کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5761568 1624661 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
پیش نمایش صفحه اول مقاله
Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars
چکیده انگلیسی


- We develop genetic parameters for locally-adapted wheat cultivars across the globe.
- We use locally-adapted cultivars to simulate global wheat yields and production.
- Simulated wheat yields and country production agree well with those reported by FAO.
- Our results provide baseline global wheat production for global impact analysis.

Climate change is expected to impact global food supply and food security by affecting growing conditions for agricultural production. Process-based dynamic growth models are important tools to estimate crop yields based on minimum inputs of climate, soil, crop management, and crop cultivar parameters. Using region-specific cultivar parameters is critical when applying crop models at a global scale because cultivars vary in response to climate conditions, soils, and crop management. In this study, parameters were developed for modern cultivars representing all 17 CIMMYT wheat Mega Environments (MEs) using field experimental data and genetic cultivar relationships for the CROPSIM-CERES model in DSSAT v 4.5 (Decision-Support System for Agrotechnology Transfer). Cultivar performance was tested with independent CIMMYT breeding trial field experiments across several locations. Then crop simulations were carried out at 0.5 × 0.5 ° pixels for global wheat-growing areas, using cultivars representing MEs, soil information, region-specific crop management, and initial soil conditions. Aggregated simulated wheat yields and production were compared to reported country yields and production from Food and Agriculture Organization (FAO) statistics, resulting in a Root Mean Square Error (RMSE) of 1.3 t/ha for yield and 2.2 M t/country for country production. Some of the simulated errors are relatively large at country level because of uncertainties in pixel information for climate, soil, and crop management input and partly because of crop model uncertainties. In addition, FAO yield statistics have uncertainties because of incomplete farm reports or poor estimates. Nevertheless, this new cultivar-specific, partially-validated global baseline simulation enables new studies on issues of food security, agricultural technology, and breeding advancement impacts combined with climate change at a global scale.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Field Crops Research - Volume 202, 15 February 2017, Pages 122-135
نویسندگان
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