Performance of DSSAT-Nwheat across a wide range of current and future growing conditions

Crop models are widely used in agricultural impact studies. However, many studies have reported large uncertainties from single-model-based simulation analyses, suggesting the need for multi-model simulation capabilities. In this study, the APSIM-Nwheat model was integrated into the Decision Support System for Agro-technology (DSSAT), which already includes two wheat models, to create multi-model simulation capabilities for wheat cropping systems analysis. The new model in DSSAT (DSSAT-Nwheat) was evaluated using more than 1000 observations from field experiments of 65 treatments, which included a wide range of nitrogen fertilizer applications, water supply (irrigation and rainout shelter), planting dates, elevated atmospheric CO₂ concentrations, temperature variations, cultivars, and soil types in diverse climatic regions that represented the main wheat growing areas of the world.DSSAT-Nwheat reproduced the observed grain yields well with an overall root mean square deviation (RMSD) of 0.89 t/ha (13%). Nitrogen applications, water supply, and planting dates had large effects on observed biomass and grain yields, and the model reproduced these crop responses well. Crop total biomass and nitrogen uptake were reproduced well despite relatively poor simulations of observed leaf area measurements during the growing season. The low sensitivity of biomass simulations to poor simulations of leaf area index (LAI) were due to little changes in intercepted solar radiation at LAI >3 and water and nitrogen stress often limiting photosynthesis and growth rather than light interception at low LAI.The responses of DSSAT-Nwheat to temperature variations and elevated atmospheric CO₂ concentrations were close to observed responses. When compared with the two other DSSAT-wheat models (CERES and CROPSIM), these responses were similar, except for the responses to hot environments, due to different approaches in modeling heat stress effects.The comprehensive evaluation of the DSSAT-Nwheat model with field measurements, including a comparison with two other DSSAT-wheat models, created a multi-model simulation platform that allows the quantification of model uncertainties in wheat impact assessments.     

Analysis on Function Orientation and Development Countermeasures of New Agricultural Business Entities

Along with the rapid advance of industrialization and urbanization process, fostering new agricultural business entities become inevitable for agricultural transformation and the construction of agricultural modernization in China. The status of the new agricultural business entities determines the level of modern agricultural development. In recent years, new agricultural business entities have grew rapidly. However, there are still many problems including the difficulties in financing loans, inadequate agricultural insurance system, bad implementation of agricultural subsidies, jagged agricultural talents and so on. In order to foster new agricultural business entities, countermeasures should be carried out to ensure financial support, perfect the agricultural insurance, strengthen the level of agricultural subsidies, strive to develop the degree of specialization agricultural operators and so on.     

河西荒漠灌区紫花苜蓿施肥效应及其基于数据包络分析法的经济效益研究

为科学准确地评判河西走廊苜蓿主产区紫花苜蓿饲草生产中施肥措施对其产品质量及生产收益的影响,本研究以“甘农3号”紫花苜蓿为材料,通过2016、2017年2年田间试验,以该区域紫花苜蓿饲草生产的平衡施肥推荐方案(N 103.5 kg·hm^-2、P₂O₅ 105 kg·hm^-2、K₂O 90 kg·hm^-2)为对照,探讨了不施肥及3种不完全施肥(缺氮偏施、缺磷偏施、缺钾偏施)处理下紫花苜蓿的生产性能,并采用数据包络分析法(DEA)对其经济效益进行分析。结果表明:与不施肥相比,施肥措施各处理均显著提高紫花苜蓿产量、蛋白总量,降低其酸性洗涤纤维和中性洗涤纤维,提高了相对饲用价值,从而改善了紫花苜蓿品质,并有效增加了经济效益;与氮、磷、钾平衡施肥相比,各偏肥处理的紫花苜蓿产量和品质均显著低于平衡施肥,尤以缺磷偏施的降幅最大,2016、2017年2年的产量和蛋白总量降幅分别达到25.9%、25.7%和33.4%、33.1%。因此,磷是河西荒漠灌区紫花苜蓿饲草生产的养分限制因子,氮、磷、钾对该地区紫花苜蓿生产性能影响顺序为:磷>氮>钾。运用数据包络分析法(DEA)分析出河西荒漠灌区紫花苜蓿的施肥效应为氮、磷、钾平衡施肥的经济效益最优,为DEA有效;不完全施肥的3个评价单元及不施肥评价单元为DEA无效,其中,不施肥经济效益最低,3个不完全施肥评价单元中的缺磷偏肥的紫花苜蓿经济效益比缺氮偏肥和缺钾偏肥更低;另外还以DEA模型推算出不同施肥措施下紫花苜蓿饲草生产经济效益改进的具体方案,其中,不施肥的紫花苜蓿饲草生产需调整的幅度最大,调整额度达10678.88 CNY·hm^-2,各施肥措施需调整的幅度排序为:不施肥>缺磷偏施>缺氮偏施>缺钾偏施。     

山羊可溶型干细胞因子mRNA在不同毛色皮肤组织中的表达水平简

为探讨可溶性干细胞因子（stem cell factor, SCF）基因表达水平与山羊毛色间的相关性，本试验利用实时荧光定量PCR（QRT-PCR）技术研究了SCF基因mRNA在黑色和白色山羊皮肤中的表达量，并对结果进行统计分析。经内参基因校正后，黑色山羊皮肤中可溶型SCF的相对表达量是白色山羊相对表达量的0.27倍（P>0.05）。可溶型SCF mRNA表达量可能与山羊毛色表型不存在相关性。     

肌细胞增强因子2B基因在人和动物中的研究进展

肌细胞增强因子2B(MEF2B)基因属于肌细胞增强因子2(MEF2)基因家族成员,广泛表达于人和动物的肌肉和神经组织中,在肌肉生成、神经系统发育和分化、肝脏纤维化等方面具有重要的作用,作者从MEF2B基因的结构、组织分布、生物学功能及研究进展等方面对该基因进行了综述.     

基于GIS的村级尺度统计数据空间化方法与时序分析初探

选择重庆市巴南区石龙镇大连村、大兴村、白马村、金星村、合路村、柏树村、大桥村、大园村和中伦村9个行政村作为研究区,将研究区的遥感影像、数字高程模型、行政界线等数据的空间参考坐标系统一为1980西安坐标系,选择2006-2012年研究区的农用肥施用量数据作为村级尺度统计数据空间化方法研究的研究数据,利用专家打分法对不同土地利用类型与农用肥施用之间的相关性进行打分,分值范围是0~1分。结合村级行政界线、行政村面积、农用肥施用量、土地利用数据和专家打分结果,构建农用肥施用数据空间化模型,分别生成2006-2012年村级农用肥施用数据空间化分布栅格数据,栅格尺度选择1、10、100和200 m这4种,并对栅格化结果进行对比分析。同时,对2006-2012年的农用肥施用空间分布数据进行时序分析,获取农用肥施用量的动态变化趋势。通过研究得到以下结论:1村级农用肥施用量数据空间化尺度与土地利用数据的类型及空间分辨率有关;2研究区各行政村农用肥施用量在2006-2012年期间总体变化趋于平稳。本研究对于实现村级统计数据空间化方法具有一定的参考意义,而空间化后的村级统计数据对于进行村镇区域规划、土地整改、生态环境保护等具有重要指导意义。     

黄河三角洲台田间渗水池塘的水质变动规律分析

以黄河三角洲地区台田间渗水池塘为研究对象,分析了渗水池塘的水质因子变动规律。结果表明:不同池塘间水质因子差异较大,但均表现出水体盐度较高、氮磷等营养物质含量较低、K+离子含量相对较低、Ca2+离子和Na+离子含量相对较高及K+/Na+显著低于正常海水等特点。结果说明,黄河三角洲地区台田间渗水池塘的水质条件不适合直接进行水产养殖,应对水质调整后才可做养殖之用。     

香蕉TGA转录因子家族的鉴定及枯萎病菌胁迫下的表达分析

尖孢镰刀菌（Fusarium oxysporum f. sp. Cubense, Foc）引起的香蕉枯萎病是我国香蕉的主要病害之一,严重影响香蕉的产量和品质。TGA防御反应基因在香蕉应对尖孢镰刀菌胁迫的应答转录调控过程中至关重要。本研究以拟南芥TGA转录因子家族成员蛋白为查询序列,在香蕉基因组数据库中Blast筛选出TGA转录因子家族成员,并对该家族成员进行生物信息学分析。共鉴定得到9个香蕉TGA家族成员,分别命名为MaTGA1~MaTGA9;香蕉TGA家族蛋白富含酸性氨基酸,大部分蛋白以α螺旋为主;亚细胞定位主要在细胞核内。进化树分析表明,香蕉MaTGA转录因子家族的9个成员可分为Class Ⅰ和Class Ⅱ两类,基因结构及功能结构域的分布情况也呈现出高度一致。进一步通过RT-qPCR分析发现,MaTGA2、MaTGA3和MaTGA8在香蕉枯萎病菌侵染后的‘威廉斯’（易感病）及‘南天黄’（抗病）中均显著下调表达,MaTGA1、MaTGA6、MaTGA7和MaTGA9均呈现先下降后上升的趋势;然而MaTGA4和MaTGA5仅在‘威廉斯’中上调表达,以上结果表明MaTGA2、MaTGA3和MaTGA8在香蕉抗枯萎病中发挥重要的生物学功能。本研究结果为香蕉TGA转录因子功能挖掘奠定理论基础。     

改性木屑处理含铬废水的研究

采用磷酸改性木屑后用于含铬废水吸附处理,探讨废水pH值、处理时间、木屑投加量、处理温度4个因素对铬去除率的影响;并拟合25℃改性木屑吸附处理含铬废水的动力学、等温线方程,估算热力学数据。结果表明:木屑对含铬废水有较强去除力,改性木屑去除力加强;改性木屑处理20ml浓度为50mg/L含铬废水的适宜条件为pH值=1～4,处理时间90min,木屑投加量1g,处理温度20～30℃;改性木屑吸附处理含铬废水的动力学特性符合颗粒内扩散方程和二级吸附速率方程;吸附等温线方程符合Langmuir吸附;25℃吸附过程ΔH=-20.489kJ/mol,ΔS=-78.426J/(mol.K),ΔG=2.89kJ/mol。