Contents & Foreword, Characterizing And ... - IRRI books

In rainfed agriculture, crop performance is strongly influenced by climatic characteristicsand by spatial heterogeneity over soil types, topographic sequences, andagrohydrologic conditions. Cultivar and management interact with these environmentalvariables, thus complicating the task of identifying improved cultivars. These interactionsand the complexity of factors involved make it difficult to adequately definethe target population of environments or even to reliably assess cultivar performanceover those environments (Wade et al 1995, Cooper 1999). To provide a focus forselection programs, it is essential to clearly identify the target population of environments,their spatial and temporal frequencies, and their characteristics.Wade et al (1996) discussed two broad approaches for characterization of environments:one based on analysis of physical parameters such as soil properties, climate,and hydrology, and the other based on discrimination by reference lines. Thefirst approach, physical characterization, requires access to substantial data sets and acapacity to interpret their implications for crop adaptation. It is hampered by a lack ofdata and poor understanding of plant responses to complex combinations of environmentalfactors. Since this is a priority topic for research, however, such relationshipswill become clearer as data coverage, methodologies, and physiological understandingimprove (V.P. Singh et al, this volume).In the second approach, differential responses of reference lines are used as abioassay for the occurrence of particular conditions (Cooper and Fox 1996, Wade etal 1996). Although this approach requires less environmental data for new test locations,its effectiveness depends on knowledge of the reference lines and their patternsof adaptation. Confidence in the classification is improved and further understandingis developed if key environmental data are collected on the new test environments aswell as on cultivar response.The availability of pattern analysis methods permits rigorous analysis of G × Einteractions and classification of genotypes and environments into groupings withsimilar patterns of adaptation or discrimination. Using these methodologies, recentstudies have reported a reliable assessment of repeatable G × E interactions in rainfedlowland rice (Cooper et al 1999, Wade et al 1999). Groups of varieties with commonpatterns of adaptation over environment groups were identified in these studies. Referencelines would be chosen as standard and well-known representatives of thesevariety groups (Cooper and Fox 1996, Wade et al 1996). The principle is that a fewreference lines can be used to represent a wide range of genotypic adaptation. Furthermore,discrimination between these lines could be used to classify new test environmentsinto previously identified targets.An improved capacity to classify new test environments is important becausebreeders need to know how new sites relate to the target population of environmentsfor which they are breeding. Also, performance of a new genotype in a new set ofmultienvironment trials needs to be assessed relative to the performance of otherlines in similar environments. Both these requirements can be met by using a representativeset of reference lines since the adaptation of a new genotype may be classifiedby its similarity in response to the reference line with which it groups and byknowledge of the types of environments in which it and the reference line show simi-132 McLaren and Wade