摘要:
小气候因子对春茶产量有着重要影响, 建立其相关关系可以更好地为春茶的生产管理服务。本文测定记录了春茶生产期间18个小气候因子及每天茶叶的产量, 应用多元统计分析方法建立了春茶产量与小气候因子的回归模型, 并对茶树生长的小气候因子进行聚类分析和因子分析, 以找出决定春茶产量的小气候因子及其组合。结果表明, 春茶产量与大多数小气候因子间具有显著的线性回归关系, 可以此对春茶产量进行预测预报。另外, 采用逐步回归方法剔除次要的自变量因子, 保留对春茶产量影响较大的小气候因子, 最少可用7个自变量进行回归拟合。聚类分析可以把茶园小气候因子划分为表征水、热特征的4类。因子分析也表明, 温度、水分及其组合是诸环境变量的公因子, 具有较大的载荷。研究表明, 采用较少的环境因子, 回归模型仍具有显著性, 这样可有效降低环境因子的监测和生产管理成本, 为有计划地安排春茶生产和提高经济效益服务。
关键词:
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茶园 /
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小气候 /
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气候因子 /
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回归模型 /
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春茶 /
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产量
Abstract:
Microclimatic factors have significant effects on yield of spring tea. Regression relations derived from these factors are crucial for the management of spring tea. 18 microclimatic factors and tea outputs were measured during spring tea harvest season. The relationships between yield of spring tea and microclimatic factors were explored. Using the multiple stepwise regression analysis, empirical yield models of spring tea were fitted to microclimatic factors, achieving a high confidence level. These models with different factors show similar and significant regression trends. Eighteen microclimatic factors are categorized into four groups through cluster analysis. Factor analysis indicates that common microclimatic factors of the environment variables are temperature, water and their combination factor, which own bigger load. In conclusion thus, an economic method can be established through measuring fewer microclimatic factors with significant regression models. Such economic methods can achieve similar outcomes with fewer investment, management and processing of spring tea. This can significantly benefit spring tea cultivation and economy.
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