Genome-Wide Analysis of the Peroxidase Gene Family and Verification of Lignin Synthesis-Related Genes in Watermelon

Watermelon (Citrullus lanatus) is an important horticultural crop worldwide, but peel cracking caused by peel hardness severely decreases its quality. Lignification is one of the important functions of class III peroxidase (PRX), and its accumulation in the plant cell wall leads to cell thickening and wood hardening. For in-depth physiological and genetical understanding, we studied the relationship between peel hardness and lignin accumulation and the role of PRXs affecting peel lignin biosynthesis using genome-wide bioinformatics analysis. The obtained results showed that lignin accumulation gradually increased to form the peel stone cell structure, and tissue lignification led to peel hardness. A total of 79 ClPRXs (class III) were identified using bioinformatics analysis, which were widely distributed on 11 chromosomes. The constructed phylogenetics indicated that ClPRXs were divided into seven groups and eleven subclasses, and gene members of each group had highly conserved intron structures. Repeated pattern analysis showed that deletion and replication events occurred during the process of ClPRX amplification. However, in the whole-protein sequence alignment analysis, high homology was not observed, although all contained four conserved functional sites. Repeated pattern analysis showed that deletion and replication events occurred during ClPRXs’ amplification process. The prediction of the promoter cis-acting element and qRT-PCR analysis in four tissues (leaf, petiole, stem, and peel) showed different expression patterns for tissue specificity, abiotic stress, and hormone response by providing a genetic basis of the ClPRX gene family involved in a variety of physiological processes in plants. To our knowledge, we for the first time report the key roles of two ClPRXs in watermelon peel lignin synthesis. In conclusion, the extensive data collected in this study can be used for additional functional analysis of ClPRXs in watermelon growth and development and hormone and abiotic stress response.     

Differential Physio-Biochemical and Metabolic Responses of Peanut (Arachis hypogaea L.) under Multiple Abiotic Stress Conditions

The frequency and severity of extreme climatic conditions such as drought, salinity, cold, and heat are increasing due to climate change. Moreover, in the field, plants are affected by multiple abiotic stresses simultaneously or sequentially. Thus, it is imperative to compare the effects of stress combinations on crop plants relative to individual stresses. This study investigated the differential regulation of physio-biochemical and metabolomics parameters in peanut (Arachis hypogaea L.) under individual (salt, drought, cold, and heat) and combined stress treatments using multivariate correlation analysis. The results showed that combined heat, salt, and drought stress compounds the stress effect of individual stresses. Combined stresses that included heat had the highest electrolyte leakage and lowest relative water content. Lipid peroxidation and chlorophyll contents did not significantly change under combined stresses. Biochemical parameters, such as free amino acids, polyphenol, starch, and sugars, significantly changed under combined stresses compared to individual stresses. Free amino acids increased under combined stresses that included heat; starch, sugars, and polyphenols increased under combined stresses that included drought; proline concentration increased under combined stresses that included salt. Metabolomics data that were obtained under different individual and combined stresses can be used to identify molecular phenotypes that are involved in the acclimation response of plants under changing abiotic stress conditions. Peanut metabolomics identified 160 metabolites, including amino acids, sugars, sugar alcohols, organic acids, fatty acids, sugar acids, and other organic compounds. Pathway enrichment analysis revealed that abiotic stresses significantly affected amino acid, amino sugar, and sugar metabolism. The stress treatments affected the metabolites that were associated with the tricarboxylic acid (TCA) and urea cycles and associated amino acid biosynthesis pathway intermediates. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and heatmap analysis identified potential marker metabolites (pinitol, malic acid, and xylopyranose) that were associated with abiotic stress combinations, which could be used in breeding efforts to develop peanut cultivars that are resilient to climate change. The study will also facilitate researchers to explore different stress indicators to identify resistant cultivars for future crop improvement programs.     

15N同位素在华北冬小麦夏玉米氮营养来源研究中的应用

小麦-玉米一年两作是华北平原最主要的种植方式之一,对保障国家粮食安全至关重要。阐明该种植体系作物氮营养来源定量组成对区域养分资源管理、施肥制度优化、作物营养状况调控都具有十分重要的意义。¹⁵N作为氮元素的一种稳定同位素,其示踪技术在农田氮肥去向,作物氮营养来源等农业生产领域得到广泛应用。本文主要概述了¹⁵N同位素技术在研究当季施入化肥氮、前茬残留化肥氮、播前土壤固有硝态氮对华北冬小麦-夏玉米氮营养贡献中的具体应用方法、实例及相关研究结果,并对叶面肥氮、还田秸秆氮、大气沉降氮等其他氮营养来源的研究进行了展望,以期为该种植体系养分资源管理以及施肥制度优化提供理论参考。     

轧机垂直系统动力学参数辨识

 针对轧机垂直系统动力学参数可信度不足等问题,提出一种基于实测数据的改进粒子群算法辨识轧机垂直系统动力学参数的方法。首先,将轧机垂直系统刚度和阻尼考虑成达芬振子和范德波尔振子,构建轧机垂直系统非线性动力学模型,并对粒子群算法进行改进;然后,通过数值仿真算例辨识得到系统在感染噪声和不含噪声时的动力学参数,验证了该算法的有效性;最后,以现场某轧机垂直系统为研究对象,基于现场实测数据,应用该算法进行辨识,得到了轧机垂直系统动力学参数估计,通过实测位移、速度和加速度信号分别与辨识后的位移、速度和加速度信号进行对比,证明该方法辨识轧机垂直系统动力学参数结果可靠,具有一定的工程应用价值。     

自主式水下机器人试验平台研制与实验研究

为了进行自主式水下机器人智能行为的研究,自行研制了“海狸”水下机器人试验平台．介绍了“海狸”水下机器人的系统结构,在分析推进器性能的基础上,通过数字罗盘、加速度计以及深度计等传感器获得的运行速度、角速度等位姿信息,建立了水下机器人前向运动模型,进行了水下机器人运动控制与状态监测系统的实验研究．水池实验结果表明,“海狸”水下机器人可实现自主式水下机器人的基本运动控制,所建立的水下机器人前向运动模型能够描述水下机器人试验平台的动态行为,状态监测算法能够识别水下机器人的典型故障,从而验证了所提算法的有效性,同时也验证了作为水下机器人智能行为研究载体的试验平台的有效性和可行性．     

基于灰度共生矩阵和支持向量机的气液两相流流型识别

根据灰度共生矩阵具有较好的纹理表达能力的特性,提出了一种基于图像灰度共生矩阵和支持向量机相结合的气液两相流流型识别的新方法。该方法利用高速摄影系统获取水平管道内气液两相流的流动图像,经过图像处理后,提取图像灰度共生矩阵的纹理特征,进而建立流型图像的灰度共生矩阵纹理特征向量,并以此特征向量作为流型样本对支持向量机进行训练,实现了对流动图像的流型智能化识别。实验结果表明,支持向量机能够快速准确地识别水平管道内的7种典型流型,整体识别率达到100%,每幅流型图像的判别时间约为1.7 s,为流型在线识别提供一种新方法。     

2-(2,5-二氨基苯)乙醇的合成

在二氯乙烷介质中,将3-氟苯乙酸于70℃下硝化4 h得到5-氟-2-硝基苯乙酸(质量分数为67.8%)。用硼烷还原5-氟-2-硝基苯乙酸后,接着用氨水在高压釜中加热到100℃氨解,得到2-(5-氨基-2-硝基苯)乙醇(84.4%)。最后,10%Pd/C作催化剂,在无水异丙醇介质中,0.6～0.7 MPa下,于70～80℃催化氢化12 h,得到目标分子2-(2,5-二氨基苯)乙醇(64%)。与文献工艺相比,目标分子总收率提高11%。用H–NMR和MS确定了目标分子2-(2,5-二氨基苯)乙醇的化学结构。     

基于M型标准块的视觉引导机器人系统手眼标定方法研究

针对线结构光传感器引导的机器人系统的手眼标定问题,提出了一种以M型标准块为标定物的方法。该M型标定物的两条平行的脊线作为约束,基于两条平行脊线的约束建立包含手眼关系、机器人运动学以及两条直线位姿参数误差的模型。首先基于定点约束求解手眼关系初值并以此为基础解算出直线位姿参数的初值,然后通过最小二乘法解算误差参数并补偿到模型中,不断迭代直至计算的误差参数小于阈值,最终得到最终的机器人手眼关系及运动学误差参数。为了验证标定方法的有效性,以某精加工平面为被测物,利用线结构光机器人系统对平面进行测量,得到平面点云;拟合最小二乘平面,计算点到平面距离的均方根值作为评价依据。分别对所述M型标准块和标准球两种方法进行了实验对比,结果表明,相较于标准球方法,所述M型标准块方法得到的均方根误差由0.152 mm减少到0.080 mm,均方根误差的标准差由0.043 mm减少到0.005 mm,其标定结果的精度及稳定性得到显著提高。     

基于改进YOLOv5的飞机舱门识别与定位方法研究

机场特种车辆的自动靠机是未来智慧机场发展的必然要求,实现自动靠机的关键是对飞机舱门进行准确识别与定位;针对于此问题,提出一种基于改进YOLOv5和单目视觉的舱门识别与定位方法,通过在模型中加入了一种轻量化的卷积注意力模块（CBAM,convolutional block attention module）,提高了算法对飞机舱门的特征提取能力;针对YOLOv5的重复特征提取问题,引入了空间金字塔池化结构（SPPCSPC,spatial pyramid pooling cross stage paritial connection）,并改进分组卷积组数为4,提高了算法的检测精度;通过获取候选框中角点的像素,利用空间几何关系,实现了对舱门准确的三维定位。实验结果表明,改进后的YOLOv5算法mAP达到96.5%,相比原有算法提升了5.6%。在舱门前方19 m和1 m处时,实时最大定位误差分别为0.15 m和0.01 m,能够满足特种车辆靠机完成后与舱门保持5-10 cm的安全距离要求。