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Taghinezhad E, Kaveh M, Szumny A, Figiel A, Blasco J. Qualitative, energy and environmental aspects of microwave drying of pre-treated apple slices. Sci Rep 2023; 13:16152. [PMID: 37752295 PMCID: PMC10522627 DOI: 10.1038/s41598-023-43358-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 09/22/2023] [Indexed: 09/28/2023] Open
Abstract
In the present research, response parameters such as specific energy consumption (SEC), thermal efficiency (TE), energy efficiency (EF), drying time (DT), greenhouse gas (GHG) emission (such as CO2 and NOx), and quality features (color variation and shrinkage) were modeled by response surface methodology (RSM) for apple slices dried in a microwave dryer under ultrasonication (30 ℃-10 min) and blanching (80 °C-2 min) pretreatments. Also, RSM was applied to optimize two independent parameters including microwave power and sample thickness in the levels 100, 200, and 300 W and 2, 4, and 6 mm, respectively. The results indicated the significant influence (P < 0.01) of the independent parameters on the response parameters. The vales of SEC, DT, GHG emission, shrinkage, and color difference were linearly decreased with the declining sample thickness and increasing microwave power, while the energy and thermal efficiencies were increased by a quadratic equation. The use of ultrasonication and blanching pretreatments decreased the SEC, GHG emissions, and DT; while improving the quality of the samples as compared to the non-treated slices. The optimization results showed the optimal drying times (31.55, 82.19, and 50.55 min), SEC (3.42, 10.07, and 4.37 MJ/kg), CO2 with natural gas (1539.75, 1518.75, and 4585 g), CO2 with gas oil (3662.53, 2099.25, 2721.25 g), NOx with natural gas (10.094, 9.956, and 12.906 g), and NOx with gas oil (12.934, 12.758, and 16.538 g) at a microwave power of 300 W and sample thickness of 2 mm with desirability of 0.921, 0.935, and 0.916 for control samples, ultrasonicated, and blanched, respectively.
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Affiliation(s)
- Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, 5619911367, Ardabil, Iran.
- Department of Chemistry, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375, Wrocław, Poland.
| | - Mohammad Kaveh
- Department of Petroleum Engineering, College of Engineering, Knowledge University, 44001, Erbil, Iraq
| | - Antoni Szumny
- Department of Chemistry, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375, Wrocław, Poland
| | - Adam Figiel
- Institute of Agricultural Engineering, Wroclaw University of Environmental and Life Sciences, Chełmońskiego 37a, 51-630, Wrocław, Poland
| | - José Blasco
- Centro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias (IVIA), CV-315, Km 10.7, Moncada, 46113, Valencia, Spain
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Taghinezhad E, Szumny A, Figiel A. The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process. Molecules 2023; 28:molecules28072930. [PMID: 37049695 PMCID: PMC10096048 DOI: 10.3390/molecules28072930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 03/29/2023] Open
Abstract
Drying is one of the common procedures in the food processing steps. The moisture content (MC) is also of crucial significance in the evaluation of the drying technique and quality of the final product. However, conventional MC evaluation methods suffer from several drawbacks, such as long processing time, destruction of the sample and the inability to determine the moisture of single grain samples. In this regard, the technology and knowledge of hyperspectral imaging (HSI) were addressed first. Then, the reports on the use of this technology as a rapid, non-destructive, and precise method were explored for the prediction and detection of the MC of crops during their drying process. After spectrometry, researchers have employed various pre-processing and merging data techniques to decrease and eliminate spectral noise. Then, diverse methods such as linear and multiple regressions and machine learning were used to model and predict the MC. Finally, the best wavelength capable of precise estimation of the MC was reported. Investigation of the previous studies revealed that HSI technology could be employed as a valuable technique to precisely control the drying process. Smart dryers are expected to be commercialised and industrialised soon by the development of portable systems capable of an online MC measurement.
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Affiliation(s)
- Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
- Department of Food Chemistry and Biocatalysis, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375 Wrocław, Poland
- Correspondence:
| | - Antoni Szumny
- Department of Food Chemistry and Biocatalysis, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375 Wrocław, Poland
| | - Adam Figiel
- Institute of Agricultural Engineering, Wroclaw University of Environmental and Life Sciences, Chełmońskiego 37a, 51-630 Wrocław, Poland
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Kaveh M, Taghinezhad E, Witrowa‐Rajchert D, Imanian K, Khalife E, Nowacka M. Use of ultrasound pre‐treatment before microwave drying of kiwifruits – an optimization approach with response surface methodology. J FOOD PROCESS PRES 2022. [DOI: 10.1111/jfpp.16714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Mohammad Kaveh
- Department of Petroleum Engineering College of Engineering Knowledge University, 44001 Erbil Iraq
| | - Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering Moghan College of Agriculture and Natural Resources University of Mohaghegh Ardabili, Ardabil 56199‐11367 Ardabil Iran
| | - Dorota Witrowa‐Rajchert
- Department of Food Engineering and Process Management Institute of Food Sciences Warsaw University of Life Sciences‐SGGW, 02‐776 Warsaw Poland
| | - Kamal Imanian
- Agricultural Engineering Research Department West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO Urmia Iran
| | - Esmail Khalife
- Department of Civil Engineering Cihan University‐ Erbil Kurdistan Region Iraq
| | - Małgorzata Nowacka
- Department of Food Engineering and Process Management Institute of Food Sciences Warsaw University of Life Sciences‐SGGW, 02‐776 Warsaw Poland
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Nazarloo AS, Sharabiani VR, Gilandeh YA, Taghinezhad E, Szymanek M. Evaluation of Different Models for Non-Destructive Detection of Tomato Pesticide Residues Based on Near-Infrared Spectroscopy. Sensors (Basel) 2021; 21:3032. [PMID: 33925882 PMCID: PMC8123465 DOI: 10.3390/s21093032] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/19/2021] [Accepted: 04/23/2021] [Indexed: 11/17/2022]
Abstract
In this study, the possibility of non-destructive detection of tomato pesticide residues was investigated using Vis/NIRS and prediction models such as PLSR and ANN. First, Vis/NIR spectral data from 180 samples of non-pesticide tomatoes (used as a control treatment) and samples impregnated with pesticide with a concentration of 2 L per 1000 L between 350-1100 nm were recorded by a spectroradiometer. Then, they were divided into two parts: Calibration data (70%) and prediction data (30%). Next, the prediction performance of PLSR and ANN models after processing was compared with 10 spectral preprocessing methods. Spectral data obtained from spectroscopy were used as input and pesticide values obtained by gas chromatography method were used as output data. Data dimension reduction methods (principal component analysis (PCA), Random frog (RF), and Successive prediction algorithm (SPA)) were used to select the number of main variables. According to the values obtained for root-mean-square error (RMSE) and correlation coefficient (R) of the calibration and prediction data, it was found that the combined model SPA-ANN has the best performance (RC = 0.988, RP = 0.982, RMSEC = 0.141, RMSEP = 0.166). The investigational consequences obtained can be a reference for the development of internal content of agricultural products, based on NIR spectroscopy.
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Affiliation(s)
- Araz Soltani Nazarloo
- Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.S.N.); (Y.A.G.)
| | - Vali Rasooli Sharabiani
- Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.S.N.); (Y.A.G.)
| | - Yousef Abbaspour Gilandeh
- Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.S.N.); (Y.A.G.)
| | - Ebrahim Taghinezhad
- Department of Agricultural Engineering and Technology, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
| | - Mariusz Szymanek
- Department of Agricultural, Forest and Transport Machinery, University of Life Sciences in Lublin, Street Głęboka 28, 20-612 Lublin, Poland;
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Kaveh M, Abbaspour-Gilandeh Y, Taghinezhad E, Witrowa-Rajchert D, Nowacka M. The Quality of Infrared Rotary Dried Terebinth ( Pistacia atlantica L.)-Optimization and Prediction Approach Using Response Surface Methodology. Molecules 2021; 26:molecules26071999. [PMID: 33916010 PMCID: PMC8036459 DOI: 10.3390/molecules26071999] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 03/29/2021] [Accepted: 03/30/2021] [Indexed: 12/30/2022] Open
Abstract
Most agricultural products are harvested with a moisture content that is not suitable for storage. Therefore, the products are subjected to a drying process to prevent spoilage. This study evaluates an infrared rotary dryer (IRRD) with three levels of infrared power (250, 500, and 750 W) and three levels of rotation speed (5, 10, and 15 rpm) to dry terebinth. Response surface methodology (RSM) was used to illustrate and optimize the interaction between the independent variables (infrared power and rotation speed) and the response variables (drying time, moisture diffusivity, shrinkage, color change, rehydration rate, total phenolic content, and antioxidant activity). As infrared power and rotation speed increased, drying time, rehydration rate, antioxidant activity, and total phenolic content decreased, while the other parameters were increased. According to the results, the optimum drying conditions of terebinth were determined in the IRRD at an infrared power of 250 W and drum rotation speed of 5 rpm. The optimum values of the response variables were 49.5 min for drying time, 8.27 × 10−9 m2/s for effective moisture diffusivity, 2.26 for lightness, 21.60 for total color changes, 34.75% for shrinkage, 2.4 for rehydration rate, 124.76 mg GAE/g d.m. for total phenolic content and 81% for antioxidant activity.
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Affiliation(s)
- Mohammad Kaveh
- Department of Biosystems Engineering, College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
| | - Yousef Abbaspour-Gilandeh
- Department of Biosystems Engineering, College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
- Correspondence: (Y.A.-G.); (M.N.); Tel.: +48-22-593-75-79 (M.N.)
| | - Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
| | - Dorota Witrowa-Rajchert
- Department of Food Engineering and Process Management, Institute of Food Sciences, Warsaw University of Life Sciences—SGGW, 02-776 Warsaw, Poland;
| | - Małgorzata Nowacka
- Department of Food Engineering and Process Management, Institute of Food Sciences, Warsaw University of Life Sciences—SGGW, 02-776 Warsaw, Poland;
- Correspondence: (Y.A.-G.); (M.N.); Tel.: +48-22-593-75-79 (M.N.)
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Fazeli Burestan N, Afkari Sayyah AH, Taghinezhad E. Prediction of some quality properties of rice and its flour by near-infrared spectroscopy (NIRS) analysis. Food Sci Nutr 2021; 9:1099-1105. [PMID: 33598193 PMCID: PMC7866604 DOI: 10.1002/fsn3.2086] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/10/2020] [Accepted: 12/11/2020] [Indexed: 11/22/2022] Open
Abstract
The measurement of different quality properties requires particular tools and chemical materials, most of which are time-using. The present research was accomplished to survey the possibility of using NIRS (870-2450 nm) to predict the amylose content (AC), protein content (PC), breakdown (BDV), and setback viscosity (SBV) of white rice (Khazar variety) and its flour. Determination coefficients of calibration models to flour samples of AC, PC, BDV, and SBV generated by the partial least-squares (PLS) regression were obtained as R 2 cal ≥ .85 and R 2 pre ≥ .80. Root mean square error of calibration (RMSEC) was calculated as 0.393, 0.07, 2.55, and 1.33, respectively. Similarly to grain samples, were obtained as R 2 cal ≥ .88 and R 2 pre ≥ .71 for calibration and prediction. RMSEC was measured as 0.303, 0.27, 2.59, and 3.11, respectively. NIRS has the potential to be used as a quick technique for predicting the quality attributes of kernel specimens.
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Affiliation(s)
| | | | - Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh ArdabiliArdabilIran
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Taghinezhad E, Kaveh M, Szumny A. Optimization and Prediction of the Drying and Quality of Turnip Slices by Convective-Infrared Dryer under Various Pretreatments by RSM and ANFIS Methods. Foods 2021; 10:foods10020284. [PMID: 33572543 PMCID: PMC7911452 DOI: 10.3390/foods10020284] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 01/14/2023] Open
Abstract
Drying can prolong the shelf life of a product by reducing microbial activities while facilitating its transportation and storage by decreasing the product weight and volume. The quality factors of the drying process are among the important issues in the drying of food and agricultural products. In this study, the effects of several independent variables such as the temperature of the drying air (50, 60, and 70 °C) and the thickness of the samples (2, 4, and 6 mm) were studied on the response variables including the quality indices (color difference and shrinkage) and drying factors (drying time, effective moisture diffusivity coefficient, specific energy consumption (SEC), energy efficiency and dryer efficiency) of the turnip slices dried by a hybrid convective-infrared (HCIR) dryer. Before drying, the samples were treated by three pretreatments: microwave (360 W for 2.5 min), ultrasonic (at 30 °C for 10 min) and blanching (at 90 °C for 2 min). The statistical analyses of the data and optimization of the drying process were achieved by the response surface method (RSM) and the response variables were predicted by the adaptive neuro-fuzzy inference system (ANFIS) model. The results indicated that an increase in the dryer temperature and a decline in the thickness of the sample can enhance the evaporation rate of the samples which will decrease the drying time (40–20 min), SEC (from 168.98 to 21.57 MJ/kg), color difference (from 50.59 to 15.38) and shrinkage (from 67.84% to 24.28%) while increasing the effective moisture diffusivity coefficient (from 1.007 × 10−9 to 8.11 × 10−9 m2/s), energy efficiency (from 0.89% to 15.23%) and dryer efficiency (from 2.11% to 21.2%). Compared to ultrasonic and blanching, microwave pretreatment increased the energy and drying efficiency; while the variations in the color and shrinkage were the lowest in the ultrasonic pretreatment. The optimal condition involved the temperature of 70 °C and sample thickness of 2 mm with the desirability above 0.89. The ANFIS model also managed to predict the response variables with R2 > 0.96.
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Affiliation(s)
- Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
- Correspondence: ; Tel.: +98-45-3271-5408
| | - Mohammad Kaveh
- Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
| | - Antoni Szumny
- Department of Chemistry, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375 Wrocław, Poland;
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Fazeli Burestan N, Afkari Sayyah AH, Taghinezhad E. Mathematical modeling for the prediction of some quality parameters of white rice based on the strength properties of samples using response surface methodology (RSM). Food Sci Nutr 2020; 8:4134-4144. [PMID: 32884694 PMCID: PMC7455930 DOI: 10.1002/fsn3.1703] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/19/2020] [Accepted: 05/20/2020] [Indexed: 11/12/2022] Open
Abstract
One of the major problems in predicting the quality properties of rice is that conducting experiments in the food industry can be highly expensive. The objective of this study was to predict some quality properties in varieties (Domsiah, Hashemi, Dorfak, and Kadus) via compression test at moisture levels 9 and 14% w.b. Based on historical data design, RSM was used to model and estimate of dependent variables (amylose (AC) and protein content (PC), gelatinization temperature, gel consistency GC), minimum (Min.V), final (FV), breakdown (BDV) and setback viscosity (SBV), peak time (PT) and pasting temperature (Pa.T)) through independent variables (the rate of force, deformation, rupture energy, tangent, and secant modulus). An ANOVA test showed that models were significant (p < 0.05). The most appropriate model for response variables prediction of AC and GC (Kadus 14%), PC (Domsiah 9%), Min.V, FV, and SBV (Dorfak 9%), BDV (Dorfak 14%), PT (Hashemi 14%), and Pa.T (Kadus 9%) was R pred 2 as 0.86, 0.85, 0.93, 0.955, 0.953, 0.94, 0.94, 0.86, and 0.91, respectively, with the most appropriate optimal values as 23.52%, 48, 10%, 164.95 RVU, 304.12 RVU, 162.66 RVU, 64.52 RVU, 6.09 min, and 92.45°C and desirability as 0.91, 0.95, 0.95, 0.80, 0.89, 0.83, 0.84, 0.89, and 0.96, respectively. The optimal values of the independent variables have a decreasing trend, and the optimal values of the response variables are proportional to the optimal conditions. The results indicated that the RSM could be quite useful in the optimization of the models developed for predicting the rice quality properties.
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Affiliation(s)
| | | | - Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh ArdabiliArdabilIran
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Kaveh M, Taghinezhad E, Aziz M. Effects of physical and chemical pretreatments on drying and quality properties of blackberry ( Rubus spp.) in hot air dryer. Food Sci Nutr 2020; 8:3843-3856. [PMID: 32724646 PMCID: PMC7382141 DOI: 10.1002/fsn3.1678] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 05/08/2020] [Accepted: 05/13/2020] [Indexed: 11/15/2022] Open
Abstract
This research examines the impact of various pretreatments on effective moisture diffusivity coefficient (Deff ), activation energy (Ea ), specific energy consumption (SEC), color, and shrinkage of blackberry (Rubus spp.). Hot air drying experiments were conducted under three different temperatures (50, 60, and 70°C) and four pretreatments, including thermal pretreatment by hot water blanching at 70, 80, and 90°C, pulse pretreatment with microwave having power of 90, 180, and 360 W, chemical pretreatment using ascorbic acid (1% in distilled water), and mechanical pretreatment using ultrasonic vibration with working frequency of 28 ± 5% kHz for 15, 30, and 45 min. The results show that the highest Deff value, which was 1.00 × 10-8 m2/s, could be achieved by using a microwave pretreatment with power and drying temperature of 360 W and 70°C͘, respectively. Moreover, the lowest Deff value obtained from this similar pretreatment condition was 3.10 × 10-9 m2/s at a drying temperature of 50°C, while Ea ranged from 13.61 to 26.02 kJ/mol. The highest and lowest SECs were 269.91 kW hr/kg for the control sample and 75.63 kW hr/kg for the microwave pretreatment, respectively. Furthermore, the largest color change and shrinkage were detected in ascorbic acid pretreatment and control sample, respectively.
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Affiliation(s)
- Mohammad Kaveh
- Department of Biosystems EngineeringCollege of Agriculture and Natural ResourcesUniversity of Mohaghegh ArdabiliArdabilIran
| | - Ebrahim Taghinezhad
- Department of Agricultural Engineering and TechnologyMoghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh ArdabiliArdabilIran
| | - Muhammad Aziz
- Institute of Industrial ScienceThe University of TokyoTokyoJapan
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Taghinezhad E, Kaveh M, Jahanbakhshi A, Golpour I. Use of artificial intelligence for the estimation of effective moisture diffusivity, specific energy consumption, color and shrinkage in quince drying. J FOOD PROCESS ENG 2020. [DOI: 10.1111/jfpe.13358] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran
| | - Mohammad Kaveh
- Department of Biosystems Engineering, Faculty of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran
| | - Ahmad Jahanbakhshi
- Department of Biosystems Engineering, Faculty of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran
| | - Iman Golpour
- Department of Mechanical Engineering of BiosystemsUrmia University Urmia Iran
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Jahanbakhshi A, Kaveh M, Taghinezhad E, Rasooli Sharabiani V. Assessment of kinetics, effective moisture diffusivity, specific energy consumption, shrinkage, and color in the pistachio kernel drying process in microwave drying with ultrasonic pretreatment. J FOOD PROCESS PRES 2020. [DOI: 10.1111/jfpp.14449] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Ahmad Jahanbakhshi
- Department of Biosystems Engineering College of Agriculture and Natural Resources University of Mohaghegh Ardabili Ardabil Iran
| | - Mohammad Kaveh
- Department of Biosystems Engineering College of Agriculture and Natural Resources University of Mohaghegh Ardabili Ardabil Iran
| | - Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering Moghan College of Agriculture and Natural Resources University of Mohaghegh Ardabili Ardabil Iran
| | - Vali Rasooli Sharabiani
- Department of Biosystems Engineering College of Agriculture and Natural Resources University of Mohaghegh Ardabili Ardabil Iran
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Taghinezhad E, Szumny A, Kaveh M, Rasooli Sharabiani V, Kumar A, Shimizu N. Parboiled Paddy Drying with Different Dryers: Thermodynamic and Quality Properties, Mathematical Modeling Using ANNs Assessment. Foods 2020; 9:foods9010086. [PMID: 31941076 PMCID: PMC7023440 DOI: 10.3390/foods9010086] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 12/29/2019] [Accepted: 01/09/2020] [Indexed: 11/16/2022] Open
Abstract
The effect of hybrid infrared-convective (IRC), microwave (MIC) and infrared-convective-microwave (IRCM) drying methods on thermodynamic (drying kinetics, effective moisture diffusivity coefficient (Deff), specific energy consumption (SEC)) and quality (head rice yield (HRY), color value and lightness) characteristics of parboiled rice samples were investigated in this study. Experimental data were fitted into empirical drying models to explain moisture ratio (MR) variations during drying. The Artificial Neural Network (ANN) method was applied to predict MR. The IRCM method provided shorter drying time (reduce percentage = 71%) than IRC (41%) and microwave (69%) methods. The Deff of MIC drying (6.85 × 10−11–4.32 × 10−10 m2/s) was found to be more than the observed in IRC (1.32 × 10−10–1.87 × 10−10 m2/s) and IRCM methods (1.58 × 10−11–2.31 × 10−11 m2/s). SEC decreased during drying. Microwave drying had the lowest SEC (0.457 MJ/kg) compared to other drying methods (with mean 28 MJ/kg). Aghbashlo’s model was found to be the best for MR prediction. According to the ANN results, the highest determination coefficient (R2) values for MR prediction in IRC, IRCM and MIC drying methods were 0.9993, 0.9995 and 0.9990, respectively. The HRY (from 60.2 to 74.07%) and the color value (from 18.08 to 19.63) increased with the drying process severity, thereby decreasing the lightness (from 57.74 to 62.17). The results of this research can be recommended for the selection of the best dryer for parboiled paddy. Best drying conditions in the study is related to the lowest dryer SEC and sample color value and the highest HRY and sample lightness.
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Affiliation(s)
- Ebrahim Taghinezhad
- Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
- Correspondence: (E.T.); (A.S.); Tel.: +98-45-3271-5408 (E.T.); +48-694-647-222 (A.S.)
| | - Antoni Szumny
- Department of Chemistry, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375 Wrocław, Poland
- Correspondence: (E.T.); (A.S.); Tel.: +98-45-3271-5408 (E.T.); +48-694-647-222 (A.S.)
| | - Mohammad Kaveh
- Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (M.K.); (V.R.S.)
| | - Vali Rasooli Sharabiani
- Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (M.K.); (V.R.S.)
| | - Anil Kumar
- Department of Mechanical Engineering, Delhi Technological University, Delhi 110042, India;
| | - Naoto Shimizu
- Research Faculty of Agriculture, Hokkaido University, Hokkaido 064-8589, Sapporo, Japan;
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Jahanbakhshi A, Rasooli Sharabiani V, Heidarbeigi K, Kaveh M, Taghinezhad E. Evaluation of engineering properties for waste control of tomato during harvesting and postharvesting. Food Sci Nutr 2019; 7:1473-1481. [PMID: 31024721 PMCID: PMC6475739 DOI: 10.1002/fsn3.986] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 01/26/2019] [Accepted: 02/07/2019] [Indexed: 11/29/2022] Open
Abstract
In Iran, more than 30% of agricultural products turn into waste at different stages from harvesting to consumption. Thus, main factors for performing of this present study are including of: (a) the importance of tomato as an agricultural product and (b) lack of information about reducing waste during tomato processing. In this study, some physical, nutritional, mechanical, and hydrodynamic properties of tomato were measured under standard conditions. Physical properties included the length, width, thickness, mean diameter (geometric and arithmetic), mass, volume, density, sphericity, surface area, and aspect ratio. Also, nutritional properties, moisture, dry matter, pH, total soluble solid (TSS), and titration acidity (TA) of tomato were evaluated. The mechanical properties of tomato (compression and shear) were measured using Instron instrument. The hydrodynamic properties were measured with water in transportation, separation, and sorting of tomatoes. The physical properties were including of length, width, thickness, mass, volume, and geometric and arithmetic mean diameters showed a direct relationship with the size of tomatoes. Also, volumetric mass (density) had an inverse relation with tomato size. Yield point and shear force were obtained 51.27 and 22.20 N, respectively. The nutritional properties such as pH value, TSS, and TA were equal to 4.22, 22.23οBrix, and 2%, respectively. The hydrodynamic properties of tomatoes such as the terminal velocity, the tomatoes' rise time in the water column, the buoyancy force, and the drag force were obtained to be equal to 0.05 m/s, 10.11 S, 0.52 N, and 0.17 N, respectively.
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Affiliation(s)
- Ahmad Jahanbakhshi
- Department of Biosystems EngineeringUniversity of Mohaghegh ArdabiliArdabilIran
| | | | | | - Mohammad Kaveh
- Department of Biosystems EngineeringUniversity of Mohaghegh ArdabiliArdabilIran
| | - Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh ArdabiliArdabilIran
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Alaei B, Dibagar N, Chayjan RA, Kaveh M, Taghinezhad E. The effect of short and medium infrared radiation on some drying and quality characteristics of quince slices under vacuum condition. Quality Assurance and Safety of Crops & Foods 2018. [DOI: 10.3920/qas2017.1252] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- B. Alaei
- Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - N. Dibagar
- Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - R. Amiri Chayjan
- Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - M. Kaveh
- Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, 59661-14477 Ardabil, Iran
| | - E. Taghinezhad
- Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, 56199-11367 Ardabil, Iran
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15
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Karami H, Kaveh M, Mirzaee‐Ghaleh E, Taghinezhad E. Using PSO and GWO techniques for prediction some drying properties of tarragon (
Artemisia dracunculus
L.). J FOOD PROCESS ENG 2018. [DOI: 10.1111/jfpe.12921] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Hamed Karami
- Young Researchers and Elite Club, Kermanshah BranchIslamic Azad University Kermanshah Iran
| | - Mohammad Kaveh
- Young Researchers Club and EliteSardasht Branch, Islamic Azad University Sardasht Iran
- Young Researchers Club and EliteUrmia Branch, Islamic Azad University Urmia Iran
| | | | - Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural ResourcesUniversity of Mohaghegh Ardabili Ardabil Iran
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Kaveh M, Jahanbakhshi A, Abbaspour-Gilandeh Y, Taghinezhad E, Moghimi MBF. The effect of ultrasound pre-treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network. J FOOD PROCESS ENG 2018. [DOI: 10.1111/jfpe.12868] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Mohammad Kaveh
- Department of Biosystems Engineering; University of Mohaghegh Ardabili; Ardabil Iran
| | - Ahmad Jahanbakhshi
- Department of Biosystems Engineering; University of Mohaghegh Ardabili; Ardabil Iran
| | | | - Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural Resources; University of Mohaghegh Ardabili; Ardabil Iran
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Taghinezhad E, Brenner T. Mathematical modeling of starch gelatinization and some quality properties of parboiled rice based on parboiling indicators using RSM. J FOOD PROCESS ENG 2016. [DOI: 10.1111/jfpe.12483] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Ebrahim Taghinezhad
- Moghan College of Agriculture and Natural Resources; University of Mohaghegh Ardabili; 56199-11367 Iran
| | - Tom Brenner
- Materials and Life Sciences Department; Sophia University; Chiyoda, Tokyo Japan
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Taghinezhad E, Khoshtaghaza MH, Suzuki T, Minaei S, Brenner T. Quantifying the Relationship between Rice Starch Gelatinization and Moisture-Electrical Conductivity of Paddy during Soaking. J FOOD PROCESS ENG 2015. [DOI: 10.1111/jfpe.12235] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ebrahim Taghinezhad
- Biosystems Engineering Department; Tarbiat Modares University; PO Box 14115-336 Tehran 1497713111 Iran
| | | | - Toru Suzuki
- Food Science and Technology Department; Tokyo University of Marine Science & Technology; Tokyo Japan
| | - Saeid Minaei
- Biosystems Engineering Department; Tarbiat Modares University; PO Box 14115-336 Tehran 1497713111 Iran
| | - Tom Brenner
- Food Science and Technology Department; Tokyo University of Marine Science & Technology; Tokyo Japan
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