Methods for measuring N2O flux from water surface and N2O dissolved in water from agricultural land

A new chamber method and a stripping method were developed for field measurements of the rate of N₂O emission from the water surface and for determinations of dissolved N₂O in water from agricultural land.

These methods were used for the measurement of drainage canal water and flooded water of rice fields during the period of June 1982 to January 1983. The results demonstrate that aquatic systems of agricultural land may provide both source and sink for atmospheric N₂O.     

Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton

Cotton is a perennial plant with an indeterminate growth pattern that is typically produced like an annual, but requires proper management to effectively produce high yields and good fiber quality in a thermally limited environment like the northern Texas High Plains. In 2007 and 2008, we investigated the effect of irrigation scheduling/control method and amount on cotton (Gossypium hirsutum L.) yield and water use efficiency. Methods were automatic irrigation scheduling and control of a center pivot system, and manually scheduled irrigation to replenish soil-water to field capacity. Cotton was irrigated with LEPA (low energy, precision application) drag socks in furrow dikes; three blocks were irrigated manually and three were irrigated automatically. Six replicates of the manual and automatic irrigation treatments were included in the randomized block design. Manual irrigations were based on the weekly replenishment of soil-water to field capacity in the top 1.5 m of the soil profile and included a fully irrigated treatment (I₁₀₀), and treatments receiving 67% (I₆₇) and 33% (I₃₃) of the I₁₀₀ amount, plus a non-irrigated treatment (I₀). Automatic irrigations were triggered using a time temperature threshold (TTT) algorithm, which was designated as the I₁₀₀ treatment, and treatments receiving 67%, 33%, and 0% of that amount (I₆₇, I₃₃ and I₀, respectively). In 2007, overall mean lint yields (102.3 and 101.6 g m⁻², manual and automatic, respectively) were not significantly different. Similarly, yields were not significantly different across automatic and manual treatments in the same treatment level, with the exception of the I₆₇ treatment where the manual treatment yields were 11% greater. In 2008, the mean yields were 70% less than those in 2007 for both methods of irrigation (30.3 and 30.9 g m⁻², manual and automatic, respectively) due to harsh climatic conditions at emergence and heavy rainfall and cooler temperatures in the month of August. Yields from the automatically irrigated plots in the I₁₀₀ and I₆₇ treatments, however, were significantly greater than yields from the corresponding manually irrigated plots; though there was no significant difference between yields in the drier treatments (I₃₃ and I₀) plots. These results indicate that the TTT algorithm is a promising method for auto-irrigation scheduling of short season cotton in an arid region. However, further studies are essential to demonstrate consistent positive outcomes.     

粉胶比对沥青混合料路用性能影响的试验研究

合理的粉胶比有利于提高沥青混合料的路用性能。试验在不同粉胶比条件下,通过车辙试验、低温弯曲试验、浸水马歇尔和冻融劈裂试验,分析沥青混合料的高温性能、低温性能和水稳性的变化,以确定合理的粉胶比范围。试验结果表明：粉胶比的增大,动稳定度增大,在粉胶比为1.2时出现峰值,随后开始下降;弯拉应变随粉胶比的增大而增大,粉胶比在1.0-1.1之间达到峰值,之后开始减小;劲度模量先减小后增大,呈凹形曲线,粉胶比为1.0时达到最小值;残留稳定度随粉胶比变化呈现增加后减小变化,最大值出现在粉胶比为1.0左右;冻融劈裂强度比先增大后减小,最大值在1.0-1.2范围内。综合考虑,在进行沥青混合料配合比设计时,粉胶比宜控制在0.9-1.2范围内。     

Automated canopy temperature estimation via infrared thermography: A first step towards automated plant water stress monitoring

Canopy temperature estimation is an important process for plant water status monitoring. In this paper the problem for measurement data of the scene acquired via an infrared (IR) thermography system is considered. An optical image taken from the plant canopy is aligned with the underlying IR image, so that plant leaf area can be extracted via simple colour identification techniques and then the temperature distribution of the leaf area is obtained. The success of this procedure relies on the assumption that both optical-IR image alignment and leaf area extraction are perfect. In practice, such assumptions are rarely justifiable and the computed result can often be found undesirable. Particularly, the simple colour identification technique fails when temperatures of reference leaves, which are embedded in the canopy and provide known conductance to water vapour, are required to be estimated. In this paper, we address this issue and propose a novel algorithm to solve the problem. The underlying plant leaf temperature distribution is considered to be the fusion of two temperature densities separable via a combination of colour identification and Gaussian mixture distribution extraction techniques. A N-average method is tested with moderate success to estimate reference leaf temperatures from the estimated leaf temperature distribution. Our experimental results demonstrate the effectiveness and consistency of the proposed algorithm.