Warren-Vega Walter M, Aguilar-Hernández David E, Zárate-Guzmán Ana I, Campos-Rodríguez Armando, Romero-Cano Luis A
Grupo de Investigación en Materiales y Fenómenos de Superficie, Departamento de Ciencias Biotecnológicas y Ambientales, Universidad Autónoma de Guadalajara, Av. Patria 1201, Zapopan CP 45129, Jalisco, Mexico.
Consejo Regulador del Tequila A. C., Av. Patria 723, Zapopan CP 45030, Jalisco, Mexico.
Foods. 2022 Apr 14;11(8):1138. doi: 10.3390/foods11081138.
The interest of consumers to acquire Tequila has caused an increase in its sales. As demand increases, the Tequila industry must obtain its raw material at a constant rate and agave farmers must be prepared to satisfy this supply chain. Because of this, modernization of the strategies used to ensure a planned, scheduled, timely, and predictable production will allow farmers to maintain the current demand for Tequila. This has been evidenced in official historical records from 1999 to 2020 where there is a fluctuation in the price of agave due to supply and demand. Given this scenario, this research shows the development of a multivariable predictive mathematical model that will permit the agave−Tequila production chain to work based on a smart implementation of planned actions to guarantee the agave supply to the Tequila industry. The proposed model has a goodness of fit (R = 0.8676; R¯2 = 0.8609; F(1,20) = 131.01 > F0.01 (1,20) = 8.10) and demonstrates the impact on agave prices is due to several factors: Tequila exports (α = 0.50) > agave plants harvested “jima” (α = 0.44) > dollar exchange (α = 0.43) > Tequila production (α = 0.06) > annual accumulated precipitation (α = 0.05). Nevertheless, the price forecast can be influenced by climate change or economic crises that affect the supply chain. In conclusion, a prediction of agave price stabilization for five years is shown where authorized producers can evaluate future scenarios so that the agave supply chain can be guaranteed for Tequila production, facilitating the decision making regarding its raw material.
消费者对龙舌兰酒的兴趣促使其销量增加。随着需求的增长，龙舌兰酒行业必须以恒定的速度获取原材料，龙舌兰种植农户必须做好准备以满足这一供应链的需求。因此，用于确保有计划、按预定时间、及时且可预测的生产的策略现代化，将使农户能够维持当前对龙舌兰酒的需求。这一点在1999年至2020年的官方历史记录中得到了证明，其中龙舌兰的价格因供需关系而波动。在这种情况下，本研究展示了一个多变量预测数学模型的开发，该模型将使龙舌兰 - 龙舌兰酒生产链能够基于对计划行动的智能实施来运作，以保证向龙舌兰酒行业供应龙舌兰。所提出的模型具有良好的拟合度（R = 0.8676；R¯2 = 0.8609；F(1,20) = 131.01 > F0.01 (1,20) = 8.10），并表明对龙舌兰价格产生影响的因素有多个：龙舌兰酒出口（α = 0.50）> 收割的龙舌兰植株数量“希马”（α = 0.44）> 美元汇率（α = 0.43）> 龙舌兰酒产量（α = 0.06）> 年累计降水量（α = 0.05）。然而，价格预测可能会受到影响供应链的气候变化或经济危机的影响。总之，展示了对龙舌兰价格稳定五年的预测，授权生产商可以据此评估未来的情况，从而确保龙舌兰酒生产的龙舌兰供应链，便于就其原材料做出决策。
