Statistical modeling applications to mitigate the effects of climate change on quality traits of cereals: A bibliometric approach

Abstract

Agricultural production is highly dependent on climate conditions. Cereal yield and quality attributes are expected to vary depending on climate change. Climate alteration is a multifaceted issue which requires complex solutions. Accurate modeling and prediction of climate change impacts on crop production can help build efficient agronomic approaches to cope with this complicated problem. Various statistical methods started to be utilized in modeling and prediction of climate change effects on plant production. Bibliometric analysis is a powerful tool to quantify scientific production, quality and impact. This technique also provides readers with full information related to intellectual, conceptual and social structures of a certain area together with its evolution over time. We used the Web of Science database to extract the relevant literature on modeling applications to mitigate the effects of climate change on quality traits of cereals. Our results projected an upward publication trend with considerable spikes in 2018 and 2020. Although the topic has flourished in recent years, the literature on the field is still fragmented. This fact supports the need for systematization of the literature as we aim in this paper. The study results provide a holistic overview of the fragmented literature on the field by revealing research trends and hidden network patterns between scientific actors. In this way, it is a useful source for scholars interested on the topic to find new collaborations and future research directions.