基于视觉的苗期作物株间除草关键技术研究现状

基于视觉的苗期作物和杂草的图像分割技术逐渐成熟,通过视觉技术对苗期作物进行精准识别和定位,是实现株间除草的关键技术和难点。作物的精准识别首先需要利用颜色特征将图像中的作物、杂草和土壤背景进行分割;其次利用实际识别对象的位置特征,形状特征,纹理特征,光谱特征等构造新的特征向量,结合成熟的分类算法对作物和杂草进行特征分类识别。针对棉苗和大豆苗,主要提取位置特征、形状特征,多采用支持向量机为主分类算法;针对玉米,主要提取位置特征、纹理特征,多采用人工神经网络为主的分类算法;针对部分蔬菜苗,主要提取形状特征、光谱特征,多采用算法结合的优化算法,具体实现时需要根据离线样本学习的结果来平衡苗期作物的识别准确率与实时性。在目前的算法中,主要存在三方面的问题:作物特征提取效果易受到遮挡、光照等干扰;分类算法目前还不能得到非常令人满意的准确性和实时性;目前算法一般是针对某种时段的作物,不具有通用性。这些都是后续算法研究中需要进一步解决的问题。     

厢式运输车前轮主销后倾角改进设计

基于轮胎侧偏特性建立前轮转向后回正力矩数学模型 ,根据转向轮回正力矩与回正阻力力矩平衡方程式 ,计算了 5 0 2 1型厢式运输车主销后倾角 ,按照国标 GB/T6 32 3.4 - 94的要求做了转向回正试验 ,验证了理论分析和设计计算的正确性 ,为前轮定位参数中主销后倾角的设计提供理论参考。     

Demography,population dynamics and sustainability of the Patagonian sheep flocks

Sheep production is the main agricultural activity in Patagonia. Since the middle of the 20th century, sheep numbers have declined steadly. We used historical records of stock numbers in four ranches to analyze the importance of regional factors so as to explain the decline of the Patagonian sheep flocks. We found that the stocks of all the four ranches declined with a similar trend but fluctuated independently, thus reflecting a complex interaction between regional and local factors. Aboveground net primary production (ANPP) and vegetation physiognomy explained most of the differences in the flocks declining rates. We estimated demographic parameters for two ranches differing in their average annual growth rates. From these demographic parameters, we constructed deterministic and stochastic matrix models to establish the relative contribution of demographic processes to the observed decline. Matrix models projected a faster decline than that observed in the ranch used to calibrate the model. This suggests that the recorded demographic parameters could drive most stocks to extinction in less than 100 years. We concluded that the observed dynamics would be generated by demographic processes, but extinction is delayed or avoided by a continuous intake of animals. Ewe survival was the most important parameter in controlling the growth rate of the flocks. The environmental stochastic model showed that the growth of the stocks was highly sensitive to increases in the frequency of good years (those that produce a positive growth) and in the transition from normal years to bad years. All these evidences point out the existence of biological constraints to sheep production in Patagonia: ANPP and vegetation structure would control flock population dynamics throughout its effects on key demographic parameters, ewe survival and marking rate (a recruitment measure). Our model results suggest that the decline in sheep numbers, and hence the sustainability of the activity, is driven, to a large extent, by the demographic characteristics of the flocks.     

From on-farm solid-set sprinkler irrigation design to collective irrigation network design in windy areas

In this paper, a contribution to the design of collective pressurised irrigation networks in solid-set sprinkler-irrigated windy areas is presented. The methodology is based on guaranteeing minimum on-farm performance, using a historical hourly wind speed database and a ballistic solid-set irrigation simulation model. The proposed method was applied to the Montesnegros Irrigation District (central Ebro basin, Spain). The district irrigates an area of 3493 ha using an on-demand schedule. The average wind speed in the area is 2.8 m s⁻¹. An analysis of district water records showed that farmers often reduce water demand when the wind speed is high, but their irrigation decision making is limited by the capacity of the irrigation network and by the unpredictable character of local winds. Simulations were performed for 11 irrigation seasons, 2 triangular sprinkler spacings (18 m × 18 m and 18 m × 15 m), and 2 sprinkler models. The percentage of monthly suitable time for irrigation was determined for four management strategies. The first one was based on a wind speed threshold (3 m s⁻¹), while the other three were based on three levels (standard, relaxed and restrictive) of two irrigation performance parameters: the Christiansen Uniformity Coefficient (CU) and the Wind Drift and Evaporation Losses (WDEL). The standard strategy classified the time as suitable for irrigation when CU ≥ 84% and WDEL ≤ 20%. The thresholds limits of the irrigation parameters for the relaxed strategy were CU ≥ 80% and WDEL ≤ 25%. Finally, the restrictive strategy used thresholds of CU ≥ 90% and WDEL ≤ 15%. The suitable time for the first strategy (56%) was always lower than for the standard and the relaxed strategies (with respective average values of 75 and 86%), and higher than for the restrictive strategy (30%). In order to design the collective network, the hydrant operating time was equalled to the suitable time for irrigation. The differences in the cost of the collective network plus the on-farm equipment were particularly relevant between the restrictive strategy and the other three. Differences in suitable operating time were clear between sprinkler spacings, and less evident between sprinkler models. The application of the proposed methodology may be limited by the availability of historical wind speed records and CU estimates for different combinations of sprinkler models, sprinkler spacings and wind speed.     

Inverse Modeling to Quantify Irrigation System Characteristics and Operational Management

Remotely sensed (RS) data is a major source to obtain spatialdata required for hydrological models. The challenge for thefuture is to obtain besides the more direct observable data(landcover, leaf area index, digital elevation model andevapotranspiration), non-visible data such as soilcharacteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inversemodeling to obtain these non-RS-visible data. For a commandarea in Haryana, India, we applied for the 2000–2001 rabiseason a RS-GIS-combined inverse modeling approach to derivenon-RS-visible data required in the regional application ofhydrological models. A Genetic Algorithm loaded stochasticphysically based soil-water-atmosphere-plant model (SWAP) wasdeveloped for the inverse problem and used in the study. Theresults showed good agreement with the inventoried data suchas soil hydraulic properties, sowing dates, groundwaterdepths, irrigation practices and water quality. The deriveddata could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluateoperational management strategies.     

永寿县沙棘人工林生长规律初探

本文对永寿县沙棘良种选育基地试验区人工沙棘林单株树高、 30 cm处直径进行了系统的研究 ,结果表明 :1.沙棘 30 cm处直径和树高的速生期一般都出现在第 2～ 5年 ,连年生长量高峰期出现在 3～ 4年之间 ,平均生长量的最大值出现在第 4～ 5年之间。 2 .分别对沙棘树高、 30 cm处直径与树龄进行回归分析 ,得出了沙棘树高、30 cm处直径的生长模型和树冠的生长模型 :D0 .3 0 =10 ( 0 .8774- 1.92 0 1/A) 、H =- 0 .2 784 + 0 .6 2 89A- 0 .0 30 9A2、Cw=1.6 43× 10 0 .2 2 9- 0 .5 3 89/A。     

计算机辅助设计线图数据处理的灰色模型与方法

在分析计算机辅助设计线图数据处理的现状后，提出了其线图数据处理的灰色模型参数估计的函数变换法。实例表明，该方法简单实用，值得在计算机辅助设计中推广使用。     

基于径流分类的日径流量预测神经网络模型

利用聚类分析法将径流序列分解为若干个子径流序列 ,对这些子径流序列分别建立局部神经网络模型 ,而后把这些局部模型合并成一个混合模型。当新的信息进入该模型时 ,首先用分类器判别其类别 ,以确定用混合模型中的何种局部模型加以模拟。通过与不加分类的总体神经网络模型的模拟结果加以对比 ,结果表明这种基于径流分类的降雨 -径流模型表现出了更优良的性能 ,可以较大地提高径流模拟精度。     

泡桐属(Paulownia)分类管见

自泡桐属(Paulownia)在1835年建立以来,至1938年,中外研究者先后发表的新种达18种、3变种,嗣后又相继发表了若干新种,经胡秀英和《中国植物志》分别归为六种和七种一变种。到目前为止,又相继发表了不少新种和变种,泡桐属共有26种7变种(包括异名)。本文根据历史文献和近年来调查研究所获得的标本、资料,对泡桐属分类中存在的异名处理和种与变种废、留欠妥以及泡桐属的归科问题,提出了自己的意见。     

蝇蛆养殖技术的研究：Ⅰ.影响成蝇卵量的因子作用模型

蝇蛆含有丰富的营养物质,是一种很有前途的动物蛋白源。本文采用正交旋转组合设计方法建立了影响种蝇卵量的多目标因子作用模型,并进行了主因子效应和交互效应分析。结果表明:种蝇饲养室温度是影响种群产卵历期的主因子;饲养室温度和饲养密度是影响前20天总卵量的主因子;饲养密度和光照时数对种群卵量的交互效应显著;饲养室温度和光照时数对种群产卵历期的交互效应显著。