Research Article
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Year 2021, Volume: 5 Issue: 3, 335 - 342, 15.09.2021
https://doi.org/10.31015/jaefs.2021.3.11

Abstract

References

  • 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

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

Year 2021, Volume: 5 Issue: 3, 335 - 342, 15.09.2021
https://doi.org/10.31015/jaefs.2021.3.11

Abstract

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.

References

  • 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
There are 24 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering (Other)
Journal Section Research Articles
Authors

Ayodeji Omotehinse 0000-0002-5036-0800

Publication Date September 15, 2021
Submission Date July 13, 2020
Acceptance Date April 16, 2021
Published in Issue Year 2021 Volume: 5 Issue: 3

Cite

APA Omotehinse, A. (2021). Analysis of Some Factors Affecting the Growth of Castor Shrub and Suitability of its Seed Oil in Industrial Application. International Journal of Agriculture Environment and Food Sciences, 5(3), 335-342. https://doi.org/10.31015/jaefs.2021.3.11


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