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. 2017 Dec 19;16:1025–1033. doi: 10.1016/j.dib.2017.12.039

Average crop yield (2001–2017) in Ethiopia: Trends at national, regional and zonal levels

Logan Cochrane a,, Yeshtila W Bekele b
PMCID: PMC5758922  PMID: 29326965

Abstract

This article presents average agricultural yield data per hectare for key cereal, legume and root crops from 2001 until 2017. Data was obtained from the annual Agricultural Sample Surveys of the Central Statistics Agency (CSA) of Ethiopia. We present data at national, regional (SNNPRS) and zonal (Wolaita) levels. The data shows that average yields for all crops, at all levels, show increasing trends during the time period. Data for the main cereal crops is consistent and aligns with literature relatively well, however we raise questions about the root crop data in an effort to encourage greater critical reflection of components of data from the CSA.

Keywords: Ethiopia, Agriculture, Yield data, Trends, Accuracy, Quality


Specification Table

Subject area Agriculture
More specific subject area Crop yield data
Type of data Figures and tables
How data was acquired Data were obtained from the annual Agricultural Sample Surveys of the Central Statistics Agency of Ethiopia.
Data format Analyzed
Experimental factors Data used in this article were obtained from the Central Statistics Agency of Ethiopia, with reference to available literature.
Experimental features Tables and graphic trends of analysis were employed.
Data source location Ethiopia
Data accessibility The data are with this article.

Value of the data

  • Average agricultural data are presented for key cereal, legume and root crops from 2001 to 2017.

  • The data can be used by researchers and policy makers to analyze the implications of agriculture products on food security and poverty reduction.

  • Average yields for all crops, at all levels, show increasing trends, with cereals doing so progressively and root crops increasing rapidly in recent years.

  • Based upon some components of the governmental data, questions are raised about accuracy, encouraging researchers to be more critical when utilizing these data sets.

1. Data

The figures and tables of agricultural data were obtained from the annual Agricultural Sample Surveys of the Central Statistics Agency (CSA) [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], covering the time period of 2001 until 2017. The CSA is the only provider of data at this scale. Average yields for all crops, at all levels, show increasing trends, with cereals doing so progressively and root crops increasing rapidly in recent years (Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5). All the data is presented on a year-by-year basis in Table 1, Table 2, Table 3, enabling ease of re-analysis. However, there are general concerns about the quality, methodologies, and politicization of data produced by central statistics agencies [14]. We present data at national, regional (Southern Nations, Nationalities and Peoples’ regional state; SNNPRS) and zonal (Wolaita) scales. The data for the major cereals (teff and maize) is relatively consistent with the literature, whereas the shifts as well as contrasts with the literature in root crops raise questions about components of the agricultural data. For example,

  • 1)

    In the 2012/13 season yields per hectare of taro and sweet potato tripled, according to CSA personnel this was due to methodological changes (Tables 4–5) [15];

  • 2)

    Data for sweet potato are stable in SNNPRS from 2007 to 2011, but during this period sweet potato virus infection was high, affecting roots, weights and cuttings yet no decline was recorded (Table 5) [16];

  • 3)

    During the 2007/08 season a higher yielding variety of taro was introduced with high adoption rates but no increase was recorded in the years that followed (Table 4) [15];

Fig. 1.

Fig. 1

National, Regional and Zonal Average Teff Yield (Qt per Ha).

Fig. 2.

Fig. 2

National, Regional and Zonal Average Maize Yield (Qt per Ha).

Fig. 3.

Fig. 3

National, Regional and Zonal Average Haricot Bean (Qt per Ha).

Fig. 4.

Fig. 4

National, Regional and Zonal Average Taro Yield (Qt per Ha).

Fig. 5.

Fig. 5

National, Regional and Zonal Average Sweet Potato Yield (Qt per Ha).

Table 1.

Ethiopia Yields by Crop (Qt per Ha).

Year Crop Yield
2001/02 Teff 8.95
2003/04 Teff 8.43
2004/05 Teff 9.48
2005/06 Teff 9.69
2006/07 Teff 10.14
2007/08 Teff 11.67
2008/09 Teff 12.2
2009/10 Teff 12.28
2010/11 Teff 12.62
2011/12 Teff 12.81
2012/13 Teff 13.79
2013/14 Teff 14.65
2014/15 Teff 15.75
2015/16 Teff 15.60
2001/02 Maize 21.16
2003/04 Maize 18.6
2004/05 Maize 17.19
2005/06 Maize 21.87
2006/07 Maize 22.29
2007/08 Maize 21.22
2008/09 Maize 22.24
2009/10 Maize 21.99
2010/11 Maize 25.4
2011/12 Maize 29.54
2012/13 Maize 30.59
2013/14 Maize 32.54
2014/15 Maize 34.31
2015/16 Maize 33.87
2001/02 Haricot Beans 8.23
2003/04 Haricot Beans 9.37
2004/05 Haricot Beans 8.61
2005/06 Haricot Beans 8.46
2006/07 Haricot Beans 9.97
2007/08 Haricot Beans 10.43
2008/09 Haricot Beans 12.35
2009/10 Haricot Beans 14.87
2010/11 Haricot Beans 14.34
2011/12 Haricot Beans 11.69
2012/13 Haricot Beans 12.62
2013/14 Haricot Beans 14.15a
2014/15 Haricot Beans 15.92a
2015/16 Haricot Beans 14.85a
2001/02 Taro 79.93
2003/04 Taro 78.39
2004/05 Taro 79.69
2005/06 Taro 68.50
2006/07 Taro 77.43
2007/08 Taro 75.29
2008/09 Taro 75.45
2009/10 Taro 77.78
2010/11 Taro 80.37
2011/12 Taro 79.41
2012/13 Taro 270.4
2013/14 Taro 279.8
2014/15 Taro 297.81
2015/16 Taro 249.61
2001/02 Sweet Potato 99.67
2003/04 Sweet Potato 105.91
2004/05 Sweet Potato 99.42
2005/06 Sweet Potato 81.40
2006/07 Sweet Potato 73.06
2007/08 Sweet Potato 84.43
2008/09 Sweet Potato 79.48
2009/10 Sweet Potato 84.31
2010/11 Sweet Potato 90.13
2011/12 Sweet Potato 76.03
2012/13 Sweet Potato 284.64
2013/14 Sweet Potato 334.04
2014/15 Sweet Potato 456.56
2015/16 Sweet Potato 334.39
a

CSA began dividing white and red haricot beans in 2013/14, the figures used are an average of the two.

Table 2.

SNNPRS Yields by Crop (Qt per Ha).

Year Crop Yield
2003/04 Teff 6.54
2004/05 Teff 7.76
2005/06 Teff 7.53
2006/07 Teff 7.80
2007/08 Teff 9.89
2008/09 Teff 10.77
2009/10 Teff 11.88
2010/11 Teff 11.18
2011/12 Teff 11.40
2012/13 Teff 12.43
2013/14 Teff 12.62
2014/15 Teff 13.7
2015/16 Teff 13.08
2003/04 Maize 17.8
2004/05 Maize 15.21
2005/06 Maize 16.27
2006/07 Maize 19.73
2007/08 Maize 17.67
2008/09 Maize 18.85
2009/10 Maize 19.33
2010/11 Maize 23.45
2011/12 Maize 27.57
2012/13 Maize 28.57
2013/14 Maize 31.18
2014/15 Maize 32.23
2015/16 Maize 30.75
2003/04 Haricot Beans 7.31
2004/05 Haricot Beans 7.89
2005/06 Haricot Beans 8.35
2006/07 Haricot Beans 9.26
2007/08 Haricot Beans 9.05
2008/09 Haricot Beans 9.87
2009/10 Haricot Beans 15.68
2010/11 Haricot Beans 13.82
2011/12 Haricot Beans 10.81
2012/13 Haricot Beans 11.44
2013/14 Haricot Beans 12.18a
2014/15 Haricot Beans 15.56a
2015/16 Haricot Beans 15.18a
2003/04 Taro 80.87
2004/05 Taro 80.40
2005/06 Taro 72.47
2006/07 Taro 81.03
2007/08 Taro 81.11
2008/09 Taro 79.77
2009/10 Taro 80.88
2010/11 Taro 83.65
2011/12 Taro 83.10
2012/13 Taro 274.84
2013/14 Taro 283.72
2014/15 Taro 302.61
2015/16 Taro 259.87
2003/04 Sweet Potato 108.2
2004/05 Sweet Potato 103.01
2005/06 Sweet Potato 102.12
2006/07 Sweet Potato 86.83
2007/08 Sweet Potato 98.72
2008/09 Sweet Potato 96.17
2009/10 Sweet Potato 101.78
2010/11 Sweet Potato 102.84
2011/12 Sweet Potato 74.08
2012/13 Sweet Potato 199.55
2013/14 Sweet Potato 228.92
2014/15 Sweet Potato 264.14
2015/16 Sweet Potato 223.19
a

CSA began dividing white and red haricot beans in 2013/14, the figures used are an average of the two.

Table 3.

Wolaita Yields by Crop (Qt per Ha).

Year Crop Yield
2003/04 Teff 5.54
2004/05 Teff 5.59
2005/06 Teff 8.43
2006/07 Teff 8.76
2007/08 Teff 7.78
2008/09 Teff 10.33
2009/10 Teff
2010/11 Teff 9.07
2011/12 Teff 10.60
2012/13 Teff 11.64
2013/14 Teff 12.11
2014/15 Teff 13.14
2015/16 Teff 13.00
2003/04 Maize 21.91
2004/05 Maize 13.08
2005/06 Maize 18.92
2006/07 Maize 19.21
2007/08 Maize
2008/09 Maize 18.19
2009/10 Maize
2010/11 Maize 17.09
2011/12 Maize 24.10
2012/13 Maize 25.73
2013/14 Maize 25.24
2014/15 Maize 26.42
2015/16 Maize 26.99
2003/04 Haricot Beans 6.75
2004/05 Haricot Beans 6.79
2005/06 Haricot Beans 7.42
2006/07 Haricot Beans 8.92
2007/08 Haricot Beans 7.57
2008/09 Haricot Beans 8.96
2009/10 Haricot Beans
2010/11 Haricot Beans 11.88
2011/12 Haricot Beans 8.60
2012/13 Haricot Beans 10.05
2013/14 Haricot Beans 16.62a
2014/15 Haricot Beans 14.51
2015/16 Haricot Beans 16.00
2003/04 Taro 80
2004/05 Taro 80.00
2005/06 Taro 84.40
2006/07 Taro 94.81
2007/08 Taro 83.84
2008/09 Taro 83.84
2009/10 Taro
2010/11 Taro 86.06
2011/12 Taro 86.06
2012/13 Taro 327
2013/14 Taro 327
2014/15 Taro 336.4
2015/16 Taro 256.4
2003/04 Sweet Potato 118
2004/05 Sweet Potato 109.00
2005/06 Sweet Potato 100.00
2006/07 Sweet Potato 87.53
2007/08 Sweet Potato 102.91
2008/09 Sweet Potato 102.91
2009/10 Sweet Potato
2010/11 Sweet Potato 106.79
2011/12 Sweet Potato 106.79
2012/13 Sweet Potato 241
2013/14 Sweet Potato 364.54
2014/15 Sweet Potato 378.66
2015/16 Sweet Potato 321.29
a

CSA began dividing white and red haricot beans in 2013/14, the figures used are an average of the two.

Alternative surveys of the required scale do not appear feasible or realistic at this time. However, the questions above highlight the need for more research to assess the data provided by central statistics agencies. Often these data sets are utilized without critical reflection about quality, methodology or politicization.

2. Experimental design, materials and methods

Average crop yield data at national, regional (SNNPRS) and zonal (Wolaita) levels (see Map 1) were obtained from the CSA annual Agricultural Sample Surveys. The data is presented using figures to highlight trends and tables to allow for further analyses of the data. We have selected SNNPRS as an example region and Wolaita as an example zone primarily due to our familiarity with the areas respectively, and thus enhancing our ability to identify questions. The objective of raising questions about the agricultural root crop yield data is to encourage researchers to engage with central statistics data more critically. This does not suggest that the CSA data is inaccurate; rather it acts an encouragement for CSA data to be a subject of greater study.

Map 1.

Map 1

National (FDRE), Regional (SNNPRS) and Zonal (Wolaita).

Footnotes

Transparency document

Transparency document associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.dib.2017.12.039.

Transparency document. Supplementary material

Transparency document

mmc1.docx (11.1KB, docx)

References

  • 1.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2004. Agricultural Sample Survey 2003/2004, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 2.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2005. Agricultural Sample Survey 2004/2005, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 3.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2006. Agricultural Sample Survey 2005/2006, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 4.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2007. Agricultural Sample Survey 2006/2007, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 5.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2008. Agricultural Sample Survey 2007/2008, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 6.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2009. Agricultural Sample Survey 2008/2009, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 7.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2010. Agricultural Sample Survey 2009/2010, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 8.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2011. Agricultural Sample Survey 2010/2011, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 9.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2012. Agricultural Sample Survey 2011/2012, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 10.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2013. Agricultural Sample Survey 2012/2013, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 11.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2014. Agricultural Sample Survey 2013/2014, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 12.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2015. Agricultural Sample Survey 2014/2015, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 13.Central Statistical Agency . Central Statistical Agency, Federal Democratic Republic of Ethiopia; Addis Ababa: 2016. Agricultural Sample Survey 2015/2016, Vol. 1: Area and Production of Major Crops. [Google Scholar]
  • 14.(a) Jerven M. Cornell University Press; Ithaca: 2013. Poor Numbers: How We Are Misled by African Development Statistics and What to Do about It. [Google Scholar]; (b) Sundaram J.K. The MDGs and poverty reduction. In: Cimadamore A., Koehler G., Pogge T., editors. Poverty and the Millennium Development Goals. Zed Books; London: 2016. pp. 26–44. [Google Scholar]; (c) Sandefur J., Glassman A. The political economy of bad data: evidence from African survey & administrative statistics. J. Dev. Stud. 2015;51:116–132. [Google Scholar]; (d) Carletto C., Jolliffe D., Banerjee R. From tragedy to renaissance: Improving agricultural data for better policies. J. Dev. Stud. 2015;51:133–148. [Google Scholar]
  • 15.L. Cochrane, Strengthening Food Security in Rural Ethiopia Doctoral Dissertation (Interdisciplinary Studies) submitted to the University of British Columbia, 2017.
  • 16.Tefera T.T., Handoro F., Gemu M. Prevalence, incidence and distribution of sweet potato virus: it's effect on the yield of sweet potato in southern region of Ethiopia. Int. J. Sci. Res. 2013;2:591–595. [Google Scholar]

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