The SIAC core database and charts
This is one of the core databases collected through funding from the Standing Panel on Impact Assessment (SPIA) of the CGIAR Independent Science and Partnership Council (ISPC) to Michigan State University under the Strengthening Impact Assessment in the CGIAR (SIAC) project (2013-2017).
The database includes varietal release and adoption estimates for eleven CGIAR mandated crops across 15 countries: 134 crop-country-combinations (CCCs) in the South, Southeast, and East Asia region. Data were collected by the CGIAR Centers (CIAT, CIMMYT, CIP, IRRI and ICRISAT) and their national partners.
This activity was built on methods – expert opinion as well as validation household surveys (in a few cases) – used by the earlier projects - DIIVA and TRIVSA projects. You can refer the guidelines here.
About the data
How were the crop-by-country combinations identified?
A consultative process was used to identify the final crop-country combinations. These CCCs were prioritized and put forward as the focus of ‘tracking the adoption of improved varieties’ under the SIAC project by the relevant Center/CRP. The criteria used to select the CCCs included the importance of the crop in terms of total area planted, importance of the country in terms of CGIAR research contributions, data gaps, linkages/capacity of NARS, the feasibility in terms of security restrictions/constraints, and available resources (i.e., budget constraint).
What are the countries of interest, and what does the data represent?
The countries included in this dataset cover the region of interest for the SIAC project in Phase 1 (i.e., South, Southeast and East Asia). Within each country, any data reported – unless otherwise specified – should be considered nationally representative (or representative at the sub-domain level, if such disaggregated data are reported). The only two countries for which data are collected and recorded at different levels (not nationally representative) are India and China. In these large and populated countries, the information is representative of the selected state (India) or province (China) level. Although the varietal release data for some crops are collected and reported at the country level for India and China, all the variety specific adoption estimates are at the CCC or sub-domain level. The adoption data refer to estimates of perceived adoption in the most recently completed agricultural year in that CCC as indicated in the database.
To summarize, across all methods, these data represent ‘perceived’ varietal adoption data representative for one year (around 2013-2015) in a given CCC or sub-domains within the CCC.
Any caveats in interpreting these results?
In the use and interpretation of this data, please note that other pilot work in SIAC undertaken by SPIA, in collaboration with World Bank LSMS-ISA; MSU; as well as some CGIAR Centers underlines that different approaches to collecting varietal adoption data – expert opinion, household surveys, DNA fingerprinting – provide widely divergent results. In some cases, DNA fingerprinting might be the only way to get accurate information on which varieties farmers are growing. Please refer the pilot studies, findings, and discussion in the final SIAC report.
Maredia et al. 2016, Varietal Release and Adoption Data for South, Southeast, and East Asia: SIAC Project (2013-2016), Rome: Independent Science and Partnership Council. Retrieved from http://www.lrbd.net/siac
SIAC data are available for download in Excel (.xlsx) format in the following four worksheets:
Read me. Provides background information on the approach to the activity, including institutions and researchers involved, methods used, and a list of the CCCs. Please also refer to citation requirements.
Varietal Release. Provides basic information for each modern crop variety, including year of first release or use, institutional source, pedigree, varietal type (OPV, cross hybrid etc.), as well as varietal traits.
Adoption_CCC_level_2014-16. For each CCC, at the subdomain and season level, provides the share of area (in percentage) under modern varieties (aggregate) and traditional varieties (aggregate). The total area for the CCC, at subdomain and season level, is also listed in hectares (ha).
Adoption_Var_level_2014-16. For each CCC, at the subdomain and season level, provides the share of area (in percentage) under each modern variety and the traditional varieties (aggregate).
The databases included in this data file were collected with support from hundreds of people over a period of 3 years (2014-2016). Each CGIAR Center was responsible to collect, assemble and submit two datasets—varietal release and varietal adoption for their mandated crops towards achieving the SIAC objective 2.1. Michigan State University (MSU) provided methodological guidelines (see Maredia and Reyes 2014), established protocols, and provided data quality check. This data file is a result of the cleaning, editing, and consolidation done by Michigan State University of all the datasets submitted by the Centers, and serves as one of the deliverables of the SIAC project.
Disclaimer: Centers/NARS partners had the flexibility to explore and adapt the guidelines to Center-specific characteristics of their mandated crops and countries. The data included in these databases represent ‘minimum data’ that all Centers had agreed to collect as per the guidelines, and in some cases represent only a sub-set of all the data collected. Each Center is the custodian of the full set of data collected and assembled by their partners for their mandated crop-country-combinations (CCCs). Please contact the Center focal point (see Read me worksheet) for additional data, information or clarifications.
Other crop variety databases
CGIAR’s Tracking Improved Varieties in South Asia (TRIVSA) project was implemented during 2010–2013 and focused on the rainfed areas of South Asia. TRIVSA assessed the effectiveness of varietal improvement programs focusing on the region’s important food crops, including humid and sub-humid varieties of rice, and semi-arid varieties of sorghum, pigeon peas, pearl millet, groundnuts, and chickpeas.
The CGIAR’s Diffusion and Impact of Improved Varieties in Africa (DIIVA) project collected data on improved crop varieties in Africa south of the Sahara. The project focused on 20 crops and 30 countries – 152 crop-country combinations, together representing over 70 percent of the region’s total agricultural production value.