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GrainGenes Reference Report: JID-96-261

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Reference	JID-96-261
Title	Response of durum wheat cultivars to Algerian environments - V. Long-term yield potential of locations
Journal	Journal of Agriculture and Environment for International Development
Year	2002
Volume	96
Pages	261-271
Author	Annicchiarico P [ Show all 6 ]
Abstract	The relationship between grain yield of durum wheat and 13 environmental variables recorded across 2 years at 18 Algerian locations was investigated, and then exploited, to predict the long-term yield of potentially suitable sites according to a Geographic Information System (GIS). The site yield was estimated as the average yield of the 5 best-ranking cultivars out of 24, i.e. contemplating the cultivation of locally best-adapted material. Site yield increased with increasing annual rainfall, soil water content in spring, and winter and spring mean temperature, and with decreasing cold stress and altitude of locations. It showed just a slight trend to positive association with 3 vegetation indices. No significant curvilinear relationship emerged between site yield and any environmental variable within the range of recorded values. The selected multiple regression model for predicting site yield minimized Mallows' Cp value while having all partial regression coefficients significant at Pless than or equal to 0.10. This empirical model, which explained 63% of site yield variation, included 2 variables, i.e. annual rainfall and winter mean temperature. The predictive success of these variables was also due to their ability to partly convey the information of other useful variables. Long-term yields of locations were predicted as a function of long-term values of the 2 climatic variables. For GIS mapping, the sites were grouped into 4 classes of potential yield. About 54% of the area was attributed to the 2-3 t/ha yield class, whereas only about 32% could be considered relatively high-yielding (>3 t/ha). The generated information, although needing validation from independent data and subject to revision as a consequence of breeding progress, may already assist in planning national support and food security policies. Data on other, more complex environmental factors that may become available in the GIS may further improve the predicting ability
Keyword	climatic seasons [ Show all 16 ]

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