Estimation of the Weights of Almond Nuts Based on Physical Properties through Data Mining
Quality attributes are the major parameters designating market values of the agricultural goods and commodities. Several practices are applied to improve quality parameters of the fruits and vegetables. Such quality attributes should also be estimated through various approaches before to design of equipment and tools used in handling and processing of these goods and to design storage facilities. Data mining is a novel approach used to estimate various attributes or quality parameters of the fruits from previously measured attributes. Different algorithms embedded into data mining operations may yield quite accurate and reliable equations for estimation of quality attributes. Almond is a significant cash crop for growers. Since almond is quite tolerant to droughts and salinity, it is preferred in various parts of the country by producers. Weight is the primary quality parameter designating market value of the almonds. This study was conducted to estimate nut weights of seven different almond varieties and to develop an equation for the estimation of nut weights. Data mining approach was used to estimate nut weights from physical fruit quality attributes (kernel length, width, thickness, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, shape index and aspect ratio). Present findings revealed quite significant, accurate and practicable rules to estimate the nut weights of different almond varieties. It was concluded that data mining could be used as a reliable tool to estimate the nut weights of different almond varieties from the physical attributes of the fruits.
Arslan S, Vursavus KK (2008). Physico-mechanical properties of almond nut and its kernel as a function of variety and moisture content. The Philippine Agricultural Scientist 91(2):171-179.
Dash M, Liu H (1997). Feature Selection for Classification. Intelligent Data Analysis 1(3):131-156.
Demir B, Gurbuz F, Eski I, Kus ZA, Yilmaz KU, Ercisli S (2018a). Possible use of data mining for analysis and prediction of apple physical properties. Erwerbs-Obstbau 60(1):1-7.
Demir B, Gürbüz F, Eski I, Kus ZA (2018b). Data mining approach for prediction of fruit color properties. Atatürk University Journal of the Agricultural Faculty 49(1):37-43.
Ercisli S (2004). A short review of the fruit germplasm resources of Turkey. Genetic Resources and Crop Evolution 51(4):419-435.
Ercisli S, Sayinci B, Kara M, Yildiz C, Ozturk I (2012). Determination of size and shape features of walnut (Juglans regia L.) cultivars using image processing. Scientia Horticulturae 133:47-55.
FAO (2016). Food and Agriculture Organization of the United Nations Statistics. http://www.fao.org/faostat/en/#data/QC.
Gupta RK, Das SK (1997). Physical properties of sunflower seed. Journal of Agricultural Engineering Research 66(1):1-8.
Guyon I, Elisseeff A (2003). An introduction to variable and feature selection. Journal of Machine Learning Research 3:1157-1182.
Gurbuz F, Ozbakir L, Yapici H (2009). Classification rule discovery for the aviation incidents resulted in fatality. Knowledge-Based Systems 22(8):622-632.
Imani A, Shamili M (2018). Almond nut weight assessment by stepwise regression and path analysis. International Journal of Fruit Science doi:10.1080/15538362.2017.1422450.
Khoshnam F, Tabatabaeefar A, Varnamkhasti M G, Borghei A (2007). Mass modeling of pomegranate (Punica granatum L.) fruit with some physical characteristics. Scientia Horticulturae 114(1):21-26.
Kodad O, Company RS, Alonso J M (2018). Genotypic and Environmental Effects on Tocopherol Content in Almond. Antioxidants doi:10.3390/antiox7010006.
Lorestani AN, Tabatabaeefar A (2006). Modelling the mass of kiwi fruit by geometrical attributes. International Agrophysic 20(2):135-139.
Maione C, Silva de Paula E, Gallimberti M, Batista BL, Campiglia AD, Barbosa F Jr, Barbosa RM (2016). Comparative study of data mining techniques for the authentication of organic grape juice based on ICP-MS analysis. Expert Systems with Applications 49:60-73.
McCabe WL, Smith JC, Harriot P (1986). Unit operations of chemical engineering. McGraw-Hill Book Co., New York.
Megaputer Intelligence Inc (2004). PolyAnalyst 5 Users Manual. Bloomington, IN 47404.
Mohsenin NN (1986). Physical properties of plant and animal materials. Structure, physical characteristics and mechanical properties. Gordon and Breach Science Publishers, New York.
Monagas M, Garrido I, Lebrón-Aguilar R, Bartolome B, Gómez-Cordovés C (2007). Almond (Prunus dulcis (Mill.) DA Webb) skins as a potential source of bioactive polyphenols. Journal of Agricultural and Food Chemistry 55(21):8498-8507.
Mpotokwane SM, Gaditlhatlhelwe E, Sebaka A, Jideani VA (2008). Physical properties of bambara groundnuts from Botswana. Journal of Food Engineering 89(1):93-98.
Muhammad S, Muhammad ZK (2016). A method of data mining for selection of site for wind turbines. Renewable and Sustainable Energy Reviews 55:1225-1233.
Naderi-Boldaji M, Fattahi R, Ghasemi-Varnamkhasti M, Tabatabaeefar A, Jannatizadeh A (2008). Models for predicting the mass of apricot fruits by geometrical attributes (cv. Shams, Nakhjavan, and Jahangiri). Scientia Horticulturae 118(4):293-298.
Omid M, Khojastehnazhand M, Tabatabaeefar A (2010). Estimating volume and mass of citrus fruits by image processing technique. Journal of food Engineering 100(2):315-321.
Piscopo A, Romeo F V, Petrovicova B, Poiana M (2010). Effect of the harvest time on kernel quality of several almond varieties (Prunus dulcis (Mill.) DA Webb). Scientia Horticulturae 125(1):41-46.
Rashidi M, Keshavarzpour F (2011). Prediction of Tangerine Mass Based on Geometrical Properties. Academic Journal of Plant Sciences 4(4):98-104.
Rasouli M, Mollazade K, Fatahi R, Zamani Z, Imani A, Martínez-Gómez P, Ebadi A (2010). Evaluation of engineering properties in almond nuts. International Journal of Natural & Engineering Sciences 4(1):17-26.
Rathod RR, Garg RD (2016). Regional electricity consumption analysis for consumers using data mining techniques and consumer meter reading data. International Journal of Electrical Power & Energy Systems 78:368-374.
Sayinci B, Ercisli S, Akbulut M, Savsatli Y, Baykal H (2015). Determination of shape in fruits of cherry laurel (Prunus laurocerasus) accessions by using elliptic Fourier analysis. Acta Scientiarum Polonorum Hortorum Cultus 14:63-82.
Schulze K, Nagle M, Spreer W, Mahayothee B, Müller J (2015). Development and assessment of different modeling approaches for size-mass estimation of mango fruits (Mangifera indica L., cv. ‘Nam Dokmai’). Computers and Electronics in Agriculture 114:269-276.
Shahbazi F, Rahmati S (2013). Mass modeling of sweet cherry (Prunus avium L.) fruit with some physical characteristics. Food and Nutrition Sciences 4(1):1-5.
Sivaci A, Duman S (2014). Evaluation of seasonal antioxidant activity and total phenolic compounds in stems and leaves of some almond (Prunus amygdalus L.) varieties. Biological Research 47(1):1-5.
Soares JDR, Pasqual M, Lacerda WS, Silva SO, Donato SLR (2013). Utilization of artificial neural networks in the prediction of the bunches’ weight in banana plants. Scientia Horticulturae 155:24-29.
Sorkheh K, Shiran B, Khodambshi M, Rouhi V, Ercisli S (2011). In vitro assay of native almond species (Prunus L. spp.) for drought tolerance. Plant Cell, Tissue and Organ Culture 105(3):395-404.
Tabatabaeefar A, Vefagh-Nemotolahee A, Rajabipour A (2000). Modeling of orange mass based on dimensions. Journal of Agricultural Science and Technology 2:299-305.
Tintarev N, Masthoff J (2011). Designing and evaluating explanations for recommender systems. In: Recommender Systems Handbook. Springer, Boston, MA.
Vishwakarma RK, Shivhare US, Nanda SK (2012). Physical properties of guar seeds. Food and Bioprocess Technology 5(4):1364-1371.
Vivek Venkatesh G, Iqbal S M, Gopal A, Ganesan D (2015). Estimation of volume and mass of axi-symmetric fruits using image processing technique. International Journal of Food Properties 18(3):608-626.
Open Access Journal:
The journal allows the author(s) to retain publishing rights without restriction. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author.