Estimating Some Physical Properties of Sour and Sweet Cherries Based on Combined Image Processing and AI Techniques
-
Saeedeh Taghadomi-Saberi
and
Zahra Emam-Djomeh
Abstract
Physical properties of agricultural products are considered as important factors in optimization of storage conditions, packaging, transportation, water adsorption/desorption, heat, pesticides, and foodstuff moving out and also their breathing. This paper presents a time and cost economizing method to determine these important attributes of sour and sweet cherries by combining image processing and two common artificial intelligence techniques, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS). The measuring technique consisted of a charge-coupled device camera for image acquisition, fluorescent illuminants, capture card, and MATLAB for image analysis. Several networks were designed, trained, and generalized with a back-propagation algorithm using “trainlm” as training function. Several ANFIS models were designed with different number and type of membership functions (MFs) for each input. Generally, “gaussian” and “pi-shaped” MFs showed better results for estimating output variables among others. Considering statistical analysis, ANFIS showed better results than ANN.
Acknowledgment
The financial support provided by University of Tehran, Iran, under Grant No. 1305051/6/20, is gratefully acknowledged.
References
1. Anonymous. Countries by commodity 2011. Food and agriculture organization of the united nations, FAOSTAT. Available at: www.faostat.fao.org, 2011. Accessed:9 June 2013.Search in Google Scholar
2. MoredaGP, Ortiz-CañavateJ, García-RamosFJ, Ruiz-AltisentM. Non-destructive technologies for fruit and vegetable size determination – a review. J Food Eng2009;92:119–36.10.1016/j.jfoodeng.2008.11.004Search in Google Scholar
3. JordanRB, ClarkCJ. Sorting of kiwifruit for quality using drop velocity in water. Trans ASAE2004;47:1991–8.10.13031/2013.17787Search in Google Scholar
4. HoffmannT, FürllC, LudwigJ. A system for the on-line starch determination at potato tubers. In: Proceedings of the international conference on agricultural engineering (AgEng), Technologisch Instituut vzw, CD-ROM, 2004.Search in Google Scholar
5. EifertJD, SanglayGC, LeeDJ, SumnerSS, PiersonMD. Prediction of raw produce surface area from weight measurement. J Food Eng2006;74:552–6.10.1016/j.jfoodeng.2005.02.030Search in Google Scholar
6. OmidM, KhojastehnazhandM, TabatabaeefarA. Estimating volume and mass citrus fruits by image processing technique. J Food Eng2010;100:315–21.10.1016/j.jfoodeng.2010.04.015Search in Google Scholar
7. CostaC, AntonucciF, PallottinoF, AguzziJ, SunDW, ShapeMP. Analysis of agricultural products: a review of recent research advances and potential application to computer vision. Food Bioprocess Technol2011;4:673–92.10.1007/s11947-011-0556-0Search in Google Scholar
8. Taghadomi-SaberiS, OmidM, Emam-DjomehZ, AhmadiH. Estimation of sweet cherry antioxidant activity and anthocyanin content during ripening by artificial neural network assisted image processing technique. Int J Food Sci Technol2013;48:735–41.10.1111/ijfs.12021Search in Google Scholar
9. KhoshnamF, TabatabaeefarA, Ghasemi-VarnamkhastiM, BorgheiAM. Mass modelling of pomegranate (Punica granatum L.) Fruit with some physical characteristics. Sci Horticulturae-Amsterdam2007;114:21–6.10.1016/j.scienta.2007.05.008Search in Google Scholar
10. KhojastehnazhandM, OmidM, TabatabaeefarA. Determination of tangerine volume using image processing methods. Int J Food Properties2010;13:760–70.10.1080/10942910902894062Search in Google Scholar
11. BoydasMG, SayinciB, GozlekciS, OzturkI, ErcisliS. Basic physical properties of fruits in loquat (Eriobotrya Japonica) (Thunb. LINDL.) Cultivars and genotypes determined by both classical method and digital image processing. Afr J Agric Res2012;7:4171–81.10.5897/AJAR12.940Search in Google Scholar
12. SabliovCM, BoldorD, KeenerKM, FarkasBE. Imageprocessing method to determine surface area and volume of axi-symmetric agricultural products. Int J Food Properties2002;5:641–53.10.1081/JFP-120015498Search in Google Scholar
13. WangTY, NguangSK. Low cost sensor for volume and surface area computation of axisymmetric agricultural products. J Food Eng2007;79:870–7.10.1016/j.jfoodeng.2006.01.084Search in Google Scholar
14. KhojastehnazhandM, OmidM, TabatabaeefarA. Determination of orange volume and surface area using image processing technique. Int. Agrophys2009;23:237–42.Search in Google Scholar
15. PallottinoF, CostaC, AntonucciF, MenesattiP. Sweet cherry freshness evaluation through colorimetric and morphometric stem analysis: two refrigeration systems compared. Acta Alimentaria2013;42:428–36.10.1556/AAlim.42.2013.3.16Search in Google Scholar
16. LeeDJ, XuX, EifertJ, ZhanP. Area and volume measurements of objects with irregular shapes using multiple silhouettes. Opt Eng2006;45:1–10.10.1117/1.2166847Search in Google Scholar
17. MollazadeK, OmidM, ArefiA. Comparing data mining classifiers for grading raisins based on visual features. Comput Electron Agric2012;84:124–31.10.1016/j.compag.2012.03.004Search in Google Scholar
18. OmidM, MahmoudiA, OmidMH. An intelligent system for sorting pistachio nut varieties. Expert Syst Appl2009;36:11528–35.10.1016/j.eswa.2009.03.040Search in Google Scholar
19. MollazadeK, AhmadiH, OmidM, AlimardaniR. An intelligent model based on data mining and fuzzy logic for fault diagnosis of external gear hydraulic pumps. Insight2009;51:594–600.10.1784/insi.2009.51.11.594Search in Google Scholar
20. NaderiboldajiM, KhadivikhubA, TabatabaeefarA, Ghasemi VarnamkhastiM, ZamaniZ. Some physical properties of sweet cherry (Prunus avium L.) fruit. American-Eurasian J Agric Environ Sci2008;3:513–20.Search in Google Scholar
21. MAthWorks. Matlab user’s guide. The MAthWorks Inc,Massachusetts, USA: Natick, 2009.Search in Google Scholar
22. FuL, OkamotoH, KataokaT, ShibataY. Color based classification for berries of Japanese blue honeysuckle. Int J Food Eng2011;7:article 5.10.2202/1556-3758.2408Search in Google Scholar
23. OtsuN. A threshold selection method from gray-level histograms. IEEE T Syst MAN Cy1979;9:62–6.10.1109/TSMC.1979.4310076Search in Google Scholar
24. OmidM, BaharlooeiA, AhmadiH. Modelling drying kinetics of pistachio nuts with multilayer feed-forward neural network. Drying Technol2009;27:1069–77.10.1080/07373930903218602Search in Google Scholar
25. PeraltaJ, LiX, GutierrezG, SanchisA. Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm. Neural Comput Appl2013;22:11–20.10.1007/s00521-011-0741-0Search in Google Scholar
26. OmidM, MahmoudiA, OmidMH. Development of pistachio sorting system using principal component analysis (PCA) assisted artificial neural network (ANN) of impact acoustics. Expert Syst Appl2010;37:7205–12.10.1016/j.eswa.2010.04.008Search in Google Scholar
27. YalcinH, OzturkI, KaramanS, KisiO, SagdicO, KayacierA. Prediction of effect of natural antioxidant compounds on hazelnut oil oxidation by adaptive neuro-fuzzy inference system and artificial neural network. J Food Sci2011;76:1112–20.10.1111/j.1750-3841.2011.02139.xSearch in Google Scholar PubMed
28. SoltaniF, KerachianR, ShirangiE. Developing operating rules for reservoirs considering the water quality issues: application of ANFIS-based surrogate models. Expert Syst Appl2010;37:6639–45.10.1016/j.eswa.2010.03.057Search in Google Scholar
29. EkiciBB, AksoyUT. Prediction of building energy needs inearly stage of design by using ANFIS. Expert Syst Appl2011;38:5352–8.10.1016/j.eswa.2010.10.021Search in Google Scholar
30. NaderlooL, AlimardaniR, OmidM, SarmadianF, JavadikiaP, TorabiMY, et al. Application of ANFIS to predict crop yield based on different energy inputs. Measurement2012;45:1406–13.10.1016/j.measurement.2012.03.025Search in Google Scholar
31. MollazadeK, OmidM, AkhlaghianTabF, Rezaei-KalajY, MohtasebiSS, ZudeM. Analysis of texture-based features for predicting mechanical properties of horticultural products by laser light backscattering imaging. Comput Electron Agric2013;98:34–45.10.1016/j.compag.2013.07.011Search in Google Scholar
32. RongHJ, HanS, ZhaoGS. Adaptive fuzzy control of aircraft wing-rock motion. Appl Soft Comput2014;14:181–93.10.1016/j.asoc.2013.03.001Search in Google Scholar
33. Taghadomi-SaberiS, OmidM, Emam-DjomehZ, AhmadiH. Evaluating the potential of artificial neural network and neuro-fuzzy techniques for estimating antioxidant activity and anthocyanin content of sweet cherry during ripening by using image processing. J Sci Food Agric2014;94:95–101.10.1002/jsfa.6202Search in Google Scholar PubMed
34. LiaoTW. Diagnosis of bladder cancers with small sample size via feature selection. Expert Syst Appl2011;38:4649–54.10.1016/j.eswa.2010.09.135Search in Google Scholar
©2014 by De Gruyter
Articles in the same Issue
- Frontmatter
- Grinding Characteristics of Black Soybeans (Glycine max) at Varied Moisture Contents: Particle Size, Energy Consumption, and Grinding Kinetics
- Design and Development of Low-Cost Makhana Grading and Roasting Machine
- Investigation of Consecutive Fouling and Cleaning Cycles of Ultrafiltration Membranes Used for Whey Processing
- Kinetic Models of Evaporation and Total Phenolics Degradation during Pomegranate Juice Concentration
- Predicting Sorption Isotherms and Net Isosteric Heats of Sorption of Maize Grains at Different Temperatures
- Estimating Some Physical Properties of Sour and Sweet Cherries Based on Combined Image Processing and AI Techniques
- Functional Properties of Re-fabricated Rice as Affected by Die During Extrusion Process
- Isolation and Characterization of Corncob Cellulose Fibers using Microwave-Assisted Chemical Treatments
- Physical Properties of Red Guava (Psidium guajava L.) Pulp as Affected by Soluble Solids Content and Temperature
- Levels of Fluoride in the Ethiopian and Imported Black Tea (Camellia sinensis) Infusions Prepared in Tap and Fluoride-Rich Natural Waters
- Process Optimization and Quality Analysis of Carambola (Averrhoa carambola L.) Wine
- Physical Properties of Gluten-Free Bread Made of Corn and Chickpea Flour
- In Vitro Anti-tumor Effects of Chemically Modified Polysaccharides from Cherokee Rose Fruit
- Optimization of Ohmic Heating of Fish Using Response Surface Methodology
- Response Surface Modeling for Optimization of Textural and Color Characteristics of Dried Grapes
- Response Surface Analysis for Preparation of Modified Flours using Twin Screw Extrusion Cooking
- Modeling the Effects of the Quantity and Particle Size of Wheat Bran on Some Properties of Bread Dough using Response Surface Methodology
- Testing of a Condensation-type Heat Pump System for Low-temperature Drying Applications
- Comparison of Chemical, Textural and Organoleptic Properties of Pastry Sheets with Two Different Additives
Articles in the same Issue
- Frontmatter
- Grinding Characteristics of Black Soybeans (Glycine max) at Varied Moisture Contents: Particle Size, Energy Consumption, and Grinding Kinetics
- Design and Development of Low-Cost Makhana Grading and Roasting Machine
- Investigation of Consecutive Fouling and Cleaning Cycles of Ultrafiltration Membranes Used for Whey Processing
- Kinetic Models of Evaporation and Total Phenolics Degradation during Pomegranate Juice Concentration
- Predicting Sorption Isotherms and Net Isosteric Heats of Sorption of Maize Grains at Different Temperatures
- Estimating Some Physical Properties of Sour and Sweet Cherries Based on Combined Image Processing and AI Techniques
- Functional Properties of Re-fabricated Rice as Affected by Die During Extrusion Process
- Isolation and Characterization of Corncob Cellulose Fibers using Microwave-Assisted Chemical Treatments
- Physical Properties of Red Guava (Psidium guajava L.) Pulp as Affected by Soluble Solids Content and Temperature
- Levels of Fluoride in the Ethiopian and Imported Black Tea (Camellia sinensis) Infusions Prepared in Tap and Fluoride-Rich Natural Waters
- Process Optimization and Quality Analysis of Carambola (Averrhoa carambola L.) Wine
- Physical Properties of Gluten-Free Bread Made of Corn and Chickpea Flour
- In Vitro Anti-tumor Effects of Chemically Modified Polysaccharides from Cherokee Rose Fruit
- Optimization of Ohmic Heating of Fish Using Response Surface Methodology
- Response Surface Modeling for Optimization of Textural and Color Characteristics of Dried Grapes
- Response Surface Analysis for Preparation of Modified Flours using Twin Screw Extrusion Cooking
- Modeling the Effects of the Quantity and Particle Size of Wheat Bran on Some Properties of Bread Dough using Response Surface Methodology
- Testing of a Condensation-type Heat Pump System for Low-temperature Drying Applications
- Comparison of Chemical, Textural and Organoleptic Properties of Pastry Sheets with Two Different Additives
