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Haghbin N, Bakhshipour A, Zareiforoush H, Mousanejad S. Non-destructive pre-symptomatic detection of gray mold infection in kiwifruit using hyperspectral data and chemometrics. Plant Methods 2023; 19:53. [PMID: 37268945 PMCID: PMC10236597 DOI: 10.1186/s13007-023-01032-y] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/27/2023] [Indexed: 06/04/2023]
Abstract
Application of hyperspectral imaging (HSI) and data analysis algorithms was investigated for early and non-destructive detection of Botrytis cinerea infection. Hyperspectral images were collected from laboratory-based contaminated and non-contaminated fruits at different day intervals. The spectral wavelengths of 450 nm to 900 nm were pretreated by applying moving window smoothing (MWS), standard normal variates (SNV), multiplicative scatter correction (MSC), Savitzky-Golay 1st derivative, and Savitzky-Golay 2nd derivative algorithms. In addition, three different wavelength selection algorithms, namely; competitive adaptive reweighted sampling (CARS), uninformative variable elimination (UVE), and successive projection algorithm (SPA), were executed on the spectra to invoke the most informative wavelengths. The linear discriminant analysis (LDA), developed with SNV-filtered spectral data, was the most accurate classifier to differentiate the contaminated and non-contaminated kiwifruits with accuracies of 96.67% and 96.00% in the cross-validation and evaluation stages, respectively. The system was able to detect infected samples before the appearance of disease symptoms. Results also showed that the gray-mold infection significantly influenced the kiwifruits' firmness, soluble solid content (SSC), and titratable acidity (TA) attributes. Moreover, the Savitzky-Golay 1st derivative-CARS-PLSR model obtained the highest prediction rate for kiwifruit firmness, SSC, and TA with the determination coefficient (R2) values of 0.9879, 0.9644, 0.9797, respectively, in calibration stage. The corresponding cross-validation R2 values were equal to 0.9722, 0.9317, 0.9500 for firmness, SSC, and TA, respectively. HSI and chemometric analysis demonstrated a high potential for rapid and non-destructive assessments of fungal-infected kiwifruits during storage.
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Affiliation(s)
- Najmeh Haghbin
- Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | - Adel Bakhshipour
- Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran.
| | - Hemad Zareiforoush
- Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | - Sedigheh Mousanejad
- Department of Plant Protection, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
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Bakhshipour A, Zareiforoush H, Bagheri I. Mathematical and intelligent modeling of stevia ( Stevia Rebaudiana) leaves drying in an infrared-assisted continuous hybrid solar dryer. Food Sci Nutr 2021; 9:532-543. [PMID: 33473314 PMCID: PMC7802544 DOI: 10.1002/fsn3.2022] [Citation(s) in RCA: 6] [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: 09/30/2020] [Revised: 11/01/2020] [Accepted: 11/02/2020] [Indexed: 12/04/2022] Open
Abstract
Drying characteristics of stevia leaves were investigated in an infrared (IR)-assisted continuous-flow hybrid solar dryer. Drying experiments were conducted at the inlet air temperatures of 30, 40, and 50°C, air inlet velocities of 7, 8, and 9 m/s, and IR lamp input powers of 0, 150, and 300 W. The results indicated that inlet air temperature and IR lamp input power had significant effect on drying time (p < .05). A comparative study was performed among mathematical, Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy System (ANFIS) models for predicting the experimental moisture ratio (MR) of stevia leaves during the drying process. The ANN model was the most accurate MR predictor with coefficient of determination (R2), root mean squared error (RMSE), and chi-squared error (χ2) values of 0.9995, 0.0005, and 0.0056, respectively, on test dataset. These values of the ANFIS model on test dataset were 0.9936, 0.0243, and 0.0202, respectively. Among the mathematical models, the Midilli model was the best-fitted model to experimental MR values in most of the drying conditions. It was concluded that artificial intelligence modeling is an effective approach for accurate prediction of the drying kinetics of stevia leaves in the continuous-flow IR-assisted hybrid solar dryer.
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Affiliation(s)
- Adel Bakhshipour
- Department of Agricultural Mechanization EngineeringFaculty of Agricultural SciencesUniversity of GuilanRashtIran
| | - Hemad Zareiforoush
- Department of Agricultural Mechanization EngineeringFaculty of Agricultural SciencesUniversity of GuilanRashtIran
| | - Iraj Bagheri
- Department of Agricultural Mechanization EngineeringFaculty of Agricultural SciencesUniversity of GuilanRashtIran
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Bakhshipour A, Zareiforoush H. Development of a fuzzy model for differentiating peanut plant from broadleaf weeds using image features. Plant Methods 2020; 16:153. [PMID: 33292367 PMCID: PMC7670791 DOI: 10.1186/s13007-020-00695-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 11/09/2020] [Indexed: 06/12/2023]
Abstract
A combination of decision tree (DT) and fuzzy logic techniques was used to develop a fuzzy model for differentiating peanut plant from weeds. Color features and wavelet-based texture features were extracted from images of peanut plant and its three common weeds. Two feature selection techniques namely Principal Component Analysis (PCA) and Correlation-based Feature Selection (CFS) were applied on input dataset and three Decision Trees (DTs) including J48, Random Tree (RT), and Reduced Error Pruning (REP) were used to distinguish between different plants. In all cases, the best overall classification accuracies were achieved when CFS-selected features were used as input data. The obtained accuracies of J48-CFS, REP-CFS, and RT-CFS trees for classification of the four plant categories namely peanut plant, Velvetleaf, False daisy, and Nicandra, were 80.83%, 80.00% and 79.17% respectively. Along with these almost low accuracies, the structures of the decision trees were complex making them unsuitable for developing a fuzzy inference system. The classifiers were also used for differentiating peanut plant from the group of weeds. The overall accuracies on training and testing datasets were respectively 95.56% and 93.75% for J48-CFS; 92.78% and 91.67% for REP-CFS; and 93.33% and 92.59% for RT-CFS DTs. The results showed that the J48-CFS and REP-CFS were the most appropriate models to set the membership functions and rules of the fuzzy classifier system. Based on the results, it can be concluded that the developed DT-based fuzzy logic model can be used effectively to discriminate weeds from peanut plant in the form of machine vision-based cultivating systems.
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Affiliation(s)
- Adel Bakhshipour
- Department of Agricultural Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran.
| | - Hemad Zareiforoush
- Department of Agricultural Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
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Bakhshipour A, Zareiforoush H, Bagheri I. Application of decision trees and fuzzy inference system for quality classification and modeling of black and green tea based on visual features. Food Measure 2020. [DOI: 10.1007/s11694-020-00390-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Payman S, Bakhshipour A, Zareiforoush H. Development of an expert vision-based system for inspecting rice quality indices. Quality Assurance and Safety of Crops & Foods 2018. [DOI: 10.3920/qas2017.1109] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [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)
- S.H. Payman
- Department of Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan; Khalij Fars highway, 5 km of Ghazvin road, 4199613776 Rasht, Iran
| | - A. Bakhshipour
- Department of Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan; Khalij Fars highway, 5 km of Ghazvin road, 4199613776 Rasht, Iran
| | - H. Zareiforoush
- Department of Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan; Khalij Fars highway, 5 km of Ghazvin road, 4199613776 Rasht, Iran
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Rostami S, Behruzian M, Hosseinzadeh Samani B, Lorigooini Z, Hosseinabadi T, Zareiforoush H, Behruzian A. Study of Combined Ultrasound-microwave Effect on Chemical Compositions and E. coli Count of Rose Aromatic Water. Iran J Pharm Res 2018; 17:146-160. [PMID: 31011349 PMCID: PMC6447883] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
Since the rose water is used in food, pharmaceutical, and cosmetic products, its microbiological control is necessary. Conventional pasteurization methods cause undesirable changes in taste, smell, medicinal properties and nutritional value with decreasing the amount of essential oil, because of high temperatures. In this study, the effects of the microwave power, temperature, ultrasound power, and ultrasonic exposure were evaluated during rose water pasteurization process on its chemical compositions and E. coli content. In order to determine the microbial inactivation by microwave and ultrasound, E. coli at a concentration of 2 × 106 per mL was inoculated to rose aromatic water. The results showed that each variable on the inactivation of E. coli and energy consumption per microbial reduction cycle had a significant effect. The optimum values of microwave power, temperature, ultrasound power, and ultrasound exposure time were obtained 326.24 W, 43.32 °C, 100 W and 4 min, respectively. The chemical composition assessment was done by GC/MS analysis. Phenethyl alcohol is one of the main components of rose water which was completely lost in the conventional pasteurization method, while in pasteurization process by combined method, it showed an acceptable decrease as compared with raw rose water. Furthermore, the proposed method caused minimal changes in the chemical compositions of the rose water as compared to the conventional heating methods.
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Affiliation(s)
- Sajad Rostami
- Department of Mechanical Engineering of Biosystem, Shahrekord University, Iran.
| | - Mehrsa Behruzian
- Department of Mechanical Engineering of Biosystem, Shahrekord University, Iran.
| | | | - Zahra Lorigooini
- Medical Plants Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Iran.
| | - Tahereh Hosseinabadi
- Department of Pharmacognosy and Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Hemad Zareiforoush
- Department of Agricultural Mechanization Engineering, University of Guilan, Rasht, Iran.
| | - Ava Behruzian
- Department of Mechanical Engineering of Biosystem, Shahrekord University, Iran.
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Hosseinzadeh Samani B, Lorigooini Z, Rostami S, Zareiforoush H, Behruzian M, Behruzian A. The simultaneous effect of electromagnetic and ultrasound treatments on Escherichia coli count in red grape juice. J Herbmed Pharmacol 2017. [DOI: 10.15171/jhp.2018.06] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Banakar A, Zareiforoush H, Baigvand M, Montazeri M, Khodaei J, Behroozi-Khazaei N. Combined Application of Decision Tree and Fuzzy Logic Techniques for Intelligent Grading of Dried Figs. J FOOD PROCESS ENG 2016. [DOI: 10.1111/jfpe.12456] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [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)
- Ahmad Banakar
- Department of Biosystems Engineering; Tarbiat Modares University; Tehran Iran
| | - Hemad Zareiforoush
- Department of Mechanization Engineering Faculty of Agricultural Sciences; University of Guilan; Rasht Iran
| | - Mehrdad Baigvand
- Department of Biosystems Engineering; Tarbiat Modares University; Tehran Iran
| | - Mehdi Montazeri
- Department of Biosystems Engineering; Tarbiat Modares University; Tehran Iran
| | - Jalal Khodaei
- Department of Biosystems Engineering; University of Kurdistan; Sanandaj Iran
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Samani BH, Khoshtaghaza MH, Lorigooini Z, Minaei S, Zareiforoush H. Analysis of the combinative effect of ultrasound and microwave power on Saccharomyces cerevisiae in orange juice processing. INNOV FOOD SCI EMERG 2015. [DOI: 10.1016/j.ifset.2015.09.015] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Zareiforoush H, Minaei S, Alizadeh MR, Banakar A. Potential Applications of Computer Vision in Quality Inspection of Rice: A Review. Food Eng Rev 2015. [DOI: 10.1007/s12393-014-9101-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Alizadeh MR, Minaei S, Rahimi-Ajdadi F, Tavakoli T, Khoshtaghaza MH, Zareiforoush H. Flow Properties of Awned and De-Awned Paddy Grains Through a Horizontal Hopper Orifice. Particulate Science and Technology 2012. [DOI: 10.1080/02726351.2011.584128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Zareiforoush H, Komarizadeh M, Alizadeh M, Tavakoli H, Masoumi M. Effects of Moisture Content, Loading Rate, and Grain Orientation on Fracture Resistance of Paddy ( Oryza SativaL.) Grain. International Journal of Food Properties 2012. [DOI: 10.1080/10942911003754643] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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