绿茶揉捻叶干燥过程中叶温变化预测

茶叶在干燥过程中其叶温的变化显著地影响着其含水率的变化,叶温制约着茶叶内含物热化学反应的速率和方向。在干燥过程中,叶温掌握高低与否,将产生出不同品质的茶叶,包括色泽、香气和味觉等。因此,茶叶叶温变化规律能被精确地预测,就可实现茶叶在加工过程中叶温的自动控制,制茶质量可望被改善。至今为止。

基于叶温监测的龙井茶机制过程关键控制点的识别

叶温的变化影响着茶叶内含物的热化学转化,决定着茶叶色泽、香气和滋味的形成。本研究利用K型热电偶监测龙井茶炒制过程中叶温及含水量的变化,结果表明,1)茶叶炒制过程中叶温随时间的变化曲线可分为3个阶段:第一阶段,茶叶下锅炒制3 min,温度从40℃快速上升至58℃;第二阶段,时长6 min,温度持续缓慢上升至70℃;第三阶段,时长2 min,温度快速上升至80℃。2)叶片含水量与叶温变化相反,变化曲线呈反向S型,可分为平台期(50℃以内,含水量下降缓慢)、快速失水期(50～70℃,含水量急剧下降)和缓慢失水期(70℃以上,含水量降速随温度的上升而变缓) 3个阶段。3)快速失水期为茶叶塑形关键点,缓慢失水期可以作为干燥适度的关键控制点。

Soil carbon dioxide fluxes of a typical broad-leaved/Korean pine mixed forest in Changbai Mountain, China

The forest ecosystem plays an important role in the global carbon cycling. A study was conducted to evaluate soil CO2 flux and its seasonal and diurnal variation with the air and soil temperatures by using static closed chamber technique in a typical broad-leaved/Korean pine mixed forest area on the northern slope of Changbai Mountain, Jilin Province, China. The experiment was carried out through the day and night in the growing season (from June to September) in situ and sample gas was analyzed by a gas chromatograph. Results showed that the forest floor was a large net source of carbon, and soil CO2 fluxes had an obvi-ous law of seasonal and diel variation. The soil CO2 flux of broad-leaved/Korean pine mixed forest was in the range of 0.302.42 mmol穖-2穝-1 with the mean value of 0.98 mmol穖-2穝-1. An examination on the seasonal pattern of soil CO2 emission suggested that the variability in soil CO2 flux could be correlated with variations in soil temperature, and the maximum of mean CO2 flux occurred in July ((1.27±23%) mmol穖-2穝-1) and the minimum was in September ((0.50±28%) mmol穖-2穝-1). The fluctuations in diel soil CO2 flux were also correlated with changes in soil temperature; however, there existed a factor for a time lag. Soil CO2 flux from the forest floor was strongly related to soil temperature and had the highest correlation with temperature at 6-cm depth of soil. Q10 values based on air temperature and soil temperature of different soil depths were at the ranges of 2.09–3.40.

Significance of Transients in Soil Temperature Series

The primary objective of this study was to investigate the impact of observation scale on the estimation of soil thermal properties.Transients are usually filtered out and ignored when classical Fourier approaches are used to deconstruct and model temperature time series.It was hypothesized that examination of such transients may be more important in identifying and quantifying short-term perturbations in internal soil heat transfer induced by agronomic disturbances. Data-logged temperatures were collected at 10-minute intervals from thermistor probes installed at 10 and 25 cm depths in isolated areas of two grassed plots.One plot(6T)had been treated twice with 6 Mg ha^(-1)composted turkey litter as received.The other plot(NPK)was fertilized at the same time with NPK fertilizer.Various methods were used to analyze the series to obtain apparent soil thermal diffusivity(D-value)at various time scales.Results supported the hypothesis that short-term differences in internal soil heat transfer between the 6T and NPK plots were more manifest and effectively captured by estimated D-values calculated from the monthly and daily partial series.The 6T plot had higher soil organic matter content than the NPK plot and had lower apparent soil thermal diffusivity.Diurnal soil temperature amplitudes, required to calculate the mean D-values from partial series,were more effectively obtained using a temperature change rate method.The more commonly used Fourier analysis tended to be effective for this purpose when the partial series reasonably presented well-defined diurnal patterns of increasing and decreasing temperatures.

Effects of climate change on potential habitats of the cold temperate coniferous forest in Yunnan province, southwestern China

We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the current and future climates, using seven climate change scenarios, projected over the years of 2070-2099. The accurate CT model on CTCFs showed that minimum temperature of coldest month （TMW） was the overwhelmingly potent factor among the six climate variables. The areas of TMW〈-4.05 were suitable habitats of CTCF, and the areas of -1.35 〈 TMW were non-habitats, where temperate conifer and broad-leaved mixed forests （TCBLFs） were distribute in lower elevation, bordering on the CTCF. Dominant species of Abies, Picea, and Larix in the CTCFs, are more tolerant to winter coldness than Tsuga and broad-leaved trees including deciduous broad-leaved Acer and Betula, evergreen broad- leaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35℃ and -4.05℃, and the warm-side distributions of CTCFs may be controlled by competition to the species of TCBLFs. Under future climate scenarios, the vulnerable area, where current potential （suitable ＋ marginal） habitats （80,749 km^2） shift to non-habitats, was predicted to decrease to 55.91% （45,053 km^2） of the current area. Inferring from the current vegetation distribution pattern, TCBLFs will replace declining CTCFs. Vulnerable areas predicted by models are important in determining priority of ecosystem conservation.

Vegetation Dynamics and Its Relationship with Climatic Factors in the Changbai Mountain Natural Reserve

This study examined the temporal variation of the Normalized Difference Vegetation Index （NDVI） and its relationship with climatic factors in the Changbai Mountain Natural Reserve （CMNR） during 2000 - 2009. The results showed as follows. The average NDVI values increased at a rate of 0.0024 year-1. The increase rate differed with vegetation types, such as 0.0034 year-1 for forest and 0.0017 year-1 for tundra. Trend analyses revealed a consistent NDVI increase at the start and end of the growing season but little variation or decrease observed in July during the study period. The NDVI in CMNR showed a stronger correlation with temperature than with precipitation, especially in spring and autumn. A stronger correlation was observed between NDVI and temperature in the tundra zone （2,000-2,600m） than in the coniferous forest （1,100-1,700m） and Korean pine-broadleaved mixed forest （7oo-1,1oom） zones. The results indicate that vegetation at higher elevations is more sensitive to temperature change. NDVI variation had a strong correlation with temperature change （r=0.7311, p〈0.01） but less significant correlation with precipitation change. The result indicates that temperature can serve as a main indicator of vegetation sensitivity in the CMNR.