Analysis of Some Factors Affecting the Growth of Castor Shrub and Suitability of its Seed Oil in Industrial Application

Some concern had been shown regarding the limited availability of castor seed to satisfy the rising yearning for its seed oil for use in industrial and domestic applications. This growing demand calls for refocus on backward integration in order to ensure sustained supply chain. This study adopts a factorial analysis that involves the use of Principal Component Analysis (PCA) and Kendall’s Coefficient of Concordance (KCC) as statistical procedures to analyze some critical factors affecting the growth of castor shrub and its seed. KCC analyzed the degree of agreement among the fifteen Judges who ranked the thirty-two identified variables affecting the growth of castor shrub and the suitability of its seed oil in industrial application in descending order of importance. The result of the KCC showed an index of concordance in ranking as indicating 61% agreement among the 15 judges. The PCA helped to analyze the Judges responses arranged in form of data matrix that was facilitated by the use of statistiXL software. The PCA result revealed significant parsimony in data reduction from thirty-two to four principal factors creatively labeled: Seed oil particularities, Resource Conversion Efficiency, Plant-cooperation-oriented yield and Soil Condition respectively. The implication of this is that the principal factors that influence the growth of castor shrub and the suitability of its seed oil in industrial application has been identified.

Keywords:

Castor Shrub, , Backward Integration, Castor Seed, Growth Variables,

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Anderson, S.L., Rovnyak, D., Strein, T.G. (2017). Identification of Edible oils by Principal Component Analysis of HNMR Spectra. J. Chem. Educ. 97 (9), pp.1377-1382 Doi: https://doi.org/10.1021/acs.jchemed.7b00012
Baran, A.J., Newman, S.M. (2017). On the application of principal component analysis to the calculation of the bulk integral optical properties for radiation parameterizations in climate models. Optics Letters, Vol. 42, Issue 5, pp. 983-986. Doi: https://doi.org/10.1364/OL.42.000983
Berman, P., Nizri, S., Wiesman, Z. (2011). Castor oil biodiesel and its blends as alternative fuel. Biomass Bioenergy, 35(7):2861–2866. Doi: https://doi.org/10.1016/j.biombioe.2011.03.024
Calegari, E.P., Porto, J.S., Nejeliski, D.M., da Cunha, D.L., de Oliveira, B.F. (2017). Experimental study on waterproofing MDF with castor oil-based vegetal polyurethane, revista Matéria, v.22, n.3. Doi: https://doi.org/10.1590/S1517-707620170003.0211
da Silva César, N., Otávio Batalha, M. (2010). Biodiesel production from castor oil in Brazil: a difficult reality. Energy Policy, 38(8):4031–4039. Doi: https://doi.org/10.1016/j.enpol.2010.03.027
Goodarzi, F., Darvishzadeh, R., Hassani, A., Hassanzaeh, A. (2011). Study on genetic variation in Iranian castor bean (Ricinus Communis L) accessions using multivariate statistical techniques. Journal of medicinal plants Research, Vol. 5 (21), pp. 5254-5261. Doi: https://doi.org/10.5897/JMPR.9001165
Hall, J., Matos, S., Severino, L., Beltrão, N. (2009). Brazilian biofuels and social exclusion: established and concentrated ethanol versus emerging and dispersed biodiesel. J Clean Prod. 17 (suppl. 1):S77–S85. Doi: https://doi.org/10.1016/j.jclepro.2009.01.003
Igboanugo, A.C., Bello, K.A., Chiejine, C.M. (2016). A factorial study of fibre cement roofing sheet manufacturing. Journal of Multidisciplinary Engineering Science and Technology (JMEST), Vol.3, Issue 2 pp.3885-3892.
Jolliffe, I.T. (2012). Principal component analysis. New York: Springer, 487.
Karthik, D., Vijayarekha, K., Manickkam, V. (2014). A simple method for detecting adulteration in sunflower oil using chemometry. Rasayan J. Chem.Vol.7, No 1: 99-103. [Google Scholar] Kongbonga, Y.G.M., Ghalila, H., Onana, M.B., Majdi, Y., Lakhdar, Z.B., Mezlini, H., Sevestre-Ghalila, S. (2011). Characterization of vegetable oils by fluorescence spectroscopy. Food Nutr Sci 2:692-699.
Lima, R.L.S., Severino, L.S., Sampaio, L.R., Sofiatti, V., Gomes, J.A., Beltrão, N.E.M. (2011) Blends of castor meal and castor husks for optimized use as organic fertilizer. Ind Crops Prod. 33(2):364–368.
Meira, M., Quintella, C.M., Ferrer, T.M., Goncalves, H.R., Kamei, A.G., Santos, M.A., Costa Neto, P.R., Pepe, I.M. (2016). Identification of Vegetable Oil or Biodiesel Added to Diesel Using Fluorescence Spectroscopy and Principal Component Analysis (PDF Download Available). Retrieved from https://www.researchgate.net/publication/259636298_Identification_of_Vegetable_Oil_or_Biodiesel_Added_to_Diesel_Using_Fluorescence_Spectroscopy_and_Principal_Component_Analysis [accessed Sep 16, 2017]. Nova 34:621–624.
Mubofu (2016) Castor oil as a potential renewable resource for the production of functional Materials. Sustain Chem Process 4:11, pp.1-12.
Mueller, D., Ferrao, M.F., Marder, L., da costa, A.B. (2013). Fourier transforms infrared spectroscopy (FTIR) and multivariate analysis for identification of different vegetable oils used in biodiesel production. Sensors (Besel), 13(4254-4271). Doi: https://doi.org/10.3390/s130404258
Placide, R., Shimelis, H., Laing, M., Gahakwa, D. (2015). Application of principal component analysis to yield and yield related traits to identify sweet potato breeding parents. Trop. Agric. (Trinidad), Vol. 92 No. 1, pp 1-15.
Pommerening, A., Muszta, A. (2015). Methods of modelling relative growth rate. Forest Ecosystems 2:5, pp. 1-9.
Scott, S.M., James, D., Ali, Z., O’Hare, W.T., Rowell, F.J. (2003). Total luminescence spectroscopy with pattern recognition for classification of edible oils. Analyst 128(7):966-973. Doi: https://doi.org/10.1039/B303009A
Severino, S.L., Auld, D.L., Baldanzi, M., Cândido, M.J.D., Chen, G., Crosby, W. (2012a). A review on the challenges for increased production of castor. Agron. J., 104:853–880. Doi: https://doi.org/10.2134/agronj2011.0210
Shojaeefard, M.H., Etgahni, M.M., Meisami, F., Barari, A. (2013) Experimental investigation on performance and exhaust emissions of castor oil biodiesel from a diesel engine. Environ Technol. 34(13–16):2019–2026. Doi: https://doi.org/10.1080/09593330.2013.777080
Thakur, S., Karak, N. (2013). Castor oil-based hyperbranched polyurethanes as advanced surface coating materials. Prog. Org. Coat. 76(1):157–164. Doi: https://doi.org/10.1016/j.porgcoat.2012.09.001
Tomazzoni, G., Meira, M., Quintella, C.M., Zagonel, G.F., Costa, B.J., de Oliveira, P.R., Pepe, I.M., Neto. (2013). Identification of vegetable oil or biodiesel added to diesel using Fluorescence spectroscopy and principal component analysis. J.Am. Oil.Chem. Soc. Doi: https://doi.org/10.1007/S11746-013-2354-5
Trevino, A.S., Trumbo, D.L. (2002). Acetoacetylated castor oil in coatings applications. Prog Org Coat. 44(1): 49–54. Doi: https://doi.org/10.1016/S0300-9440(01)00223-5
Vanaja, M., Jyothi, M., Ratnakumar, P., Vagheera, P., Raghuram Reddy, P., Jyothi Lakshmi, N., Yadav, S.K., Maheshwari, M., Venkateswarlu, B. (2015). Growth and yield responses of castor bean(Ricinus communis L.) to two enhanced CO2 levels. Plant Soil Environ., 54, 2008 (1): 38–46.
Wang, M.L., Dzievit, M., Chen, Z., Morris, J.B., Norris, J.E, Barkley, N.A., Tonnis, B., Pederson, G.A., Yu, J. (2017). Genetic diversity and population structure of castor (Ricinus communis L.) germplasm within the US collection assessed with EST-SSR markers. Genome, Vol. 60, No. 3: pp. 193-200. Doi: https://doi.org/10.1139/gen-2016-0116

International Journal of Agriculture Environment and Food Sciences-Cover

Yayın Aralığı: Yılda 4 Sayı
Başlangıç: 2017
Yayıncı: Gültekin ÖZDEMİR

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