Mathematical Models for Estimating the Mass of Plum Fruit by Selected Physical Properties

Yıl 2017, Cilt: 34 Sayı: 3, 82 - 90, 29.12.2017

Türker Saraçoğlu

https://doi.org/10.13002/jafag4304

Cited By: 1

Öz

Dimensional, optical properties and volume of agricultural products are the most important parameters in the design of postharvest equipment. In this study mass of plum fruit was estimated with using selected physical properties in linear and non-linear models. The result showed that the selected properties which were determined in this research such as length, width, thickness, geometric mean diameter, sphericity, mass, volume, projected areas and surface area values of Santa Rosa variety were significantly (p < 0.01) greater than for Can variety except for fruit density. For the practise applications, for estimating the mass of plum fruit, the thickness for Can and width for Santa Rosa can be used. The models based on projected are , R2=0.934, RMSE=0.891 for Can variety, , R2=0.961, RMSE=1.300 for Santa Rosa variety had highest R2 among the others, can be used. In third classification, the best model was obtained on the basis of the oblate spheroid volume as , R2= 0.981, RMSE=0.507 for Can variety and , R2=0.959, RMSE=1.326 for Santa Rose variety.

Anahtar Kelimeler

Plum fruit, physical properties, mass modelling

Kaynakça

• Altuntas E, Yaldiz M (2016). Physical, mechanical and chemical properties of plums (cv. Santa Rosa) affected by aminoethoxyvinylglycine applications. African Journal of Traditional, Complementary Alternative Medicines, 13:128-133.
• Berberoglu E, Altuntas E, Dulger E (2014). Development of adequate mathematical models to predict the mass of potato varieties from some physical attributes. Journal of Agricultural Faculty of Gaziosmanpasa University (JAFAG), 31: 1-11.
• Chakespari GA, Rajabipour A and Mobli H (2010). Mass modeling of two apple varieties by geometrical attributes. Australian Journal of Agricultural Engineering 1: 112-118.
• Çalışır S, Hacıseferoğulları H, Özcan M and Arslan D (2005). Some nutritional and technological properties of wild plum (Prunus spp.) fruits in Turkey. Journal of Food Engineering 66: 233–237
• Ertekin C, Gozlekci S, Kabas O, Sonmez S and Akinci I (2006). Some physical, pomological and nutritional properties of two plum (Prunus domestica L.) cultivars. Journal of Food Engineering 75: 508–514
• FAO (2017). FAO statistics data base on the world wide web. http://faostat.fao.org. (Accessed to web: 15.02.2017)
• Ghabel R, Rajabipour A, Ghasemi-Varnamkhasti M and Oveisi M (2010). Modeling the mass of Iran export onion (Allium cepa L.) varieties using some physical characteristics. Research in Agricultural Engineering 56: 33-40.
• Hassan-Beygi S R, Ghanbarian D and Farahmand M (2010). Prediction of saffron crocus corn mass by geometrical attributes. Scientia Horticulturae 124: 109–115.
• Jahromi MK, Jafari A, Rafiee S, Mirasheh R and Mohtasebi SS (2008). Mass modeling of date fruit (cv. Zahedi) with some physical characteristics. American-Eurasian Journal of Agricultural & Environmental Sciences 3: 127-131.
• Khanali M, Ghasemi Varnamkhasti M, Tabatabaeefar A and Mobli H (2007). Mass and volume modelling of tangerine (Citrus reticulate) fruit with some physical attributes. International Agrophysics 21: 329–334.
• Kheiralipour K, Tabatabaeefar A, Mobli H, Rafiee S, Rajabipour Jafari A and Mirzae A E (2010). Modeling of dropping time of kiwi fruit in water. International Journal of Food Properties 13: 1315-1322.
• Khoshnam F, Tabatabaeefar A, Ghasemi Varnamkhasti M and Borghei A (2007). Mass modeling of pomegranate (Punica granatum L.) fruit with some physical characteristics. Scientia Horticulturae 114: 21–26
• Lorestani AN and Tabatabaeefar A (2006). Modeling the mass of kiwi fruit by geometrical attributes. International Agrophysics 20: 135–139.
• Mohsenin NN (1986). Physical Properties of Plant and Animal Materials. Gordon and Breach Science Publishers, New York
• Naderi-Boldaji M, Fattahi R, Ghasemi Varnamkhasti M, Tabatabaeefar A and Jannatizadeh A (2008). Models for predicting the mass of apricot fruits by geometrical attributes (cv. Shams Nakhjavan, and Jahangiri). Scientia Horticulturae 118: 293–298.
• Omid M, Khojastehnazhand M and Tabatabaeefar A (2010). Estimating volume and mass of citrus fruits by image processing technique. Journal of Food Engineering 10: 315–321.
• Rashidi M and Seyfi K (2008). Modeling of kiwi fruit mass based on outer dimensions and projected areas. American-Eurasian Journal of Agricultural and Environmental Sciences 3: 26-29.
• Seyedabadi E, Khojastehpourb M, Sadrniab H and Saiedirad M H 2011. Mass modeling of cantaloupe based on geometric attributes: A case study for Tile Magasi and Tile Shahri. Scientia Horticulturae 130: 54-59.
• Shahi-Gharahlar A, Yavari A R and Khanali M (2009). Mass and volume modeling of loquat (Eriobotrya japonica Lindl.) fruit based on physical characteristics. Journal of Fruit and Ornamental Plant Research 17: 175-189.
• Son L (2010). Determination on quality characteristics of some important Japanese plum (Prunus salicina Lindl.) cultivars grown in Mersin-Turkey. African Journal of Agricultural Research 5: 1144–1146.
• Spreer W and Müller J (2011). Estimating the mass of mango fruit (Mangifera indica, cv. Chok Anan) from its geometric dimensions by optical measurement. Computers and Electronics in Agriculture 75: 125-131.
• Tabatabaeefar A and Rajabipour A (2005). Modeling the mass of apples by geometrical attributes. Scientia Horticulturae 105: 373–382.
• Taheri-Garavand, A and Nassiri A (2010). Study on some morphological and physical characteristics of sweet lemon used in mass models. International Journal of Environmental Sciences 1: 580-590.
• TUIK, 2017. TUIK statistics database on the world wide web. www.tuik.gov.tr/PreTablo.do?alt_id=1001. (Accessed to web: 05.05.2017)