Volume 3, Issue 4, July 2018, Page: 65-71
Forecasting of Cashew Area Harvested, Yield and Production Using Trend Analysis
Okeke Daniel Chukwujioke, Department of Agricultural Science Education, Nwafor Orizu College of Education, Nsugbe, Nigeria
Akarue Blessing Okiemute, Department of Agricultural Science Education, College of Education, Warri, Nigeria
Received: Apr. 18, 2018;       Accepted: Jun. 20, 2018;       Published: Jul. 7, 2018
DOI: 10.11648/j.ijae.20180304.11      View  981      Downloads  115
Abstract
The study was conducted to examine the trend analysis of area, yield and production for Cashew in Nigeria. The findings of the study are based on data from the years (1961 to 2016) and was taken from the database of FAO (2018). Three Models of trend analysis were applied. The models were Linear Trend Model, Quadratic Trend Model, and cubic trend Model. The most appropriate Model for trend analysis of the present study was Cubic Trend Model based on the highest R2 of (95.76 %), (95.76%) and (88.12%) for cashew area harvested, production and yield respectively, coupled with the lowest residual sum square and mean square error. Forecasting of the data was done up to 2026. The forecasted values were area harvested (409459.07ha -486296.12), yield (24272.09hg/ha – 27422.91hg/ha) and production (990382.68tons-1.127E+06). The study presents an insight to national policy makers regarding this essential crop and provides them with a reference range of values in area harvested, yield and production in future so that they may be able to effectively deal with cashew production in Nigeria.
Keywords
Cashew, Area Harvested, Yield, Production, Cubic Trend Model, RSS, MSE, Nigeria
To cite this article
Okeke Daniel Chukwujioke, Akarue Blessing Okiemute, Forecasting of Cashew Area Harvested, Yield and Production Using Trend Analysis, International Journal of Agricultural Economics. Vol. 3, No. 4, 2018, pp. 65-71. doi: 10.11648/j.ijae.20180304.11
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
ABBASI, S. S., TAHIR A, RAZA, I, ABID, S & KHAN. MN. (2015) Trend analysis and forecasting of wheat and rice prices in Pakistan. Pakistan Journal of Agricultural Research 26(3) 310-317
[2]
AGBOOLA, A. A. (2012). Essentials of Agricultural Production in Nigeria. Greenline Publishers, Ado-Ekiti, Nigeria pp. 1-2.
[3]
ASSIS, K., AMRAN, A., & REMALI, Y. (2010). Forecasting cocoa bean prices using univariate time series models. Journal of Arts Science and Commerce, 144 (1), 71-80.
[4]
BOKEN, V. K. (2000) Forecasting spring wheat yield using time series analysis: A case study for the Canadian Prairies. Agron. J. 92(6): 1047-1053.
[5]
DHAKRE AND AMOD SHARMA (2009) Growth and instability analysis of ginger production in North-east: region. Agricultural Situation in India. 463-465.
[6]
FAOSTAT (2018) Food and Agriculture Organization of the United Nations. www.fao.org/faostat/en/?
[7]
FINGER, R. (2007), Evidence of slowing yield growth the example of Swiss cereal yield. Agri-Food and Agri-Environmental Economics Group, ETH Zurich, Switzerland.
[8]
HAMMED, L. A., ANIKWE, J. C & ADEDEJI, A. R (2008) Cashew nuts and production development in Nigeria. American –Eurasian Journal of scientific research 3(1)54-61.
[9]
IBRAHIM, F. D., MOHAMMED, U. S, NMADU, J. N, YAKBU, I. T AND IBRAHIM P. A (2010) Forecasting and Growth trend of sugarcane production: meeting the goals of commercial agriculture in Nigeria. A paper presented at the Nigeria Association of Agricultural Economics
[10]
KARIM, M. R., M. A. AWAL AND M. AKTER, (2010). Forecasting of wheat production in Bangladesh. Bangladesh Journal of Agricultural. Research, 35: 17-28.
[11]
KHIN, A. A., EDDIE, C. F. C., SHAMSUNDIN, M. N., & MOHAMED, Z. A. (2008, June 15-19).Natural]Price Forecasting in the World Market, Agricultural Sustainability Through Participate Global Extension, University Putra Malaysia, Kuala Lumpur, Malaysia
[12]
NAZIR, M, AKHTAR W, AKMAL N AND BATOOL, S. (2016) Export forecasting of major fruit crops of Pakistan Science, Technology and Development 35(4) 148-152
[13]
OLAGUNJU, F. I (2015) Comparative Advantage and Competitiveness of Cashew Crop in Nigeria: The Policy Analysis Matrix. International Journal of Agriculture and Economic Development, 3(1), 1-14.
[14]
RAJAN, M. S., PALANIVEL, M., & MOHAN, S K. (2015) Forecasting of Cotton Area, Production and Productivity using Trend analysis. International Journal for Research in Applied Science & Engineering Technology (IJRASET) 3 (XII) 516-520.
[15]
RAMAKRISHNA, G. MUKHERJEE, D. N., SRIKANTH, B AND BHAVE, M. HV (2014). Modelling rice production and forecasting in Andhra Pradesh. progressive Research 9 (conf. sept) 1200 – 1203
[16]
RIMI, R. H., S. H. RAHMAN, S. KARMAKAR AND S. G. HUSSAIN, 2009. Trend analysis of climate change and investigation on its probable impacts on rice production at Sathkhira, Bangladesh. Pakistan Journal of Meteorology, 6:37-50.
[17]
SANDIP S. (2013) Trend analysis and forecasting coconut production in Assam. Journal of plantain crops. 41(2) 238-241
[18]
SRINIVASA RAO, V AND SRINIVASULU, R. (2006). Growth comparisons of turmeric up to 2020 AD. The Andhra Agricultural Journal. 53(1&2): 108-109.
[19]
TAHIR, A. S & AMRAN, A (2013), forecasting of maize area and production in Pakistan. E Sci Journal of Crop Production. 02 (02). 44-48.
[20]
TUNJI, A. (2013). Farmer’s Response to Agricultural Prices in India: A study in decision making, Heritage Publishers.
Browse journals by subject