Country-Level Bio-Economic Modeling of Agricultural Technologies to Enhance Wheat-Based Systems Productivity in the Dry Areas

Published Date
June 29, 2016
Type
Journal Article
Country-Level Bio-Economic Modeling of Agricultural Technologies to Enhance Wheat-Based Systems Productivity in the Dry Areas
Authors:
Aymen Frija
Roberto Telleria

Conservation Agriculture (CA) have a large potential for enhancing cereal yields in the semi-arid areas through
better management of soil moisture. The objective of the current paper is to quantify, at national level, the impact
of CA adoption in wheat-based agricultural systems in Syria. A country-level bio-economic approach was used
for this purpose. Different CA technical packages (TPs) were first developed and simulated through APSIM crop
modeling software, in order to estimate the long-term yields of wheat under different CA TPs for the period
2015-2039. The considered CA packages are a combination of zero-tillage, mulching, raised bed, fertilizer doses,
and planting dates. The simulated yields are then introduced into IMPACT model while assuming that TPs will
be adopted on 35% of the wheat areas in the countries. Results show that the comparative advantages of CA TPs
on overcoming the effect of climate change will only be significant after 2030. In 2039, the effect of different
TPs on average wheat yields in Syria will be 4% to 12% (depending on the TP) higher than the average yields
under climate change and no CA technology adoption. These yield enhancements may reduce the wheat trade
deficit with 30 up to 140%, also depending on the technical package. The combination of mulching techniques,
together with average nitrogen dose of 30kg/ha, and late planting date of wheat provides the best prospective for
the wheat sector in Syria

Citation:
Aymen Frija, Roberto Telleria. (29/6/2016). Country-Level Bio-Economic Modeling of Agricultural Technologies to Enhance Wheat-Based Systems Productivity in the Dry Areas. Sustainable Agriculture Research, 5 (3), pp. 113-123.
Keywords:
wheat supply
foresight modeling
syria
mulching
agriculture
planting date