Canonical Analysis of the Impact of Climate Predictors on Sugarcane Yield in the Eastern Region of Pernambuco, Brazil

0Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Sugarcane yield plays a crucial role in food safety and biofuel production, and it is strongly influenced by climatic variations. In this context, this study applies canonical correlation analysis (CCA) to identify the climatic predictors, such as sea surface temperature, atmospheric pressure, and wind speed, that affect sugarcane yield from 1990 to 2019. Hierarchical cluster analysis applied to the performance of 58 municipalities in the eastern region of Pernambuco identified three distinct and homogeneous groups. An analysis of the CCA for the three sugarcane yield groups and climatic variables revealed that the first canonical function was significant with R = 0.82 and precision of 0.67 (p ≤ 0.05 at 95% confidence level), and that the sugarcane yield groups and climatic variables were different (Wilks’ lambda = 0.14), but they were associated. Climatic variables affected the three sugarcane productivity groups, with redundancy indices of 29.7%, 52.2%, and 59.9%. Climatic variables with positive canonical weights enhance performance, while those with negative weights decrease yields. The structural canonical loads and cross-loadings reveal that sea surface temperature plays a crucial role in determining sugarcane yield, potentially influencing precipitation and temperature patterns in the region. The sensitivity analysis confirms the stability of the canonical loads and the robustness of the results, demonstrating that this research can support yield forecasting, regional agricultural policy, and drought management. Identifying climate predictors, such as sea surface temperature, wind speed, and atmospheric pressure, enables the creation of accurate models to predict sugarcane productivity, assisting farmers in planning input management, irrigation during dry periods, and harvesting. Furthermore, climate data can inform policies that encourage sustainable agricultural practices and adaptation to climate conditions, strengthening food security and guiding the selection of more resilient sugarcane varieties, increasing production resilience.

Cite

CITATION STYLE

APA

Silva, R. R. da, Moura, G. B. de A., Lopes, P. M. O., Nascimento, C. R., & Giongo, P. R. (2025). Canonical Analysis of the Impact of Climate Predictors on Sugarcane Yield in the Eastern Region of Pernambuco, Brazil. Agriculture (Switzerland), 15(20). https://doi.org/10.3390/agriculture15202162

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free