Genetic material developed and improved are tested through a number of on-station trials, but are finally targeted for the farmers’ fields where the actual crop production takes place to feed the population of a country. Afghanistan needs to increase wheat production to support its domestic need of wheat consumption, reduce its imports and enhance the exports. The purpose of this study was to assess the effect of the improved varieties of wheat in the target domain in Afghanistan. The improved varieties with a package of practice were implemented in farmers’ field through demonstration plots. A total of 223 farmers’ fields were included in the trials implemented in eight districts in East Central Zone. Across all the locations, the improved varieties showed substantial increase of yield over local variety in range of 53-86% and yield stability across the locations. Consequently, the wide use of improved varieties with package of practice can result considerable gain to farmers to harvest more yield which motivated farmer to accelerate variety replacement up 100% and other hand, this increase will positively recover farmers economic status. As whole, increase in the yield would be contributed to meet current need of the country in wheat and improve the food security.
on-farm trials, wheat, improved genotypes, food security, productivity risks, GGE bi-plot
Akbarzai, D. K., Saharawat, Y., Mohammadi, L., Manan, A. R., Habibi, A., Tavva, S., Nigamananda, S. & Singh, M. (2017). Genotype × Environment Interaction and Identification of High Yielding Wheat Genotypes for Afghanistan. Journal of Experimental Biology and Agricultural Sciences, 5, 225-234.
Anderson, J. R. (1974). Risk-efficiency in the interpretation of agricultural production research. Review of Marketing and Agricultural Economics, 42, 131-184.
Asfaw, A., Alemayehu, F., Gurum, F., & Atnaf, M. (2009). AMMI and SREG GGE biplot analysis for matching varieties onto soybean production environments in Ethiopia. Scientific Research and Essays, 4, 1322-1330.
Basford, K. E., & Cooper, M. (1998). Genotype x environment interaction and some considerations of their implications for wheat breeding in Australia. Australian Journal of Agriculture Research, 49, 153-174.
DeLacy, I.H., Basford, K.E., Cooper, M. & Fox. P.N. (1996). Retrospective analysis of historical data sets from multi-environment trials- Case studies. p. 243–267.M. Cooper and G.L. Hammer (ed): Plant Adaptation and Crop Improvement. CAB Int., Wallingford, UK.
Eberhart, S. A. & Russell W. A. (1966). Stability parameters for comparing varieties. Crop Science, 6, 36-40.
Finlay, K. W. & Wilkinson G. N. (1963). The analysis of adaptability in plant breeding programme. Journal of Agricultural Research, 14, 742-754.
Farshadfar, E., Mohammadi, R., Aghaee, M., & Vaisi, Z. (2012). GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. Australian Journal of Crop Science, 6, 1074-1079.
Haddad, N., Singh, M., & Mumdouh, Q. (2005). On-farm evaluation of improved Barley production technology packages in Jordan. Jordan Journal of Agricultural Sciences, 1, 1.
Jambormias, E. (2011). Describing of GGE-biplot graphics to evaluate genotypes performance and changes of environmental stress in small islands (in Indonesian). Proceedings of National Conference: Development of Small Islands (PERMAMA). University of Pattimura. Ambon, 299-310.
Karimizadeh, R., Mohammadi, M., Sabaghni, N., Mahmoodi, A. A., Roustami, B., & Seyyedi, F. (2013). GGE biplot analysis of yield stability in multi-environment trials of lentil genotypes under rainfed condition. Notulae Scientia Biologicae 5, 256-262.
Kaya, Y., Akcura, M., & Taner, S. (2006). GGE-biplot analysis of multi- environment yield trials in bread wheat. Turkish Journal of Agriculture Forestry, 30, 325-337.
Lin, C. S., Binns, M. R., & Lefkovitch, L. P. (1986). Stability an analysis: Where do we stand. Crop Science. 26, 894-900.
Mohammadi, L., Saharawat, Y., Akbarzai, D. K., Manan, A. R., Habibi, A., Soofizada, Q., Tavva, S., Swain, N. & Singh, M. (2017). Genotype × Environment Interaction in Chickpea (Cicer Arietinum L.) Under Afghanistan Environments and Identification of High Yielding Genotypes. Journal of Experimental Biology and Agricultural Sciences, 5, 428-438.
Sharma, R. C., Morgounov. A. I., Braun, H. J., Akin, B., Keser, M., Bedoshvili, D., Bagci, A., Martius, C., & Ginkel, V. M. (2010). Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia. Euphytica, 171, 53–64.
Sharma, R. C., Rajaram, S., Alikulov, S., Ziyaev, Z., Hazratkulova, S., Khodarahami, M., Nazeri, S. M., Belen, S., Khalikulov, Z., Mosaad, M., Kaya, Y., Keser, M., Eshonova, Z., Kokhmetova, A., Ahmedov, M. G., Kamali, J. M. R., & Morgounov, A. I. (2012). Improved winter wheat genotypes for Central and West Asia. Euphytica, 190, 19–31.
Tadesse, W., Morgounov, A. I., Braun, H. J., Akin, B., Keser, M., Kaya, Y., Sharma, R. C., Rajaram, S., Singh, M., Baum, M., & Ginkel, V. M. (2013). Breeding progress for yield and adaptation of winter wheat targeted to irrigated environments at the International Winter Wheat Improvement Program (IWWIP). Euphytica, 194, 177–185.
Tavva, S., Singh, M., Rizvi, J., Saharawat, Y. S., Swain, N., & Shams, K. (2017). Potential of introducing improved production practices in food legumes in increasing food security in Afghanistan. SCIENTIA AGRICOLA, 76(1), 41-46
VSN International. ( 2015). The Guide to the Genstat Command Language (Release 18), Part 2 Statistics. VSN International, Hemel Hempstead, UK.
Yan, W., Hunt, L. A., Sheng, Q., & Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Science, 40, 597–605.
Yan, W. (2011). GGE Biplot vs. AMMI Graphs for Genotype-by-Environment Data Analysis. Journal of the Indian Society of Agricultural Statistics, 65, 181-193.
Yan, W., & Tinker, N. A. (2006). Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science, 86, 623-645.