小麦机械化无垄栽培技术理论与应用

随着现代农业科技不断发展，机械化技术在我国多个农业生产区得到大量应用。机械化无垄栽培的理论基础源于对小麦生物学特性的研究，技术则源于机械化设备快速、均匀种植功能，让小麦种子能在适宜的环境和土层中均匀分布。该文从理论角度分析小麦生物学特性及机械化无垄栽培增产机制，并结合河南省平顶山市某县的实际种植情况，分析小麦机械化无垄栽培技术的应用要点和效益，另外对该技术应用中存在的问题进行解答，最后对小麦机械化无垄栽培技术应用推广前景进行预测，并提出相关建议。      

1～21日龄艾维茵肉鸡净能需要量研究

本试验在实测饲粮玉米和豆粕净能(NE)值的基础上,研究1～21日龄艾维茵肉鸡净能需要量.选用1日龄的艾维茵肉公鸡250只,随机分为5组,每组5个重复,每个重复10只鸡,饲粮净能水平分别为8.97、9.25、9.54、9.83、10.11 MJ/kg,考察不同净能水平对1～21日龄艾维茵肉鸡生长性能和氮代谢的影响.结果表...     

Effects of Addition of Three Types of Biochar on the Soil Nitrogen Balance and Cotton Yield

The objective of this study was to determine the effect of biochar addition on the soil N balance and cotton yield in a drip-irrigated cotton field. The experiment included four soil amendments: control, cotton straw biochar, corn cob biochar, and poultry manure biochar. The biochar was applied at a rate of 4.5 t·hm^－2 except control. The results showed that all three types of biochar significantly reduced both the apparent soil N loss and the N surplus. The effect of cotton straw biochar treatment was most significant, relative to the control. Plant nitrogen uptake differed significantly between the different treatments, decreasing in the order cotton straw biochar > poultry manure biochar > corn cob biochar. Cotton yield also differed significantly between the different treatments, decreasing in the order poultry manure biochar > corn cob biochar, and cotton straw biochar.     

川北地形过渡带地形因子对土地利用与景观格局变化的影响

[目的]基于地形特征分析不同用地类型时空分布变化,不仅能解释土地利用时空变化规律,并能更进一步为优化土地利用结果,生态环境保护奠定基础。[方法]基于四川省北部江油市2003,2010,2018年3期遥感影像,运用土地利用转移矩阵法,分析不同用地类型之间的转化情况;接着利用地形位指数法、分布指数法,分析地形因子影响下不同用地类型分布指数变化特征;之后利用移动窗口法,探究景观格局中斑块密度与Shannon多样性指数时空变化规律;最后结合双变量空间相关性分析,分析地形因子与景观指数间的空间相关性特征。[结果](1)在2003—2010年期间,水田面积减少最多(减少面积2 238.98 hm~2),建设用地面积增加最多(面积增加3 360.36 hm~2);在2010—2018年期间,水田面积减少1 175.84 hm~2,建设用地面积增加1 614.78 hm~2;2003—2010年期间江油市土地利用的变化量整体高于2010—2018年。(2)北部山区主要由旱地转移为林草地,南部平原地区主要为水田转移为建设用地,中部丘陵区域旱地和水田相互转化强烈。(3)随时间变化,旱地和未利用地优势等级向中地形位等级靠拢;低地形位等级上建设用地、水田和水域优势度逐渐降低,并具有优势等级向较高地形位等级扩展趋势。(4)山区河流沿岸以及山地平原交汇处斑块密度与Shannon多样性指数较高,且呈线性分布;随时间变化,丘陵区域斑块密度增加,主城区附近Shannon多样性指数呈下降趋势。(5)高—高聚集区主要表现为向山地丘陵交汇处聚集;城区附近景观指数因受其他因素影响较多,导致该区域景观指数与地形位指数呈现出不显著相关性。[结论]在地形过渡带区域,不同地貌对于各类用地变化的影响在时空上存在差异性,其地形因子与景观指数的空间相关性差异明显。     

影响大容量纤维测试仪测试精度的因素分析与控制

皮棉样品的轧花方式会带来纤维样品的加工误差,样品的整理和制样水平会影响纤维品质测试结果的重复性;实验室温湿环境条件控制、样品平衡时间、马克隆值试样称见质量、仪器间台差、人为误差是纤维品质实验室测试环节容易产生误差的主要因素。经大量试验验证和跟踪对比,提出了有效提高测试精度的控制措施。     

水稻两段栽培技术在浉河区生产上的应用成效

介绍了水稻两段栽培技术的原理和方法,以及信阳市浉河区推广水稻两段栽培技术在减肥控氮、节本增效等方面取得的主要成效和主要做法。     

不同品种和地区对稻米镉含量与品质的耦合影响

为了研究不同水稻品种在不同种植地区的稻米镉含量及其与品质的关系,以分别种植在湖南长沙和广东惠州的‘齐丰占’、‘湘直粳’、‘玉香油占’等46个不同遗传背景的水稻品种(系)为研究对象,采用原子吸光光谱法测定稻米镉含量和FOSS全自动流动注射仪测定米质各性状指标。结果表明:(1)不同基因型水稻品种的镉积累存在极显著水平的品种间差异,在长沙地区种植稻米平均镉含量大约是惠州地区的两倍。(2)不同水稻品种(系)在惠州地区种植的稻米品质明显优于长沙地区。(3)不同水稻品种(系)在长沙地区种植的精米镉含量与胶稠度、蛋白质含量间具显著相关性;而在惠州地区主要与糙米率、精米率呈显著水平的负相关;与其他米质性状的相关性均未达显著水平。惠州地区稻田环境更利于种植水稻,‘湘晚12选32’、‘湘晚籼12号’、‘湘晚6选31’等为低镉积累品种,可推广;‘佳福占’、‘9311选’、‘R云育90’等镉含量已超过国标,不可作为生产推广品种。     

网室内棉花不育系蜜蜂授粉试验研究

本研究在网室内利用蜜蜂为6个棉花不育系材料授粉，以人工授粉作为对照，研究蜜蜂授粉和人工授粉在农艺性状等指标上的差异。结果表明，蜜蜂授粉和人工授粉的单株结铃数和空果枝数有极显著差异；不同不育系的单株结铃数差异极显著，果枝数有显著差异。晋56-1A、晋56-3A、晋56-6A的单株结铃数在蜜蜂授粉和人工授粉间有显著性差异，晋56-2A和晋56-5A的单株结铃数在不同授粉方式下有极显著差异；晋56-4A和晋56-6A的空果枝数有极显著差异。室内考种表明，蜜蜂授粉的衣分范围为26.3%～39.6%，人工授粉的衣分为29.4%～35.3%，人工授粉衣分范围相对较小。人工授粉的单铃籽粒数、制种产量均比蜜蜂授粉大，铃重、籽指、发芽率相差不大。蜜蜂授粉制种产量达人工授粉的80%左右；而制种成本可节约50%以上。因此，选择强群势蜂群、适时有效的虫害管理等措施，可提高棉花不育系制种效率，对棉花“三系”的发展有重要的推动作用。     

Quantitative trait loci mapping for yield-related traits under low and high planting densities in maize (Zea mays)

Average maize yield per hectare has increased significantly because of the improvement in high-density tolerance, but little attention has been paid to the genetic mechanism of grain yield response to high planting density. Here, we used a population of 301 recombinant inbred lines (RILs) derived from the cross YE478 × 08–641 to detect quantitative trait loci (QTLs) for 16 yield-related traits under two planting densities (57,000 and 114,000 plants per ha) across four environments. These yield-related traits responded differently to high-density stress. A total of 110 QTLs were observed for these traits: 33 QTLs only under low planting density, 50 QTLs under high planting density and 27 QTLs across both densities. Only two major QTLs, qCD6 and qWKEL2-2, were identified across low- and high-density treatments. Seven environmentally stable QTLs were also observed containing qED6, qWKEL3, qRN3-3, qRN7-2, qRN9-2 and qRN10 across both densities, as well as qRN9-1 under low density. In addition, 16 and eight pairs of loci with epistasis interaction (EPI) were detected under low and high planting densities, respectively. Additionally, nine and 17 loci showed QTL × environment interaction (QEI) under low- and high-density conditions, respectively. These interactions are of lesser importance than the main QTL effects. We also observed 26 pleiotropic QTL clusters, and the hotspot region 3.08 concentrated nine QTLs, suggesting its great importance for maize yield. These findings suggested that multiple minor QTLs, loci with EPI and QEI, pleiotropy and the complex network of “crosstalk” among them for yield-related traits were greatly influenced by plant density, which increases our understanding of the genetic mechanism of yield-related traits for high-density tolerance.