Determination of bruise preventing capacity of the cushioning material in persimmon fruit under pendulum impact test

Cevher, Elçin Yeşiloğlu

doi:10.1111/jfpe.14162

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…As a result, the higher bioyield stress of the sample leads to more resistance of the fruit to the bruise phenomenon (An et al, 2022). The results physiological differences of the samples (Hou et al, 2023;Yes ¸ilo glu Cevher, 2022). As mentioned earlier, the purpose of using SEM to calculate the BV and susceptibility was to reduce the error.…”

Section: Bruise Susceptibilitymentioning

confidence: 85%

“…The results revealed the BV of MAP + DBD (5 min) > MAP + DBD (10 min) > MAP + DBD (15 min) > MAP. According to the researchers' reports, errors in the calculation of BV happened many times due to the physiological differences of the samples (Hou et al, 2023; Yeşiloğlu Cevher, 2022). As mentioned earlier, the purpose of using SEM to calculate the BV and susceptibility was to reduce the error.…”

Section: Resultsmentioning

confidence: 99%

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Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Rashvand

Altieri

Abbaszadeh

et al. 2023

J Food Process Engineering

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In this study, the fresh and in‐packaged apricots were treated with dielectric barrier discharge (DBD) cold plasma for 5, 10, and 15 min and then stored at 21°C for 12 days to simulate the shelf life of the apricot. The effects of DBD treatment on the main quality attributes of apricot such as physicochemical traits (mass loss, pH, soluble solid content, titratable acidity, and skin color), mechanical properties (Young's modulus, tangent modulus, and bioyield stress), in‐package gas composition and ethylene production were investigated during the storage time. In addition, the bruise susceptibility (BS) of control and treated samples at the microscale was evaluated by using pendulum test and scanning electron microscopy. The results of the mass loss, pH, soluble solid content, titratable acidity, skin color, and bioyield stress have been applied for input parameters of the developed artificial neural network (ANN) and support vector regression (SVR) models to predict the CO2 and ethylene production. The statistical data showed the performance of the developed ANN to predict the CO2 (R2 = 0.983, root mean square error [RMSE] = 0.486) and ethylene production (R2 = 0.933, RMSE = 5.376) was superior to SVR (CO2: R2 = 0.894, RMSE = 6.077 and ethylene: R2 = 0.759, RMSE = 14.117). These results indicated that intelligent methods are effective and robust tools for predicting the quality parameters of fresh fruits in the postharvest process.Practical ApplicationsAdvancement of technology and artificial intelligence leads to the tendency of many food industry engineers and researchers in the R&D department to use this technology to classify and predict various food industry processes. In the process of packaging products, there are challenges such as the amount of produced carbon dioxide and ethylene inside the package, which affects the shelf life of fresh agricultural products. In this research, artificial neural networks and support vector machine methods have been used to predict the two mentioned parameters. This approach can be used for the digitalization of the packaging process of agricultural and horticultural products and reduce the number of experimental activities. In addition, it is possible to improve the digitalization process by the fusion of smart sensors with machine learning methods.

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Section: Bruise Susceptibilitymentioning

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Rashvand

Altieri

Abbaszadeh

et al. 2023

J Food Process Engineering

View full text Add to dashboard Cite

show abstract

“…The literature on determining the bruising of agricultural products under dynamic impact loading has explored various destructive and nondestructive experimental methods. The pendulum test has been widely utilized as a destructive method by researchers (Abedi & Ahmadi, 2013; Bajema & Hyde, 1998; Eissa et al, 2012; Komarnicki et al, 2016; Nikara et al, 2020; Xia et al, 2021; Xie et al, 2020, 2023; Yeşiloğlu Cevher, 2022). Nondestructive damage detection of agricultural products through various technologies has also been commonly studied (Chen & Sun, 1991; El‐Mesery et al, 2019; Firouzjaei et al, 2018; Lu & Lu, 2017; Nturambirwe & Opara, 2020; Wang et al, 1988).…”

Section: Introductionmentioning

confidence: 99%

Determining the instantaneous bruising pattern in a sample potato tuber subjected to pendulum bob impact through finite element analysis

Çelik

Akinci

Erkan

et al. 2023

J Food Process Engineering

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Potato bruising resulting from mechanical impact during production operations including harvest and postharvest is a significant concern within the potato production sector, leading to consumer complaints and economic losses. The detection of instantaneous internal bruising poses a particular challenge as it can progress over time during storage or transportation, making it difficult to identify immediately after external impact. This study aims to investigate the progression of bruising and accurately represent the instantaneous dynamic deformation behavior of potato tubers under four pendulum bob impact cases (pendulum arm angles of 30°, 45°, 60°, and 90°). To analyze the dynamic impact deformation characteristics of the tubers, solid modeling based on a reverse engineering approach and explicit dynamic engineering simulations were employed. The simulation results yielded valuable numerical data and visual representation of the deformation progression. The loading conditions considered in this study indicated that the maximum stress values, reaching 0.818 MPa at a pendulum arm angle of 90°, remained below the bio‐yield stress point of the tuber flesh (1.05 MPa) determined through experimental compression tests. Therefore, it was concluded that the impact did not cause permanent deformation (i.e., permanent bruising) in the tuber. However, the numerical analysis clearly demonstrated the sequence of stress occurrences, which is a key contributing factor to potential permanent bruising. In this regard, the bruising energy threshold of 318.314 mJ (R2: 0.96) was extrapolated. The numerical findings presented in this study can aid in evaluating the susceptibility of tuber samples to bruising. By employing nonlinear explicit dynamics simulations, this research contributes to the advancement of understanding complex deformation and bruising in solid agricultural products. Moreover, the application of these techniques holds significant industrial implications for enhancing the handling and transportation of agricultural produce.Practical applicationsThis research aims to tackle the challenge of accurately representing the immediate internal bruising pattern in potato tubers resulting from mechanical impact. Conventional methods, such as physical or analytical expressions, may not fully capture the distribution of bruising experienced by the tubers. To overcome this limitation, an engineering simulation approach is proposed to provide a more precise depiction of the instantaneous bruising pattern. By advancing the understanding of complex deformation and bruising in solid agricultural products, this research contributes to improving the efficiency and quality of agricultural production in the industry. Additionally, this study offers a step‐by‐step guide on how to conduct these simulations effectively.

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Impact of Packaging on Bruise Damage of Fresh Produce

Fadiji,

Kaseke,

Lufu

et al. 2023

Mechanical Damage in Fresh Horticultural Produce

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Determination of bruise preventing capacity of the cushioning material in persimmon fruit under pendulum impact test

Cited by 8 publications

References 19 publications

Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Determining the instantaneous bruising pattern in a sample potato tuber subjected to pendulum bob impact through finite element analysis

Impact of Packaging on Bruise Damage of Fresh Produce

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Determination of bruise preventing capacity of the cushioning material in persimmon fruit under pendulum impact test

Cited by 8 publications

References 19 publications

Prediction of CO2 and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Prediction of CO2 and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Determining the instantaneous bruising pattern in a sample potato tuber subjected to pendulum bob impact through finite element analysis

Impact of Packaging on Bruise Damage of Fresh Produce

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Product

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Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach

Prediction of CO₂ and ethylene produced in‐packaged apricot under cold plasma treatment by machine learning approach