產地氣候變化對於蔬菜價量之影響-以青江菜為例

Abstract

雲林縣為全臺蔬菜種植面積最大的縣市，供應臺灣三分之一蔬菜量，其中葉菜類為我國大宗消費蔬菜類別，但其生長快速且生長期短，加上葉片組織柔軟細嫩，容易受到風雨侵襲損害而腐爛，因此受氣候影響甚鉅，造成價格波動大。 合作社在蔬菜運銷流程上扮演緩衝與調控之功能，可以讓菜價在市場上供需穩定，而案例合作社之通路包含臺北一、西螺與高雄果菜市場，其中果菜市場之交易又分為拍賣交易與議價交易之市場機制，過去研究指出拍賣交易為主之市場其決價效率比議價交易為主之市場較佳，因此本研究期許能透過分析產地天氣波動了解拍賣市場之變化，並分析是否對合作社之價量造成影響。 本研究利用葉菜類主要產地，雲林縣四湖鄉之氣候資料進行分析，以瞭解產地氣候因子是否影響拍賣市場與合作社出貨之價量關係。藉由天氣因子分析北中南主要果菜市場批發價之關聯，利用多元線性迴歸法估計作為實證模型，探討氣候對於不同拍賣市場生產決價之關聯性，也分析不同拍賣市場與合作社之價量之關聯性。本研究利用平均溫度、降雨量、最大瞬間風速等氣候條件與月份進行迴歸分析。結果顯示，氣候中溫度與六至十月對於臺北一與西螺果菜批發市場菜價有顯著正向之影響，而高雄市場只有六月至十月對於菜價有顯著相關。對於合作社溫度、降雨量、天災與月份皆對菜價有顯著之影響。 透過本研究得知合作社青江菜價格受較多天氣因子影響，其原因推測價格直接與生產端有直接之關聯，然而作為中介角色，合作社價格上與消費端也有直接關聯，但在此研究並無討論，因此未來研究也可加入消費端之相關因子進行分析，並作為未來合作社之進行產銷決策與農產品訂價主要參考依據，以維護生產者之利潤，保障消費者之權益。

Yunlin county provides one third of vegetable production. The leafy vegetable is the major consumption category in Taiwan. However, the rapid growth rate, short period and the soft tissue of the leaf, which make it easier to rotten by the weather change which leads the price fluctuant. The cooperative farm plays a role for buffering and regulation in the sales management, which could stabilize the balance of supply and demand. The distribution of the case cooperative farm which including Taipei first wholesale fruit and vegetable market (TFWFV), Hsilo agricultural product market (HAPM) and Kaohsiung fruit and vegetable marketing companies (KFVM). These mechanisms of the markets including auction and bargain. In the previous study shows the efficiency of auction is better. Hence the research is using the fluctuant of the weather to under the mechanism in the market to analysis the effect to the price of Qingjiang in cooperative farms and wholesale markets. To understand the correlation between local weather and the price of Qingjiang price in different markets. The study uses the weather data from Sihhu township, Yunlin County as the information of place of production, the factors which including average temperature, precipitation, maximum instantaneous wind speed, wind direction and months for the multiple regression analysis. The results show the average temperature and months from June to Oct have the positive correlation with TFWFV and HAPM, but KFVM only affect by the months. In addition, the price of Qingjang in cooperative farm affects by the average temperature, precipitation, type and flood and months. The study shows the price of Qingjiang affect by the factors of weather compare with the wholesale’s markets. We assumed the price have high correlation with production end. The cooperative farm could play a role of the stabilize the fluctuant from the price. However, the consumer end other than the wholesale markets did not consider in the study, which may be an important factor in the regression model. Taking together, to consider both production and consumer factors which may provide a better model for pricing strategy, which could protect the right of the farmers and consumers.