer science, followed by the application of a MLP in landscape aesthetic quality prediction proposed by (Jahani). In the method of this research, the structure of MLP was structured for aesthetic quality prediction of plants and water in urban park landscapes. The accuracies of designed MLP structures were tested to achieve the most accurate one in aesthetic quality prediction. This method creates an environmental decision support system tool for landscape designers, and it is a platform to predict the quality of environment. In practice, the designed environmental decision support system tool is applied by landscape managers to predict the aesthetic quality of landscape in designing new urban parks. Applies Multi-Layer Perceptron method in landscape assessment. Accurate MATLAB extension for landscape aesthetic evaluation. Defined criteria for aesthetic value of landscape.

show abstract

Section: Methods Detailsmentioning

confidence: 99%

A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach

Aboufazeli

Jahani²,

Farahpour

2021

MethodsX

Self Cite

View full text Add to dashboard Cite

show abstract

“…Based on the morphometric leaf parameters of 12 Hypericum species, a cubic degree polynomial regression function was proposed for estimation of the biosynthetic capacity of Hypericum shoot cultures ( Kimáková et al., 2018 ). Furthermore, Saffariha et al. (2021) designed several models to predict changes of hypericin content in relation to ecological and phenological factors.…”

Section: Phenotyping Of Secondary Metabolism In Response To Biotic/ab...mentioning

confidence: 99%

Does phenotyping of Hypericum secondary metabolism reveal a tolerance to biotic/abiotic stressors?

et al. 2022

View full text Add to dashboard Cite

In this review we summarize the current knowledge about the changes in Hypericum secondary metabolism induced by biotic/abiotic stressors. It is known that the extreme environmental conditions activate signaling pathways leading to triggering of enzymatic and non-enzymatic defense systems, which stimulate production of secondary metabolites with antioxidant and protective effects. Due to several groups of bioactive compounds including naphthodianthrones, acylphloroglucinols, flavonoids, and phenylpropanes, the world-wide Hypericum perforatum represents a high-value medicinal crop of Hypericum genus, which belongs to the most diverse genera within flowering plants. The summary of the up-to-date knowledge reveals a relationship between the level of defense-related phenolic compounds and interspecific differences in the stress tolerance. The chlorogenic acid, and flavonoids, namely the amentoflavone, quercetin or kaempferol glycosides have been reported as the most defense-related metabolites associated with plant tolerance against stressful environment including temperature, light, and drought, in association with the biotic stimuli resulting from plant-microbe interactions. As an example, the species-specific cold-induced phenolics profiles of 10 Hypericum representatives of different provenances cultured in vitro are illustrated in the case-study. Principal component analysis revealed a relationship between the level of defense-related phenolic compounds and interspecific differences in the stress tolerance indicating a link between the provenance of Hypericum species and inherent mechanisms of cold tolerance. The underlying metabolome alterations along with the changes in the activities of ROS-scavenging enzymes, and non-enzymatic physiological markers are discussed. Given these data it can be anticipated that some Hypericum species native to divergent habitats, with interesting high-value secondary metabolite composition and predicted high tolerance to biotic/abiotic stresses would attract the attention as valuable sources of bioactive compounds for many medicinal purposes.

show abstract

“… 2020 ), evaluation of the effect of human activities on vegetation (Jahani and Saffariha 2021 ), prediction of ecological varieties conditional on habitat (Saffariha et al. 2021 ), influence of factors on the perception of the landscape (Jahani et al. 2022 ), and uncertainty quantification for water resources applications (Ciriello et al.…”

Section: Introductionmentioning

confidence: 99%

Bayesian modeling for pro-environmental behavior data: sorting and selecting relevant variables

Reveco-Quiroz

Sandoval-Díaz

Álvares

2022

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

Pro-environmental behaviors towards climate change can be measured and evaluated in different fields. Typically, surveys are the standard tool for extracting personal information regarding this phenomenon. However, statistical modeling for these surveys is not straightforward, as the response variable is often not explicit. Hence, we propose a set of methodological procedures to deal with pro-environmental behavior data. First, validity evidence through a factorial analysis. Second, indexes are created from factor scores, where one of the latent factors summarizes a target variable. Third, a Beta regression is used to model the index of interest. Fourth, the inferential process is performed from a Bayesian perspective, in which posterior probabilities are used to sort and select the relevant variables. Finally, suitable models are obtained, and conclusions can be drawn from them. As a motivation, we used data from two Chilean surveys to illustrate our methodology as well as interpret and discuss the results.

show abstract

Prediction of hypericin content in Hypericum perforatum L. in different ecological habitat using artificial neural networks

Cited by 30 publications

References 38 publications

A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach

A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach

Does phenotyping of Hypericum secondary metabolism reveal a tolerance to biotic/abiotic stressors?

Bayesian modeling for pro-environmental behavior data: sorting and selecting relevant variables

Contact Info

Product

Resources

About