Improvement of postharvest quality, secondary metabolites, antioxidant activity and quality attributes of Prunus persica L. subjected to solar drying and slice thickness

El-Beltagi, Hossam S.; Khan, Ayesha; Shah, Syed Tanveer; Basit, Abdul; Sajid, Muhammad; Hanif, Muhammad; Mohamed, Heba I.

doi:10.1016/j.sjbs.2023.103866

Saudi Journal of Biological Sciences

2023

DOI: 10.1016/j.sjbs.2023.103866

|View full text |Cite

Improvement of postharvest quality, secondary metabolites, antioxidant activity and quality attributes of Prunus persica L. subjected to solar drying and slice thickness

Hossam S. El-Beltagi,

Ayesha Khan,

Syed Tanveer Shah

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 124 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Enhancing the Quality and Fruit Yield of Sweet Cherry (Prunus Avium) Cultivars by Foliar Application of Boron

Sajid,

Basit,

Shah

et al. 2024

Applied Fruit Science

View full text Add to dashboard Cite

Enhancing the Quality and Fruit Yield of Sweet Cherry (Prunus Avium) Cultivars by Foliar Application of Boron

Sajid,

Basit,

Shah

et al. 2024

Applied Fruit Science

View full text Add to dashboard Cite

Zein-based nisin-loaded electrospun nanofibers as active packaging mats for control of Listeria monocytogenes on peach

Khalil,

ElLeithy,

Ayoup

et al. 2024

Food Chemistry

View full text Add to dashboard Cite

Artificial Neural Network Modeling Techniques for Drying Kinetics of Citrus medica Fruit during the Freeze-Drying Process

Topal,

Şahin,

Vela

2024

Processes

View full text Add to dashboard Cite

The main objective of this study is to analyze the drying kinetics of Citrus medica by using the freeze-drying method at various thicknesses (3, 5, and 7 mm) and cabin pressures (0.008, 0.010, and 0.012 mbar). Additionally, the study aims to evaluate the efficacy of an artificial neural network (ANN) in estimating crucial parameters like dimensionless mass loss ratio (MR), moisture content, and drying rate. Feedforward multilayer perceptron (MLP) neural network architecture was employed to model the freeze-drying process of Citrus medica. The ANN architecture was trained using a dataset covering various drying conditions and product characteristics. The training process, including hyperparameter optimization, is detailed and the performance of the ANN is evaluated using robust metrics such as RMSE and R². As a result of comparing the experimental MR with the predicted MR of the ANN modeling created by considering various product thicknesses and cabin pressures, the R² was found to be 0.998 and the RMSE was 0.010574. Additionally, color change, water activity, and effective moisture diffusivity were examined in this study. As a result of the experiments, the color change in freeze-dried Citrus medica fruits was between 6.9 ± 0.2 and 21.0 ± 0.6, water activity was between 0.4086 ± 0.0104 and 0.5925 ± 0.0064, effective moisture diffusivity was between 4.19 × and 21.4 × , respectively. In freeze-drying experiments conducted at various cabin pressures, it was observed that increasing the slice thickness of Citrus medica fruit resulted in longer drying times, higher water activity, greater color changes, and increased effective moisture diffusivity. By applying the experimental data to mathematical models and an ANN, the optimal process conditions were determined. The results of this study indicate that ANNs can potentially be applied to characterize the freeze-drying process of Citrus medica.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Improvement of postharvest quality, secondary metabolites, antioxidant activity and quality attributes of Prunus persica L. subjected to solar drying and slice thickness

Cited by 3 publications

References 124 publications

Enhancing the Quality and Fruit Yield of Sweet Cherry (Prunus Avium) Cultivars by Foliar Application of Boron

Enhancing the Quality and Fruit Yield of Sweet Cherry (Prunus Avium) Cultivars by Foliar Application of Boron

Zein-based nisin-loaded electrospun nanofibers as active packaging mats for control of Listeria monocytogenes on peach

Artificial Neural Network Modeling Techniques for Drying Kinetics of Citrus medica Fruit during the Freeze-Drying Process

Contact Info

Product

Resources

About