Comparisons of Three Recurrent Selection Methods in the Improvement of Maize Populations

The maize population Csyn 4 was improved for three cycles with three recurrent selection methods MS1, MS1-HS, and MHSRRS in northern China. A total of 40 NC Ⅱ testcrosses were made by four testers with Csyn 4 and 10 improved populations, which were evaluated in four environments in the cropping season of 2005. Analysis of variance indicated a significant progress （P〈 0.05） in yield and other chief agronomic traits in the improved populations and testcrosses, demonstrating that the three recurrent selection methods were effective for increasing grain yield of testcrosses and improvement of general combining ability in maize population. The average grain yield increase of population Csyn 4 in MS1, MS1-HS, and MHSRRS recurrent selections was 266.7 kg ha^-1 （5.3%）, 288.0 kg ha^-1 （5.7%）, and 231.3 kg ha^-1 （4.6%） per cycle, while the grain yield of S 1 progeny of population for Csyn 4 was increased by 420.0 kg ha^-1 （10.9%）, 376.0 kg ha^-1 （9.8%）, and 414.7 kg ha^-1 （10.8%） per cycle in MS1, MS1-HS, and MHSRRS recurrent selections, respectively. Linear responses （b） in the MS1, MS1-HS, and MHSRRS recurrent selections were the same as the realized responses of the selection （G） for grain yield increase of Csyn 4 and S1 progeny of the populations. The grain yield of testcrosses increased by 3.3-5.2% on average per cycle. The value of heterosis did not display any differences amongst the different cycles of selections. The GCA for yield component traits of population Csyn 4 was improved significantly by means of three selection methods, whereas the GCA for plant height, ear height, days to silking, and days to pollen did not show significant increase in the recurrent selections. GCA for the number of tassel branches were decreased in the selections, while GCA for the number of plant leaves were increased, but the difference was not significant.     

Influence of potassium humate on biochemical and agronomic attributes of bean plants grown on saline soil

To study the effect of soil application of potassium humate (KH) (0, 70 and 140 Kg ha^?1) on agronomic, biochemical attributes, and yield and its components on bean (Phaseolus vulgaris L.) cultivars ‘Bronco’ grown under two sites having different level of salinity (EC = 3.00 or 5.00 ± 0.20 dS m^?1). Two field trials were conducted at the Agriculture Test Station, Faculty of Agriculture, Fayoum University, in 2014 and 2015. The obtained results indicated that addition of KH increased all of the studied growth parameters, i.e. plant height, number of leaves, leaf area, stem diameter and canopy dry weight. Moreover addition of KH significantly increased membrane permeability measurements. KH significantly increased chemical composition related to salt tolerant either inorganic e.g. N, P, K, and decreased Na and Cl contents of leaves or organic components e.g. chlorophyll a + b, carotenoids, anthocyanin total phenolics, total flavonoids and proline. DPPH radical-scavenging activity and yield and its components were increased. The soil application of KH was found to be highly effective at improving the growth and yield of bean plants by alleviating the inhibitory effects of soil salinity stress.     

龙眼MEE70/MSI1基因DlMEE70-1a及其可变剪接体DlMEE70-1b的分离及其在体胚发生过程中的表达分析

MEE70/MSI1是拟南芥母性效应胚胎滞育基因,在植物胚胎发生过程中具有重要作用。采用RACE技术获得龙眼MEE70-1a(登录号KC492117)及其可变剪接体MEE70-1b(登录号KC492118)c DNA序列,克隆MSI1g DNA(登录号KC492126)序列。生物信息学分析预测Dl MEE70-1a和Dl MEE70-1b均为亲水不稳定的酸性蛋白,主要定位于过氧化物酶体和细胞核,各含有4和1个WD-repeat结构域。MEE70-1a和MEE70-1b在体细胞胚胎发生过程实时荧光定量PCR分析结果表明,Dl MEE70-1a和Dl MEE70-1b表达趋势以心形胚为界,除了Dl MEE70-1b的不完全胚型紧实结构(ICp EC)到球形胚(GE)阶段之间,都表现出先降后升的趋势;胚性愈伤组织(EC)时期两者表达量一致且最高;心形胚(HE)时期,两者表达量一致且最低,另Dl MEE70-1b在不完全胚性紧实结构(ICp EC)表达量与心形胚基本一致。这2个表达剂量是胚胎发生的重要保障,心形胚(HE)后,Dl MEE70-1a被再次激活转录促进胚胎正常发育。从Dl MEE70-1a和Dl MEE70-1b的理化性质、WD重复结构域数量、亚细胞定位以及表达量和趋势,可以推测Dl MEE70-1a需要Dl MEE70-1b的协同来调控龙眼胚胎发育。     

Contribution of time-series data cubes to classify urban vegetation types by remote sensing

Mapping urban vegetation types is important for urban planning and assessing environmental justice. Nowadays, despite data cubes projects are providing Analysis Ready Data to facilitate time-series analysis, we did not found studies employing these data for improving urban vegetation mapping. By relying solely on open data and software, this work proposes and evaluates the integration of time-series data cubes in a hybrid image classification method to map the intra-urban space, differentiating Tree cover and Herb-shrub. The urban area of Goiânia, Goiás, Brazil, is the study area. The hybrid method combined object-based classification of a pan-sharpened CBERS-4A WPM image (spatial resolution of 2 m) with the pixel-based classification of Sentinel-2 MSI time-series data cubes (10 m). Both approaches used the Random Forest algorithm. Objects from the CBERS-4A segmentation composed the spatial unit of analysis and the class assignment depended on the Sentinel-2 time-series urban land cover probabilities. Based on both Maps probabilities, Shannon entropy was calculated to attribute the final urban land cover to the objects. Urban land cover probabilities presented similar spatial distribution patterns for both classification approaches. Regarding the thematic maps, the Herb-shrub cover area was 35% higher in Sentinel-2 time-series classification than in GEOBIA classification, but Tree cover was 21% lower. In general, 75% of the study area was equally classified by the initial approaches. However, for 9% of the remaining area, the hybrid classification improved vegetation classes accuracies by 35%, contributing to the vegetation covers identification. Thus, this study contributes to methodological procedures for urban land cover study and demonstrates that hybrid maps based on open data are effective to reduce classification mistakes, allowing more accurate monitoring, planning, and designing of different urban vegetation types. Future research efforts should focus on scale compatibility between data of different spatial resolutions and expand the use of data cubes to integrate time-series information into the GEOBIA classification.     

基于Sentinel-2影像的平寨水库水体透明度遥感反演

[目的]研究水体透明度的变化规律及其空间分异驱动因素,为管理湖库及恢复湖库生态系统提供科学依据。[方法]基于2020年5月18日,8月26日,11月14日的Sentinel-2 MSI卫星影像及准同步实测透明度数据构建平寨水库透明度遥感反演模型,利用地理探测器定量分析影响透明度空间分异的驱动因素。[结果](1)平寨水库水体透明度与Sentinel-2 MSI的B₃波段最为敏感,利用波段组合B₃×B₄作为最佳敏感因子构建出的透明度反演模型具有较高的精度(R²=0.81,RMSE=0.11 m, MRE=16.91%)。(2)平寨水库水体透明度呈现出中心库区高而各支流上游低,近水体两岸低的空间分布趋势,且水体透明度11月>8月>5月。[结论]总悬浮物、叶绿素a及总有机碳含量是平寨水库水体透明度空间分异的主要因素。总磷、总氮、水温及风速通过影响水体中的总悬浮物、叶绿素a及总有机碳含量进而影响水体透明度空间分布。     

基于星-机光谱融合的棉花叶片SPAD值反演

【目的】为提高棉花叶片叶绿素含量的反演精度,并掌握其在山东省夏津县的空间分布特征。【方法】本研究以山东省德州市夏津县为研究区,以夏津县大李庄棉田为试验区,通过SPAD（soil and plant analyzer development,SPAD）仪实地测定试验区棉花叶片叶绿素含量的相对值（SPAD值）,并获取同期试验区无人机（unmanned aerial vehicle,UAV）近地多光谱图像和研究区Sentinel-2A MSI（MSI）卫星影像;然后分别基于UAV和MSI的光谱反射率,构建并筛选最优光谱参量,采用多元线性回归（multiple linear regression,MLR）建立SPAD值定量反演模型;最后采用二次多项式拟合法融合UAV和Sentinel-2A MSI对应的最优光谱参量,对比分析融合前后模型效果,优选最佳反演模型,实现研究区SPAD值反演。【结果】研究表明,(REG-R)/(REG+R)、R/G、CL(red edge)、NDVI可作为SPAD值的最优光谱参量;基于UAV图像的定量反演模型精度优于基于MSI影像的模型;基于二次多项式拟合后建模R ²提高了0.015—0.057,RMSE降低了0.457—0.638,验证R ²提高了0.040—0.085,RMSE降低了0.387—0.397,RPD提高了0.020—0.139;将融合后的MSI光谱参量代入基于UAV图像的反演模型（Fused MSI-Mod_UAV）,也可获得较高的反演精度,建模R ²达0.672,RMSE为3.982,验证R ²达0.713,RMSE为3.859,RPD为1.685;基于上述模型进行研究区棉花叶片SPAD值反演分析,试验区整体呈南高北低的分布趋势,研究区呈中间低、四周高的分布趋势,均与实地情况一致,具有较好的预测效果。【结论】采用二次多项式拟合法融合无人机和卫星影像数据,可较好地实现区域高精度作物生长指标的定量反演,研究结果可丰富多源遥感融合理论与技术,为后续棉花长势监测与精准生产提供技术参考和数据支持。     

基于Sentinel-2A MSI特征的毛竹林刚竹毒蛾危害检测

为快速、准确地检测毛竹林刚竹毒蛾（Pantana phyllostachysae Chao）危害,基于Sentinel-2A MSI数据分析不同刚竹毒蛾危害等级下毛竹林像元光谱的变化,从叶损量、绿度、含水率等多个维度选择对刚竹毒蛾危害具有响应能力的22个Sentinel-2A MSI光谱衍生指标;经单因素方差分析（ANOVA）以及递归特征消除法（Recursive feature elimination, RFE）优选后,得到可用于刚竹毒蛾危害识别的10个遥感特征,包括LAI、RVI、NDMVI、EVI、NDVI₇₀₅、NDVI₇₈₃、RegVI₁、RegVI₂、GVMI和NDWI;将上述指标作为自变量,虫害等级作为因变量,建立基于XGBoost模型的刚竹毒蛾危害检测模型。研究发现,Sentinel-2A MSI数据波段6、7、8、8a对刚竹毒蛾危害具有较强的响应能力;红边与近红外波段参与构建的指数有效反映了竹林的受害情况;XGBoost模型对刚竹毒蛾危害识别的总精度为83.70%,对不同刚竹毒蛾危...