## 5 Conclusions  
This SLR provides a comprehensive understanding of RTM applications for crop yield and traits retrieval as per the described criteria. It can be concluded from this SLR that RTMs are significantly effective in crop yield prediction and crop traits retrieval. This is because the radiative transfer model's philosophy is similar to crop growth linked to radiation's reflectance, absorbance and transmission. Still, this area needs the attention of researchers for further exploration to benefit agriculture with enhanced crop productivity. The limited number of studies of crop yield prediction, however, indicate a research gap for further investigation, particularly through integration with crop growth models to strengthen information reliability and accuracy. Moreover, there is a need for more radiative transfer models that have ability to capture small trait variations. Similarly, RTMs other than PROSAIL also need further research to explore their potential for crop yield prediction and crop traits retrieval. This will improve crop traits retrieval accuracy, leading to improvements in crop yield modeling. Most RTMs and CGMs connecting through LAI is another area of research focus, in order to have other crop traits for strengthening this connectivity. The addition of investigations into crops other than cereal could broaden the base of RTM applications to explore its potential and enhance research activities in this field. In the future, as crop traits and their retrieval accuracy are improved, crop productivity will also be enhanced due to effective decision-making and crop growth monitoring being used to mitigate the challenges of food security.  
Conceptualization, R.A.F.I. and G.Z.; methodology, R.A.F.I, G.Z., C.T. and O.-u.-R.; formal analysis, R.A.F.I.; investigation, R.A.F.I. and C.T.; resources, Y.T. and H.J.; data curation, R.A.F.I. and O.-u.-R.; writing--original draft preparation, R.A.F.I.; writing--review and editing, G.Z., Y.T. and G.J.; visualization, R.A.F.I.; funding acquisition, G.Z. and G.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (grant number 41971320), Beijing Natural Science Foundation (grant number 162028), the Science and Technology Program of Yunnan Province, China (grant number 202102 AE090051) and the Study on Carbon Neutrality Benefits and Contribution Accounting of Three Gorges Reservoir (grant number 102126222020270019081).  
All the relevant data (screened articles) is available in the manuscript as references and graphs.  
The author wants to acknowledge the support and dedication of [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] for completing this manuscript. Their support made it possible to complete this task in a short period. Moreover, we are grateful to [PERSON] and his team for the development of CiteSpace. A free and effective source, not only for scientometrics and bibliometric analysis, but also for comprehensive visualizations relevant to the research interest. We are also grateful to [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] for reviewing this manuscript.  
The authors declare no conflicts of interest.