Geographical detector-based wheat quality attribution under genotype, environment, and crop management frameworks

Abstract

Elucidating the determining factors for wheat quality is an essential but complex task, influenced by wheat cultivars, environmental conditions, and management decisions. This study analyzed 285 winter wheat varieties, 13 wheat quality traits, and 9 influencing factors under a genotype, environment, and crop management framework by a geographical detector model in China’s main winter wheat-producing area. Our results revealed the attribution of wheat quality in the genotype × environment × crop management (G × E × M) interaction framework. The factors influencing wheat quality in China were ranked as follows: wheat cultivar > precipitation > Tmax > irrigation > soil type > Tmin > fertiliser > sunshine duration > landform. The wheat cultivar was the dominant factor affecting wheat quality, which explained 38.57%, 38.78%, and 28.13% of the variation in gluten index, stabilization time, and sedimentation index, respectively. In addition, the sensitivity of the wheat quality traits to the G × E × M interaction framework was detected. The wheat quality trait sensitivity ranked from the highest to the lowest followed the order gluten index > sedimentation index > hardness index > stabilisation time > seed moisture > crude protein > formation time > wet gluten > water absorption > landing value > flour output ratio > ash > capacity. Gluten and sedimentation were highly sensitive traits for wheat quality under the G × E × M interaction framework, with sensitivity index values of 66.94% and 58.11% in the G × E × M framework, respectively. Furthermore, we proposed an integrated improvement strategy for an end-use wheat quality trait based on the sensitivity of wheat quality traits in the G × E × M framework. The gluten index, crude protein, wet gluten, and hardness index should be prioritized according to wheat’s commercial value and sensitivity index. However, other quality traits with higher commercial importance, such as flour output ratio, capacity, and landing value, should be put behind the improvement list. Our result identified the critical factors for most wheat quality traits in the G × E × M framework. It extended the comprehensive strategy for wheat quality improvement.