## 5 Conclusions  
In this study, different vegetation indices and algorithms were used for modeling the biomass and leaf area index of forage crops (common grass and buffel grass) in agroforestry systems in the Caatinga biome. Additionally, the removal of system components (trees and soils) was performed to improve the accuracy of the models. Based on the presented results, we suggest employing regression tree-based models (CART) as a viable option when constructing predictive models for biomass and leaf area index of common grass and buffel grass in agroforestry systems within the Caatinga biome.  
The robustness of these models, evidenced by their ability to handle outliers and their relative insensitivity to training data, makes them suitable for the complexity of the conditions found in this environment. Furthermore, the simplicity and ease of replication of linear regression-based models, particularly when using indices like NGRDI and VARI, make them a viable option for estimating productive indices in these conditions. It is also worth emphasizing the importance of tree removal from orthomosaics as a significant procedure in predicting both evaluated modeling methods.  
**Author Contributions:** Conceptualization, A.C.B., E.J.O.d.S. and W.M.d.S.; methodology, A.C.B., C.d.J.P.C., D.M.J., E.J.O.d.S., J.C.B.D.J. and W.M.d.S.; software, A.C.B., A.M.d.R.F.J., E.J.O.d.S. and W.M.d.S.; validation, A.M.d.R.F.J., J.C.B.D.J., M.L.d.S.M. and M.V.d.C.; formal analysis, D.M.J., E.J.O.d.S., J.C.B.D.J., M.V.d.C. and W.M.d.S.; investigation, A.C.B., C.d.J.P.C., E.J.O.d.S., J.C.B.D.J., M.L.d.S.M. and W.M.d.S.; resources, A.C.B., D.M.J., E.J.O.d.S., J.C.B.D.J. and M.V.d.C.; data curation, A.C.B., C.d.J.P.C., E.J.O.d.S., M.L.d.S.M. and W.M.d.S.; writing--original draft preparation, A.C.B., C.d.J.P.C., E.J.O.d.S., M.L.d.S.M. and W.M.d.S.; writing--review and editing, A.M.d.R.F.J., D.M.J., J.C.B.D.J. and M.V.d.C.; visualization, A.C.B., A.M.d.R.F.J., E.J.O.d.S. and W.M.d.S.; supervision, E.J.O.d.S. and J.C.B.D.J.; project administration, E.J.O.d.S., J.C.B.D.J. and W.M.d.S.; funding acquisition, E.J.O.d.S., J.C.B.D.J. and M.V.d.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** Financial support was provided by the Foundation for the Support of Science and Technology of the State of Pernambuco (FACEPE) under grants IBPG-1035-501/21. The authors would like to thank the Coordination for the Improvement of Higher Education Personnel (CAPES) under the Finance Code 001. A.M.d.R.F.J. acknowledges support from the Sao Paulo Research Foundation--FAPESP grant 2023/05323-4. M.V.d.C. acknowledges a scholarship from the National Council for Scientific and Technological Development--CNPq.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
**Acknowledgments:** We thank the Section Managing Editor, [PERSON], and three anonymous reviewers for their insightful comments and suggestions on the manuscript.  
**Conflicts of Interest:** The authors declare no conflicts of interest.