戴瑞奶绵羊产奶性状的全基因组关联分析

旨在通过对奶绵羊产奶性状的全基因组关联分析（GWAS）,寻找和定位与奶绵羊产奶性状相关的遗传标记和功能基因。本研究以135只戴瑞奶绵羊为试验材料,基于全基因组重测序技术,通过SAMTOOLS进行单核苷酸多态性（SNP）检测,使用PLINK v1.90进行质控,利用GEMMA v 0.98.1的混合线性模型对质控结果进行奶绵羊产奶性状相关的全基因组关联分析。结果表明,有1个SNP与泌乳后90天日均产奶量在全基因组范围内显著相关,8个SNPs达到潜在显著关联,相关的候选基因包括TRNAQ-CUG-2、LOC114117240、ACADL、MYL1、CHD6、SLCO3A1;有2个SNPs与150天日均产奶量达潜在显著关联,相关的候选基因包括PRMT6、RNF180;有2个SNPs与泌乳周期达潜在显著关联,相关的候选基因包括PRMT6、TRNAW-CCA-68、TRNAS-GGA-61。进一步基因功能分析推测,ACADL、SLCO3A1可能是影响奶绵羊产奶性状的候选基因。本研究为奶绵羊产奶性状的分子机制解析提供了一定的基础,为我国奶绵羊新品种培育提供了一定的理论参考。     

Simulation of transpiration, drainage, N uptake, nitrate leaching, and N uptake concentration in tomato grown in open substrate

Free-drainage or “open” substrate system used for vegetable production in greenhouses is associated with appreciable NO₃⁻ leaching losses and drainage volumes. Simulation models of crop N uptake, N leaching, water use and drainage of crops in these systems will be useful for crop and water resource management, and environmental assessment. This work (i) modified the TOMGRO model to simulate N uptake for tomato grown in greenhouses in SE Spain, (ii) modified the PrHo model to simulate transpiration of tomato grown in substrate and (iii) developed an aggregated model combining TOMGRO and PrHo to calculate N uptake concentrations and drainage NO₃⁻ concentration. The component models simulate NO₃⁻-N leached by subtracting simulated N uptake from measured applied N, and drainage by subtracting simulated transpiration from measured irrigation. Three tomato crops grown sequentially in free-draining rock wool in a plastic greenhouse were used for calibration and validation. Measured daily transpiration was determined by the water balance method from daily measurements of irrigation and drainage. Measured N uptake was determined by N balance, using data of volumes and of concentrations of NO₃⁻ and NH₄⁺ in applied nutrient solution and drainage. Accuracy of the two modified component models and aggregated model was assessed by comparing simulated to measured values using linear regression analysis, comparison of slope and intercept values of regression equations, and root mean squared error (RMSE) values. For the three crops, the modified TOMGRO provided accurate simulations of cumulative crop N uptake, (RMSE = 6.4, 1.9 and 2.6% of total N uptake) and NO₃⁻-N leached (RMSE = 11.0, 10.3, and 6.1% of total NO₃⁻-N leached). The modified PrHo provided accurate simulation of cumulative transpiration (RMSE = 4.3, 1.7 and 2.4% of total transpiration) and cumulative drainage (RMSE = 13.8, 6.9, 7.4% of total drainage). For the four cumulative parameters, slopes and intercepts of the linear regressions were mostly not statistically significant (P < 0.05) from one and zero, respectively, and coefficient of determination (r²) values were 0.96-0.98. Simulated values of total drainage volumes for the three crops were +21, +1 and −13% of measured total drainage volumes. The aggregated TOMGRO-PrHo model generally provided accurate simulation of crop N uptake concentration after 30-40 days of transplanting, with an average RMSE of approximately 2 mmol L⁻¹. Simulated values of average NO₃⁻ concentration in drainage, obtained with the aggregated model, were −7, +18 and +31% of measured values.     

Inhibition study of red rice polyphenols on pancreatic α-amylase activity by kinetic analysis and molecular docking

This study sought to investigate the possible inhibition mechanism of red rice polyphenols (RRP) on pancreatic α-amylase (PA) activity. RRP showed strong inhibition against PA activity and the half-inhibitory concentration (IC₅₀) value was 3.61 μg/mL. The fluorescence quenching of PA by RRP was a combination of static quenching and dynamic quenching. RRP could aggregate with PA and the physiochemical properties of the aggregates were closely related to the concentration of RRP. Kinetic analysis suggested that the inhibition mode of RRP on PA was reversible inhibition, which was a mixing of competitive inhibition and noncompetitive inhibition. Molecular docking speculated that RRP could form hydrogen bonds with PA by binding to the catalytic active sites (ASP197, GLU233 and ASP300) and the microenvironments of TRP58 and TRP59 were altered, thus inhibiting PA activity.     

云南引进帝国百脉根的研究

对引进帝国百脉根进行茎叶比、干鲜比、干草产量、营养成分和体外干物质消化率(IVDMD)的测定。结果表明，帝国百脉根含有丰富的营养，分枝期和盛花期粗蛋白含量分别高达28．0%和20．79%，粗纤维含量为13．0%和17．46%，Ca、P 丰富，比例恰当，体外干物质消化率较高而稳定，在分枝期和开花期分别为58．64%和57．25%。因此，帝国百脉根为饲用价值较高的优良豆科牧草，应予以进一步开发利用。     

放牧率和放牧时期对绵羊排粪量、采食量和干物质消化率关系的影响

实验研究表明，绵羊在同一放牧时期，随着放牧率的增大，鲜粪量有所减少，粪中干物质含量有所增大，但只有处理1．33羊／hm2·138天与6．67羊／hm2·138天问存在显著性差异。在同一放牧率条件下，不同放牧时期相比，以8月份粪中干物质含量最低；在各种处理之间，放牧绵羊全天干粪量均无显著性的差异。在同一放牧时期，随着放牧率的增大日采食量显著减少，而同一放牧率不同放牧时期的日采食量保持相对稳定。粪便的干重与干物质采食量的关系很小，与干物质消化率呈负相关。放牧绵羊白天排粪量为晚上的2倍，但粪中干物质含量几乎没有差异，同时，不同放牧率和不同放牧时期对粪便的颜色和形状等均有较明显的影响。     

不同刈割处理对稻草轮作黑麦草干物质产量和体外消化量的影响

[目的]探讨不同刈割处理对稻草轮作黑麦草干物质产量和体外消化量的影响。[方法]以黑麦草为材料,采用二因素四水平研究稻草轮作模式下不同刈割处理对黑麦草干物质产量和体外消化量的影响。[结果]在4个水平留茬高度下,40cm高度刈割黑麦草千物质产量最高,达5357．50kg／hm^2;在40cm高度刈割下,留萑高度为6cm的刈割处理黑麦草的千物质产量最大,达1562．50kg／hm^2;40cm高度下刈割并留茬6cm处理下的黑麦草干物质体外消化量最大,为1064．68kg/hm^2。[结论]在黑麦草高度为30～40cm且留茬高度为6cm左右时刈割,能取得最高的干物质产量和体外干物质消化量。     

DM642采集彩色线阵CCD图像EDMA帧的设计

基于专用视频/图像处理芯片DM642和彩色线阵CCD TCD2252D设计了一套实时图像采集处理系统。重点研究了在实时图像采集处理系统中,使用EDMA来实时传输图像时,视频缓冲区FIFO阈值与EDMA帧尺寸的设计。     

不同收获期玉米青贮DM和CP奶牛瘤胃降解率研究

结果表明：蜡熟期玉米青贮DM的有效降解率（60.07%）分别比乳熟期（52.91%）和乳熟前期（45.13%）高7.16个百分点（P＜0.05）和14.94个百分点（P＜0.01）;乳熟期玉米青贮DM的有效降解率比乳熟前期高7.78个百分点（P＜0.05）.蜡熟期玉米青贮CP的有效降解率（81.93%）分别比乳熟期（76.43%）和乳熟前期（73.36%）高5.50个百分点（P＜0.05）和8.57个百分点（P＜0.05）;乳熟期玉米青贮CP的有效降解率比乳熟前期高3.07个百分点，但差异不显著.     

不同复种方式下作物的粗蛋白和可消化干物质总产量比较

在南京对6种不同复种方式下作物的营养物质产量进行了比较研究,结果表明:多花黑麦草Lolium multiflorum粗蛋白总产量和可消化干物质总产量分别是小麦Triticum eastivum的1.45倍和1.26倍;杂交狼尾草Pennisetum americanum×P.purpureum粗蛋白总产量和可消化干物质总产量平均值分别是水稻Oryza sativa的2.06倍和1.61倍;6种复种方式中,粗蛋白总产量和可消化干物质总产量以多花黑麦草-杂交狼尾草为最高,黑麦Secale cereal-杂交狼尾草其次.集约农区发展草食性畜禽养殖业以二季均种植牧草效率较高.     

甘蓝杂种致死材料的鉴定与遗传分析

杂种致死是一种生殖隔离类型,致死材料的鉴定及遗传分析不仅有助于了解杂种致死的遗传机制,还可以为致死基因的定位和克隆奠定基础。利用已知携带杂种致死基因的甘蓝自交系09-211、09-222、10-260和其他自交系配制的杂交组合为试材,鉴定携带致死基因的新材料,并对甘蓝杂种致死性状进行了遗传分析。结果表明:11-204和11-176是2个新的甘蓝致死材料;11-176与09-222及10-260具有遗传等效性,而11-204与09-211具有遗传等效性;甘蓝杂种致死性状是由2个显性基因互补控制的,其中1个致死基因来自09-211或11-204,另1个致死基因来自09-222或10-260或11-176,其遗传模式符合Dobzhansky-Muller(DM)模式。