## 3 Results and Discussion
### Proximate Composition Statistical Algorithm  
Figure 1 shows the biplot principal component analysis (PCA) that allowed grouping the samples of degraded sugarcane residues, with and without the inoculation of phytopathogenic fungi, and relating them to their physicochemical characteristics. Plan 1-2 shows the formation of three clusters according to six vectors: moisture, ash, organic nitrogen, organic matter, organic carbon, and the carbon-to-nitrogen ratio. The size of each cluster was determined by the number of residue samples that exhibited the highest correlation with each other. The interpretation indicates that the samples that make up each group are closely related to each other in terms of the quantitative variables measured. In contrast, the groups that are farther apart imply significant differences in their physicochemical composition. In the factorial graph, the accumulated inertia of the two-dimensional representation amounted to 97.4%, with 91.6% of the data variability distributed in the first dimension and 5.8% in the second dimension. The conformation of the clusters was as follows: Cluster  
Figure 1: Two-dimensional projection of residue samples on principal components 1 and 2. Note. Each dot represents a waste sample coded by its respective treatment; the vectors represent the proximate composition indicators: Org. nitrogen (%), organic nitrogen (%); Org. Mat, organic matter (%); Org. carb (%), organic carbon (%); C:N, carbon to nitrogen ratio. 1 (green color), constituted by six samples of degraded residues (P1, P2, P3, P4, P5, P6), corresponding to degraded residues without inoculation and residues inoculated with _Colletotrichum_ spp. belonging to treatments T1 and T2, respectively; Cluster 2 (blue color), formed by three samples of processed residues (P7, P8, P9), corresponding to residues inoculated with the phytopathogenic fungus _Rhizopus_ spp. from treatment T3; and Cluster 3 (red), composed of three samples of degraded residues (P10, P11, P12) inoculated with the combination of _Colletotrichum_ spp. and _Rhizopus_ spp. from treatment T4. The results from the principal component analysis (PCA) reveal distinct patterns in the proximate composition of the degraded residues based on the phytopathogenic fungi used. Cluster 1, which includes residues without inoculation and those treated with _Colletotrichum_ spp., exhibits higher levels of organic matter, organic carbon, the carbon-nitrogen ratio, and moisture, indicating incomplete decomposition. Cluster 2, consisting of residues inoculated with _Rhizopus_ spp., shows a stronger correlation with organic nitrogen, suggesting a different degradation pathway or nitrogen assimilation process. Cluster 3, where residues were treated with a combination of _Colletotrichum_ spp. and _Rhizopus_ spp., is associated with higher ash content and organic nitrogen levels, reflecting advanced degradation and mineralization stages. These relationships highlight the differential effects of fungal treatments on the decomposition dynamics of sugarcane residues. Additionally, Cluster 1 was determined to have the lowest biodegradation index because it is more closely associated with higher values of organic matter and organic carbon. This indicates that the samples in this cluster retain a greater proportion of biodegradable material, suggesting lower degradation efficiency. In contrast, Clusters 2 and 3 show higher associations with organic nitrogen and ash content, which are indicative of more advanced biodegradation stages. In one study, [PERSON] and [PERSON] [40] emphasize the importance of evaluating the stability and maturity of a compost, since an immature and unstable compost has the potential to cause a series of problems in crops, such as self-heating, odor emission, inhibition of germination, and phytotoxicity. Within the classification of compost maturity tests, classical chemical tests include evaluations of the carbon/nitrogen ratio, organic matter, humification parameters, exchange capacity, pH, and spectroscopy, among others [41].