Soil organic matter fractionation as a tool for predicting nitrogen mineralization in silty arable soils

After decades of searching for a practical method to estimate the N mineralization capacity of soil, there is still no consistent methodology. Indeed it is important to have practical methods to estimate soil nitrogen release for plant uptake and that should be appropriate, less time consuming, and cost effective for farmers. We fractionated soil organic matter (SOM) to assess different fractions of SOM as predictors for net N mineralization measured from repacked (disturbed) and intact (undisturbed) soil cores in 14 weeks of laboratory incubations. A soil set consisting of surface soil from 18 cereal and root‐cropped arable fields was physically fractionated into coarse and fine free particulate OM (coarse fPOM and fine fPOM), intra‐microaggregate particulate OM (iPOM) and silt and clay sized OM. The silt and clay sized OM was further chemically fractionated by oxidation with 6% NaOCl to isolate an oxidation‐resistant OM fraction, followed by extraction of mineral bound OM with 10% HF (HF‐res OM). Stepwise multiple linear regression yielded a significant relationship between the annual N mineralization (kg N/ha) from undisturbed soil and coarse fPOM N (kg N/ha), silt and clay N (kg N/ha) and its C:N ratio (R² = 0.80; P < 0.01). The relative annual N mineralization (% of soil N) from disturbed soils was related to coarse fPOM N, HF‐res OC (% of soil organic carbon) and its C:N ratio (R² = 0.83; P < 0.01). Physical fractions of SOM were thus found to be the most useful predictors for estimating the annual N mineralization rate of undisturbed soils. However, the bioavailability of physical fractions was changed due to the disturbance of soil. For disturbed soils, a presumed stable chemical SOM fraction was found to be a relevant predictor indicating that this fraction still contains bio‐available N. The latter prompted a revision in our reasoning behind selective oxidation and extraction as tools for characterizing soil organic N quality with respect to N availability. Nonetheless, the present study also underscores the potential of a combined physical and chemical fractionation procedure for isolating and quantifying N fractions which preferentially contribute to bulk soil N mineralization. The N content or C:N ratio of such fractions may be used to predict N mineralization in arable soils.     

离心泵非定常流动计算及性能预测

采用以SSTk-ω模型封闭的雷诺平均方程和滑移网格技术计算了离心泵内的非定常流场.基于非定常流动计算结果,考虑容积损失、圆盘摩擦损失和机械损失,对离心泵的性能进行了预测,并与实测性能曲线进行了比较.结果表明,在给定进口速度的条件下,由于叶轮与蜗壳隔舌的相对位置不同,泵的扬程和轴功率有比较大的脉动,且其脉动幅值随流量的增大而增大.定常流动计算和非定常流动计算所预测的性能曲线在大流量与设计工况时相差不大,在小流量时有明显的差别.与试验曲线相比,预测的扬程曲线偏低,轴功率曲线也偏低,效率曲线比较接近.由于在设计工况时定常计算和非定常计算差别不明显,在设计过程中采用定常计算是可行的.     

Soil Properties Degradation Assessment Using Infrared Scanning Technique of Soils （Case Study： Eastern of Congo）

Recently, near infrared reflectance （NIR） and mid-infrared （MIR） spectroscopy techniques are increasingly introduced as convenient and simple non-destructive techniques for quantifying several soil properties. This study uses MIR method to predict pH, soil organic C, total N, AI, Ca, Mg and K, CEC and soil texture for soil samples collected in Sud-Kivu, Congo. A total of 536 composite soil samples were taken from two locations （Burhale and Luhihi） at two depths （0-20 cm and 20-40 cm） using a spatially-stratified random sampling design within an area of 200 km2. Differences in characteristics were evaluated between the two locations, land use （cultivated vs. non-cultivated land） with soil depths. A random subset of the samples （10%） were analyzed using standard wet chemistry methods, and calibration models developed by MIR data to estimate soil properties for the full soil sample set. Partial least squares regression （PLS） method gave acceptable coefficients of determination between 0.71 and 0.93 for all parameters. Soil organic matter levels were higher in cultivated plots in Luhihi （3.9% C） than in Burhale （3.0% C）, suggesting lower levels of soil fertility in the later area. This indicates high levels of acidity, which are likely to limit crop production in the area. Phosphorus deficiency is acute in Burhale （2.4 mg P/kg） but less in Luhihi （5.4 mg P/kg）. In both locations, low levels of Ca and Mg indicate that soils may be susceptible to deficiencies in both elements.These findings provide new opportunities for monitoring soil quality in the region which can benefit multiple actors and scientists involved in the agricultural and environmental sectors.     

Prediction of daily reference evapotranspiration by a multiple regression method based on weather forecast data

Prediction of daily reference evapotranspiration (ET ₀) is the basis of real-time irrigation scheduling. A multiple regression method for ET ₀ prediction based on its seasonal variation pattern and public weather forecast data was presented for application in East China. The forecasted maximum temperature (T _max), minimum temperature (T _min) and weather condition index (WCI) were adopted to calculate the correction coefficient by multilinear regression under five time-division regimes (10 days, monthly, seasonal, semi-annual and annual). The multiple regression method was tested for its feasibility for ET ₀ prediction using forecasted weather data as the input, and the monthly regime was selected as the most suitable. Average absolute error (AAE) and root mean square error (RMSE) were 0.395 and 0.522 mm d^?1, respectively. ET ₀ prediction errors increased linearly with the increase in temperature prediction error. A temperature error within 3 K is likely to result in acceptable ET ₀ predictions, with AAE and average absolute relative error (AARE) <0.142 mm d^?1 and 5.8%, respectively. However, one rank error in WCI results in a much larger error in ET ₀ prediction due to the high sensitivity of the correction coefficient to WCI and the large relative error in WCI caused by one rank deviation. Improving the accuracy of weather forecasts, especially for WCI prediction, is helpful in obtaining better estimations of ET ₀ based on public weather data.     

环青海湖地区草地蝗虫发生测报的气候指标研究

采用次序统计量方法,以1988～1999年环青海湖地区草地蝗虫发生程度资料和气候资料研究了蝗虫灾害等级与当地气候指标的定量关系,建立了春季和夏季预测模型,并以此对2000～2003年该地区蝗虫发生状况进行了预测试验。结果表明,敏感气候因子有:上年11～12月气温、3～6月温度及5～6月降水量等。春季预测模型中的指标为:(1)T11<-6℃;(2)T12<-10℃;(3)T3>-4℃;(4)T4>2℃。夏季预测模型中的指标为:(1)(T11+T12)/2<-8.5℃;(2)(T3+T4)/2>-1.5℃;(3)(T5+T6)>7.5℃;(4)(R5+R6)<48mm。当模型中有3个或4个指标满足,则当年可能发生严重蝗虫灾害,当没有或只有1～2个指标满足,则不会发生严重蝗虫灾害。     

华北棉田二代棉铃虫发生程度中期预测

在华北棉区用扫网法和目测查虫法调查麦田一代棉铃虫幼虫发生量，用比较法和生命表分析法预测二代棉铃虫在棉田的发生程度和虫口密度。经1991—1994年应用检验，预测结果均与实际发生情况吻合。     

反刍动物采食量的概念与研究方法

本研究对反刍家畜采食量的研究发展与现状进行了回顾与总结,采食量及其相关术语的定义主要基于饲草料或家畜,其测定方法和精确含义有差异;反刍家畜采食是由生物和非生物因素相互作用共同影响的复杂动态过程,采食量影响因子主要分为家畜的(胃肠蠕动力、选择性采食等)、饲草料的(粗纤维含量、抗营养成分等)和饲养条件的(草层结构、草地饮水点分布等)因素3个方面;采食量的测定方法有基于牧草测定的直接法和基于家畜测定的间接法,后者较多地应用于放牧家畜;预测方法有基于数学函数和生物学原理的模型法,基于消化试验的经验法和结合家畜属性的改进经验法。舍饲条件下可准确地测定和预测家畜的采食量,但对放牧家畜还没有精确的方法。通过测定与饲草水平密切相关的家畜尿液、血液或粪便中的代谢物水平将成为预测放牧家畜采食量的准确方法。     

基于灰色理论的畜禽粪便环境污染风险预测分析

本文运用灰色建模理论中的灰色数列预测方法,利用北京密云县10个乡镇的畜禽粪便实际负荷量和最大负荷量的确定,对未来年份的畜禽粪便负荷预警值进行预测。结果表明:该流域各乡镇未来十年所受畜禽粪便的污染威胁均呈现逐年加剧趋势,其中石城和番字牌预警值上升最快;冯家峪、大城子和新城子次之,高岭、太师屯和不老屯呈现缓慢上升态势。     

Surgical repair of a peritoneopericardial diaphragmatic hernia in a pregnant dog

Objective: To describe the surgical repair and pre‐ and postoperative management of a peritoneopericardial diaphragmatic hernia (PPDH) in a pregnant dog. Case summary: A pregnant dog was presented for vomiting, lethargy, and pale mucous membranes. Pulsus paradoxus was noted on physical examination. The dog was diagnosed with a PPDH via thoracic radiographs, abdominal ultrasound, and an echocardiogram. The hernia was surgically repaired and the dog received supportive medical care until the puppies were old enough to be delivered via cesarean section. The mother and all puppies survived. New or unique information provided: This is the first report that describes the surgical repair and postoperative management of a PPDH in a pregnant dog.