Dummy regression to predict dry fiber in Agave lechuguilla Torr. in two large-scale bioclimatic regions in Mexico.

ABSTRACT: Agave lechuguilla Torr., of the family Agavaceae, is distributed from southwestern United States to southern Mexico and is one of the most representative species of arid and semiarid regions. Its fiber is extracted for multiple purposes. The objective of this study was to generate a robust model to predict dry fiber yield (Dfw) rapidly, simply, and inexpensively. We used a power model in its linear form and bioclimatic areas as dummy variables. Training, generation (80%) and validation (20%) of the model was performed using machine learning with the package 'caret' of R. Using canonical correlation analysis (CCA), we evaluated the relationship of Dwf to bioclimatic variables. The principal components analysis (PCA) generated two bioclimatic zones, each with different A. lechuguilla product

SUBMITTER: Lopez-Diaz JOM 

PROVIDER: S-EPMC9477326 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature