## 4 Results and Discussion
### Discussion  
We undertake the analysis of the response surfaces of these fuzzy logic-based decision-making rules. Fuzzy logic is the decision-making rule approach used to generate a knowledge base for the CP Agent, the GS Agent, and the GP Agent as described in Section 3.3. The CP Agent comprises the Cherry coffee-growing yield estimation model, the hectares available for planting and the precipitation and agricultural practices data are used as input. The GS Agent uses the Parchment coffee sample' quality scoring model with the gustatory and olfactory attributes of the sample as input data. The GP Agent comprises the Parchment coffee entries sorting process scheduling model, the percentage of defective coffee beans and the percentage of humidity of the coffee entry are used as input data. Appendix A  
Figure 9: Updated production schedule for decreasing demand and t\({}_{\text{mod}}\) = 7 and E\({}^{-}\) = 2  
describes the operating values for the fuzzy sets of the Fuzzy models of Cherry coffee-growing yield; quality scoring of the Robusta coffee sample; quality scoring of the Parchment coffee sample; sorting process scheduling of not-washed Robusta coffee entries; sorting process scheduling of Robusta coffee entries; and sorting process scheduling of Parchment coffee entries. Regarding the Cherry coffee-growing yield model, the factors that have a significant effect on coffee yield are nutrition, pruning, and control of pests. The factors that have a significant effect from high values are nutrition and pruning. The factor that has a significant effect from low values is control of pests. The factors that do not have a negative effect on coffee yield are rainfall and temperature. The study of [PERSON] and [PERSON]. [55] also found that adequate nutrition along with optimal planting density is expected to show high yield responses in coffee plantations. For the Parchment coffee samples' quality scoring model, ferment, sour, malodorous (FSM) is the factor that has a significant effect on coffee samples' quality score. For the Altura coffee, acidity, chemical taste, flavor, aroma, and body must have high values. For the Extra prima coffee, aroma, acidity, and body must be contained in the medium values. For the Robusta coffee samples' quality scoring model, the malodorous factor has a significant effect on the quality score, from medium values the coffee can be rejected, likewise, when sour is in the high values and ferment in the medium values. The factors that do not have a significant effect on the quality score are old and earthy. The factor that has a significant effect from high values is mold and sour. The presence of both factors, mold and old, has a significant effect on the quality score when they occur at high values. Through the development of a fuzzy expert system for sensorial evaluation of coffee bean attributes to derive quality scoring, [PERSON] and [PERSON] [38] found the ranges of the values of the attributes for the lowest and highest quality scores considering Fragrance, flavor, aftertaste, acidity, body, uniformity, balance, clean cup, sweetness, overall, and defects. Also from a fuzzy logic approach, the study of [PERSON] and [PERSON] [39] conducted a similar analysis with the attributes brew, aroma, taste, aftertaste, and body. Regarding the Parchment coffee entry sorting process scheduling model, both, Serious defects and minor defects, have a significant effect on sorting process scheduling. The green aspect factor does not have an effect on sorting process scheduling. The pellet factor has a significant effect from low values on sorting process scheduling. The humidity factor has a significant effect from medium to high values and results in complex sorting sequences. For the Robusta coffee entry sorting process scheduling model, both, serious defects and minor defects, have a significant effect from medium to high values on sorting process scheduling. The pellet factor has a significant effect from low to medium values on sorting process scheduling.