线性数学在Gayo阿拉伯咖啡配方优化调配中的应用

Dian Hasni, S.TP., M.Sc, Muhammad Nazawi, Heru Prono Widayat, Murna Muzaifa, Yusya' Abubakar
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引用次数: 0

摘要

咖啡是印尼的一种商品,售价很高。加约高地以亚齐的阿拉比卡咖啡种植园而闻名,那里通常种植三种当地品种。这些是Timtim或Gayo 1, Borbor或Gayo 2和Ateng Super。3个品种均为精品咖啡,杯子测试分数分别为84分、50分(Timtim)、85.25分(Borbor)和85.50分(Ateng Super),香气和风味各具特色。为了优化咖啡的杯化质量,在咖啡冲泡前混合是一种常见的做法。本研究旨在利用简单的线性数学模型,对当地3个85以上阿拉比卡咖啡品种混合咖啡的总杯试验进行优化。假设预测的杯子测试分数与实验室的杯子测试分数相等。在前人研究的基础上,利用3个地方品种建立了7个配方。然后基于属性分数和品种比等特定约束条件建立了两个线性模型。这七个公式在两个指定的线性模型中作为两个重复计算。第一个模型的预测分数在84,15-85,38之间,平均值为84,88;第二个模型的预测分数范围为84,07-85,13,平均值为84,80。从这七个公式中,在这两个线性模型中,R3和R7预测的杯子测试分数超过85分。通过t检验,实验室得分与预测得分之间无显著差异。可以说,假设是可以接受的,这两个线性模型可以单独或有意地用于预测混合咖啡在混合前的杯子测试分数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Apilikasi Matematika Linear Dalam Penyusunan Formulasi Optimum Pencampuran Kopi Arabika Gayo (Coffeea Arabica. L)
Coffee is an Indonesian commodity that has a high selling price. Gayo Highland is known for arabica coffee plantation site in Aceh, where commonly three local cultivars are cultivated. These are Timtim or Gayo 1, Borbor or Gayo 2 and Ateng Super. All three cultivars complied as specialty coffee with cuptest score 84,50 (Timtim), 85.25 (Borbor) and 85.50 (Ateng Super) and each cultivar has distinctive aroma and flavour. Blending is one common practice before coffee brewing in order to optimize the cupping quality of coffee. This study aims to optimize the total cup test of blended coffee from three local cultivars of arabica coffee over 85 by using simple linear mathematics models. The hypotheses was a predicted cuptest score is equivalent with the laboratory cuptest score. Based on previous research, seven formulations were set up by using three local cultivars. Then two linear models were created based on specific constraints such as attribute score and cultivar ratio. The seven formulations are calculated in two assigned linear models as two replications. First model produced predicted score in between 84,15-85,38 and mean 84,88 whilst second model has a score range 84,07-85,13 with mean 84,80.  From all seven formulation, in these two linear models R3 and R7 has predicted cuptest score over 85. By using t-test, there is not significant difference available within the laboratory score and predicted score. It can be said the hypotheses is accepted and these two linear models could be used separately and or intentionally to predict cuptest score of blended coffee before blending is performed.
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