Coffee Science_v.19, 2024
URI permanente para esta coleção${dspace.url}/handle/123456789/14639
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Item System dynamic model of green supply chain management robusta coffee Argopuro in Indonesia: A case study(Universidade Federal de Lavras, 2024-06-19) Purnomo, Bambang Herry; Ni’maturrakhmat, Viko Nurluthfiyadi; Wibowo, YuliSmall-scale Argopuro Robusta coffee agroindustry has the potential to harm the environment in every supply chain activity. Even though the waste processing process has been carried out, this is still not enough to reduce the environmental impact. Performance measurement of Green Supply Chain Management (GSCM) in the business is complex because it considers environmental indicators and operational business as a whole. GSCM performance is also dynamic because the behavior of the supply chain system often changes over time. Therefore, it is necessary to develop a performance diagnosis model that has complex and dynamic characteristics through a system dynamic model. This research aims to diagnose and improve the GSCM performance index for currently and future using a system dynamic model. The scope of the model starts from harvesting coffee cherries to selling processed products. Research result shows that there are 13 performance indicators. The indicator values are then determined using the system dynamic model to obtain an index value of GSCM. The simulation results show that in 2023, the GSCM performance value will be 35.40, which is included in the good enough status, and 2035 the performance value increase by 54.8. To improve its performance, an optimistic scenario is used. This scenario is built by providing intervention to increase the percentage of waste processing by 90% for solid waste and 70% for liquid waste. Increase the number of pickup trucks by 4 units and reduce the motorcycle by 45 units to be more optimal and reduce the amount of emissions produced. The simulation results show that with that scenario the GSCM performance index was successfully increased to 68.2 (good status) in 2035.Item Descriptive sensory tests for evaluating Coffea arabica: A systematic review(Universidade Federal de Lavras, 2024-04-20) Nascimento, Manuella Oliveira; Ombredane, Alicia Simalie; Oliveira, Livia de Lacerda deCoffee is a beverage whose price is closely related to the characteristics of its flavor, necessitating reliable sensory tests. To quantify their sensory attributes, classic sensorial methods such as Quantitative Descriptive Analysis (QDA) can be useful. However, uncertainties persist due to protocol variations, which made uncertain the quality of these protocols in evaluating coffee. This study aimed to conduct a systematic review to assess the quality of QDA protocols used for assessing Coffea arabica’s sensory attributes. The review encompassed various critical protocols control points, including pre-test procedures, coffee processing and preparation techniques, test application and data collection procedures. It was also summarized key attributes, highlighting factors impacting coffee’s sensory traits and bias risk of the studies. As the main results, it was saw that the studies have many limitations, such as not citing or controlling critical points in the tests procedures and application, which made most studies having a medium-high bias rating. The primary sensory results findings of the studies included topics such as the impact of brewing time, chemical compounds associated with sensory attributes and the effect of various roasting techniques on the sensory qualities of coffee. In conclusion, standardizing sensory evaluations in future research could enhance consistency and accuracy, yielding less biased results.