Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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YGLV6
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
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Industry of roasted and ground coffee uses Coffea arabica L. (arabica) and Coffeacanephora(robusta), main coffee species, to form blends consumed worldwide. In addition to blends composition, industries also vary the roast degree to attend the consumer market. Being that stated, this work aimed to evaluate the influence of roasting degree and blends composition, using sensorial analysis, over the product acceptability. Arabica and robusta coffee were dehulled, classified, and roasted at Agtrons numbers SCAA#65 (medium-light) e SCAA#45 (moderately dark). Afterward, the authors made a preliminary test to select the blends for conventional consumers as a function of robusta coffee percentage. After the selection and determination of adequate proportion (0, 30, and 60 % m/m) of robusta coffee, the researchers invited 49 consumers to perform the tests. The researchers used preliminary tests to indicate that 29 out of the 49 consumers are capable to complete the tests. They performed the sensorial analysis of the blends, signaling grades from 1 to 9 to flavor, aroma, and appearance. Blend composition presented a higher impact over the coffee acceptability than the roast degree, in which coffee with 0% of robusta coffee, independently of the roast degree, followed by sample with 30% of robusta coffee roasted at medium light, presented the highest grades.
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