Fine earth soil bulk density at 0.2 m depth from Land Use and Coverage Area Frame Survey (LUCAS) soil 2018

Soil Bulk Density (BD) is an extremely important variable because it is an important site characterization parameter, and it is highly relevant for policy development because it is mandatory for calculating soil nutrient stocks. BD can influence soil chemical properties, land-use planning and agronomic management. The 2018 Land Use and Coverage Area Frame Survey (LUCAS) saw the unprecedented collection of BD core analysis in a subset of the locations in Europe and the United Kingdom where soil physical and chemical properties were analysed in the 2009 and the 2015 sampling campaigns. Here, we integrated the LUCAS 2018 BD sampling campaign with the mass fraction of coarse fragments previously determined in LUCAS 2009–2015 in order to provide a dataset of the volume fraction of coarse fragments and the BD of the fine earth and improve soil organic carbon (SOC) stock estimation accuracy for topsoil. BD data sampled at 0–10 and 10–20 cm were averaged to harmonize the BD with the mass fraction of coarse fragments measured in 2009, 2012 and 2015. Samples were from cropland, grassland and woodland soils, which accounted for 41%, 21% and 30%, respectively, of the total number of selected sites (n = 6059); ‘bareland’, and ‘shrubland’ accounted for 3% of the sites each, whereas ‘artificial land’ accounted for <1%. Only six samples were classified as ‘wetland’. The dataset was produced assuming the mass density of the coarse fraction to be constant across all LUCAS soil samples. We also estimated the SOC stocks associated with LUCAS 2018 BD and SOC content measurements and showed that correcting the BD by the coarse mass fraction instead of the coarse volume fraction generates SOC stock underestimation. We found the highest deviations in woodlands and shrublands. We showed that, when SOC stock is computed with coarse mass fraction, the error compared with the computation by volume may vary depending on the SOC and coarse mass fraction. This may imply a SOC stock underestimation for European soils. This dataset fits into the big framework of LUCAS soil properties monitoring and contributes both to soil awareness and soil research and assessments, which are two important objectives of the Soil Strategy and the European Soil Observatory (EUSO).     

Measurement of tidal volume using Respiratory Ultrasonic Plethysmography in anaesthetized,mechanically ventilated horses

ObjectiveTo compare tidal volume estimations obtained from Respiratory Ultrasonic Plethysmography (RUP) with simultaneous spirometric measurements in anaesthetized, mechanically ventilated horses.Study designProspective randomized experimental study.AnimalsFive experimental horses.MethodsFive horses were anaesthetized twice (1 week apart) in random order in lateral and in dorsal recumbency. Nine ventilation modes (treatments) were scheduled in random order (each lasting 4 minutes) applying combinations of different tidal volumes (8, 10, 12 mL kg^?1) and positive end-expiratory pressures (PEEP) (0, 10, 20 cm H₂O). Baseline ventilation mode (tidal volume = 15 mL kg^?1, PEEP = 0 cm H₂O) was applied for 4 minutes between all treatments. Spirometry and RUP data were downloaded to personal computers. Linear regression analyses (RUP versus spirometric tidal volume) were performed using different subsets of data. Additonally RUP was calibrated against spirometry using a regression equation for all RUP signal values (thoracic, abdominal and combined) with all data collectively and also by an individually determined best regression equation (highest R²) for each experiment (horse versus recumbency) separately. Agreement between methods was assessed with Bland-Altman analyses.ResultsThe highest correlation of RUP and spirometric tidal volume (R² = 0.81) was found with the combined RUP signal in horses in lateral recumbency and ventilated without PEEP. The bias ± 2 SD was 0 ± 2.66 L when RUP was calibrated for collective data, but decreased to 0 ± 0.87 L when RUP was calibrated with individual data.Conclusions and clinical relevanceA possible use of RUP for tidal volume measurement during IPPV needs individual calibration to obtain limits of agreement within ± 20%.     

饲粮n-6/n-3多不饱和脂肪酸比例对畜禽健康和产品品质的影响

现今人类膳食中n-6多不饱和脂肪酸(PUFA)大多都是过量的,但n-3 PUFA却严重不足.研究表明,n-6/n-3 PUFA比例平衡对畜禽健康和产品品质有着重要意义,n-6/n-3 PUFA比例平衡成为当下最受关注的问题.本文综述了n-6/n-3 PUFA比例平衡的营养生理作用以及对畜禽产品品质的影响及如何改善畜禽产品中的n-6/n-3 PUFA比例.     

Concurrent 2009 Pandemic Influenza A (H1N1) Virus Infection in Ferrets and in a Community in Pennsylvania

We report a fall 2010 cluster of pandemic influenza A/H1N1 (pH1N1) infections in pet ferrets in Lehigh Valley region of Pennsylvania. The ferrets were associated with one pet shop. The influenza cluster occurred during a period when the existing human surveillance systems had identified little to no pH1N1 in humans in the Lehigh Valley, and there were no routine influenza surveillance systems for exotic pets. The index case was a 2.5‐month‐old neutered male ferret that was presented to a veterinary clinic with severe influenza‐like illness (ILI). In response to laboratory notification of a positive influenza test result, and upon request from the Pennsylvania Department of Health (PADOH), the Pennsylvania Department of Agriculture (PDA) conducted an investigation to identify other ill ferrets and to identify the source and extent of infection. PDA notified the PADOH of the pH1N1 infection in the ferrets, leading to enhanced human surveillance and the detection of pH1N1 human infections in the surrounding community. Five additional ferrets with ILI linked to the pet shop were identified. This simultaneous outbreak of ferret and human pH1N1 demonstrates the important link between animal health and public health and highlights the potential use of veterinary clinics for sentinel surveillance of diseases shared between animals and humans.     

典型旱年农业干旱遥感监测指标在东北地区生长季的表现

以8d为时间尺度,以土壤相对湿度（RSM）为参考指标,采用相关分析方法,分析评估典型旱年2009年作物生长季内分别表征降水、土壤和作物的3个类别10种农业干旱遥感监测指数在东北地区的适用性。结果表明：（1）生长季中、后期,综合考虑冠层温度和植被特征的温度植被干旱指数（TVDI）与RSM的相关系数绝对值在0.5左右,对土壤湿度变化较敏感,可用于该生长阶段的农业干旱监测;（2）考虑作物前期缺水的累积作物缺水指数（ACWSI）是与RSM相关性较好的指数之一,在生长季前期和后期与RSM的相关系数绝对值在0.47以上,表现良好,但应用过程中需注意累积效应的时间尺度;（3）表观热惯量（ATI）更适于生长季前期干旱监测,改进型能量指数（MEI）适用于各种植被覆盖条件,但存在一定不稳定性;（4）考虑前期累积降水的APCI指数比仅考虑8d降水的条件降水指数PCI更能反映土壤湿度状况,特别是在生长季中、后期,可作为其它监测指数的补充;（5）条件植被指数（VCI）、归一化差异水分指数（NDWI）与RSM相关性较低,对现时土壤湿度的反映不敏感,不适于研究区内短时间尺度的农业干旱监测。研究结果可为东北地区开展农业干旱监测选取合适指标提供参考,也可为农业干旱指数的广泛应用构建可行性框架。     

畜禽舍移动式智能监测平台研制

畜禽养殖场内温度、湿度及各种气体构成畜禽生长的外围环境,直接影响畜禽日常行为和生长速度及免疫状态。对这些畜禽养殖场内进行检测并监控畜禽健康状态及寻找二者间的联系,对优化养殖环境,发展健康养殖具有重要意义。该研究以STM32单片机为控制核心,在固定点传感器外设置移动式智能监测平台,通过无线定位系统UWB(Ultra Wide Band)和集成传感器对畜禽养殖场内环境进行监测,利用带图传功能摄像头和红外测温装置实时监控畜禽状态。传感器获取信息后将数据以UART、IIC或模拟量输出方式传递给STM32,STM32处理数据后通过物联网WIFI模块上传至阿里云IoT(The Internet of Things)物联网平台,用户登录网页页面即可对数据进行远程访问,并对畜禽状态进行实时监控。实测结果表明,智能检测平台检测数据与猪场内布置的传感器检测结果相近,二者偏差小于10%,在无遮挡情况下布置无线定位系统,定位误差接近10cm级。系统检测数据可信,数据传输正常,可持续长时间稳定运行。机动平台还开发了搬运功能,单次运送能力为200 kg左右。移动式智能监测平台为畜禽养殖场内实现全范围环境监控提供了设备基础。     

茉莉花茶产业概况与创新发展

茉莉花茶是中国具有悠久产销历史的再加工茶类。文章剖析了中国茉莉花茶产销概况,指出了茉莉花茶产业发展的瓶颈,提出了茉莉花茶加工技术创新与产品创新路径,展望了茉莉花茶产业发展前景,阐述了茉莉花茶的健康属性与消费空间。笔者认为,依托创新驱动,茉莉花茶产业将具有较大的发展潜力和市场消费空间。     

毛乌素沙地油蒿光系统II多时间尺度的环境响应特征

中国西北荒漠地区极端天气事件频发,探究荒漠植物适应环境波动的调节过程和机制,可帮助预测未来气候变化背景下荒漠生态系统群落的演替和发展。该研究选取宁夏盐池毛乌素沙地优势物种油蒿(Artemisia ordosica)为研究对象,进行叶绿素荧光的长期原位连续观测。运用小波分析方法探究油蒿光系统Ⅱ(Photosystem Ⅱ,PSⅡ)能量分配参数与光合有效辐射(Photosynthetically Active Radiation,PAR)、空气温度、饱和水汽压差(Vapor Pressure Difference,VPD)和土壤含水率(Soil Water Content,SWC)在多时间尺度上的动态格局。结果表明:日尺度下,PSII能量分配参数滞后PAR 43 min,分别滞后空气温度、VPD和SWC 3.3、4.6和10.72 h(P<0.05),油蒿可能通过叶黄素循环等热耗散机制和改变气孔导度等途径调节PSⅡ能量分配。在季节尺度下,PSII能量分配参数分别滞后于空气温度、VPD和PAR 7.2、8.8和14.7 d,滞后于SWC长达21.6 d(P<0.05),油蒿可能通过提高PSII修复能力、增加特定蛋白数量和叶绿素浓度等方式调节PSII能量分配。油蒿PSII能量分配参数和最大光化学效率的波动符合其物候期规律,最大光化学效率和实际光化学效率在7和8月降低,调节性热耗散和非调节性热耗散增高。5和9月,非调节性热耗散增高且伴随最大光化学效率低值出现。研究认为,不同时间尺度PSⅡ能量分配调控机制存在差异,油蒿通过修复损伤最大光化学效率维持在0.78附近使PSⅡ生理状态恢复正常生理水平,对水分亏缺、极端温度和高辐射有一定适应能力。该研究可为农作物生长实时监测与保护农业生态平衡提供科学参考。