GIS-based evaluation of maize cultivar lodging resistance performance in target growing environments

Lodging in maize is one of the major problems in maize production worldwide,which causes serious yield and economic losses annually.By evaluating cultivar lodging resistance performance in target growing environments before cultivar extension and application,the risks and losses can be significantly reduced.In this study,a GIS-based quantitative method for evaluating maize cultivar lodging resistance performance in target growing environments was established based on full cognition of environment stress,cultivar resistance,and the interaction between them.At first,comprehensive environment lodging stress is measured by three factors:1)extreme wind event in maize vegetative stage which is the direct factor,2)soil potassium content in target growing environment which is an indirect factor affecting corn stem sturdiness,and 3)planting density which is a human influence factor.Quantification methods of extreme probability analysis,spatial interpolation,normalization,and so on were used.Then,maize cultivar lodging resistance was determined using cumulative frequency distribution analysis of tested lodging data.At last,an evaluation matrix was established combining environment lodging stress and cultivar lodging resistance together,which was very simple and easy to understand method and the result is promising providing good direct support in practical cultivar application.The method used in this study,at county-level,cultivar-level and stress-level with GIS,can facilitate the identification of better-adapted growing environments for a specific maize cultivar,and provide direct support for maize cultivar recommendation and extension,so as to reduce the risk and loss of lodging in maize.It is more easy-operational and feasible than traditional surveying approach,especially for large-scale spatial trend analysis.So it is of both academic significance in accelerating precision agriculture development and practical significance in improving maize cultivar application.