Analysis of a cost-effective remote sensing system for fruit monitoring

Yoiyod, P.; Krairiksh, M.

doi:10.1109/aps.2013.6711203

Cited by 8 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2013, a study was conducted by Yoiyod and Kaririskh [93] on the ripeness monitoring of mangos through a cost-effective remote sensing system. The dielectric properties of the peel and pulp of mango fruit were measured at different maturity stages.…”

Section: Dielectric Application Datamentioning

confidence: 99%

See 1 more Smart Citation

Fruit and Vegetable Quality Assessment via Dielectric Sensing

Khaled

Novas

Gázquez

et al. 2015

Sensors

View full text Add to dashboard Cite

The demand for improved food quality has been accompanied by a technological boost. This fact enhances the possibility of improving the quality of horticultural products, leading towards healthier consumption of fruits and vegetables. A better electrical characterization of the dielectric properties of fruits and vegetables is required for this purpose. Moreover, a focused study of dielectric spectroscopy and advanced dielectric sensing is a highly interesting topic. This review explains the dielectric property basics and classifies the dielectric spectroscopy measurement techniques. It comprehensively and chronologically covers the dielectric experiments explored for fruits and vegetables, along with their appropriate sensing instrumentation, analytical modelling methods and conclusions. An in-depth definition of dielectric spectroscopy and its usefulness in the electric characterization of food materials is presented, along with the various sensor techniques used for dielectric measurements. The collective data are tabulated in a summary of the dielectric findings in horticultural field investigations, which will facilitate more advanced and focused explorations in the future.

show abstract

Section: Dielectric Application Datamentioning

confidence: 99%

“…A frequency ranging between 6 and 18 GHz is considered to be the most suitable operating frequency. The results show that a significant difference in the reflection coefficient exists between ripe and unripe mangos [93]. …”

Section: Dielectric Application Datamentioning

confidence: 99%

Fruit and Vegetable Quality Assessment via Dielectric Sensing

Khaled

Novas

Gázquez

et al. 2015

Sensors

View full text Add to dashboard Cite

show abstract

“…Coronel, Simunovic, Sandeep, and Kumar () conducted experiment on the avocado products to measure the dielectric properties of food using a continuous flow microwave system at 915 MHz and in the temperature range of 10 to 90℃. Yoiyod and Krairiksh () studied the dielectric properties of the peel and pulp of mangos at a frequency ranging between 6 and 18 GHz. Guo et al () measured the dielectric properties of fresh fruit to study their sense of quality.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive detection for moisture content in green tea based on dielectric properties and VISSA‐GWO‐SVR algorithm

Sun

Tian

et al. 2020

J Food Process Preserv

View full text Add to dashboard Cite

Moisture content was an important indicator to measure quality of green tea. In order to detect moisture content in green tea effectively and accurately, nondestructive detection for moisture content in green tea based on dielectric technology was proposed in this paper. Inductance-capacitance-resistance (LCR) measuring instrument and coaxial-line cylinder capacitor were used to collect dielectric data. The characteristic frequency points were extracted by successive projection algorithm (SPA) and variable iterative space shrinkage approach (VISSA). Support vector regression (SVR) was used to establish prediction models based on full frequency points and characteristic frequency points. The model results demonstrated that VISSA-SVR model based on dielectric loss factor ε″ performed best among all the prediction models, but the prediction accuracy was not enough, so the gray wolf optimization (GWO) algorithm was introduced to optimize the parameters (c and g) in SVR model. Furthermore, the best prediction performances for detecting moisture content in green tea was obtained, with the determination coefficient and root mean square errors (RMSEs) for prediction were 0.9695 and 0.0602, respectively. Therefore, dielectric technology combined with VISSA-GWO-SVR model is feasible for nondestructive determination of the moisture content in tea, which will provide a promising tool for the moisture content detection of other agricultural products. Practical applicationsWell understanding moisture content in tea is great importance. The practical application of this paper is to develop a novel method for moisture content detection in tea using dielectric technology. Compared with traditional methods, dielectric technology can be used to detect moisture content in tea nondestructively and accurately. Characteristic frequency selection algorithms are used to remove the redundant information in the data, and optimization algorithm is used to improve the performance of the model. Thus, dielectric technology combined with the optimal model is considered the most promising method for detecting the moisture content in green tea.How to cite this article: Sun J, Tian Y, Wu X, et al.Nondestructive detection for moisture content in green tea based on dielectric properties and VISSA-GWO-SVR algorithm. J Food Process Preserv. 2020;44:e14421.

show abstract