## 3 Results and Discussion  
### Climatic Analysis  
The Kruskal-Wallis H test revealed a significant difference in the dependent variables of climate and soil temperature among the various groups (\(\chi\)2(7) = 1004.68, \(p\) < 0.001; \(\chi\)2(11) = 1456.74, \(p\) < 0.001). After analyzing the set of climate variables, only precipitation, wind speed, and maximum temperature exhibited statistical significance following the ANOVA test among the seven climate variables. Regarding soil temperature, all variables displayed significant differences among the nine climate cacao production clusters. However, it is not anticipated that all comparisons between clusters, climate, and soil temperature variables would yield significant differences. We identified that the nine predetermined climate clusters for cacao in Arauca (24) have specific climate and soil temperature conditions (Figures 1 and 2). These new results reaffirm that there are significant climate differences among cacao regions in Arauca, allowing us to support the presence of nine agroclimatic clusters of cacao production. In general, our findings indicate that climate variables play a less influential role than soil temperature variables in potentially explaining the climate variations among the nine predetermined climate clusters in Arauca. Figure 1 illustrates the climatic variables that significantly influence the clustering of the cacao farms in the nine agroclimatic clusters of cacao production. Focusing on the three significant climate variables, we observe that the area encompassing clusters 2 and 3 in the northern region of Arauca exhibited the highest wind speeds in the entire region, whereas closer to the cordillera, the wind speed was lower (Figure 1a). Clusters 9, 1, and 4 showed significant differences in maximum temperatures for being the hottest of all areas in the region (Figure 1b). Regarding rainfall, clusters 6 and 7 closer to the foothills showed the highest precipitation values, distinctively unlike clusters 2 and 3 in the north of Arauca, which are exposed to less rainfall (Figure 1c). The influence of soil temperature variables in supporting the presence of the nine clusters was found to be stronger than that of climate variables. Surprisingly, all 11 soil temperature variables exhibited significant differences between them and the nine clusters (Figure 2). This finding suggests that changes in the microclimate of the soil may exert a stronger influence on the cacao genotypes than mere macroclimate variables. Specifically, soil climate variables related to changes in seasonality, as well as maximum and minimum ranges such as isothermality (Figure 2c), temperature seasonality (Figure 2d), and temperature annual range (Figure 2g), demonstrated the strongest influence in explaining the differences among clusters in Arauca. Figure 1: Multiple comparisons in climate variables in the 180 farms classified as nine clusters in Arauca. Values with the same letter are not statistical differences among clusters (ANOVA, [PERSON]’s test, \(p<0.05\)). Charts framed in a rectangle mean variables statistically significant. (**a**) \(p\)-value = 0.0439869, [\(p\)(x \(\leq\) F) = 0.956013]; (**b**) \(p\)-value = 0.0462364, [\(p\)(x \(\leq\) F) = 0.953764]; (**c**) \(p\)-value = 0.0000992048, [\(p\)(x \(\leq\) F) = 0.999901]. Remarkably, a substantially similar overarching pattern was observed in the soil temperature analysis, where the cooler and more humid clusters in the western foothills of the cordillera stood distinct from the hotter and drier areas in the eastern zones of Arauquita  
Figure 2: Multiple comparisons in soil temperature in the 180 farms classified as nine clusters in Arauca. Values with the same letter are not statistical differences among clusters (ANOVA, Tukey’s test, \(p\) < 0.05).