我国樟树害虫研究文献计量分析

采用文献计量学方法,统计分析了1980—2021年在国内期刊上发表的165篇关于樟树害虫研究的中文文献,系统梳理了我国樟树害虫研究概况,明确了该领域的研究热点和发展趋势.研究结果表明目前我国樟树害虫研究处于逐渐发展阶段;应用VOSviewer软件分析文献关键词共现图谱,历年来相关领域研究主要集中在园林植物上的樟树害虫,研究方向主要关注樟树害虫的生物学特性、发生规律、虫情调查和综合防治技术等方面.通过中文文献研究热点知识图谱分析可知,相关研究热点主要在樟巢螟、樟颈曼盲蝽、黑翅土白蚁、樟叶蜂等樟树害虫的研究.文献计量分析结果为我国樟树害虫研究提供了思路和方法.     

近五年我国进口巴西棉花质量分析

根据近五年实验室检测大数据,分析我国进口巴西棉花品质指标的主体范围,总结不同主体指标各等级分布情况及变化趋势.结果 表明,巴西棉花的品级、长度和马克隆值合同品质符合率高,但不同指标不同时间段品质符合率略有偏差.综合认为:近五年巴西棉花品质一致性好,主体品质占比大,主体指标范围品质符合率高.     

冻融循环下红色砒砂岩水泥土力学性能试验研究

为实现砒砂岩作为一种自然资源的潜在利用价值,提高砒砂岩有效利用,将鄂尔多斯市准格尔旗的红色砒砂岩加入不同掺量水泥制成砒砂岩水泥土,进行不同围压、不同冻融循环次数条件下的不固结不排水三轴试验,得到了砒砂岩水泥土的各力学参数的变化规律,并通过超景深三维显微镜对砒砂岩水泥土的细观结构进行观测.结果表明:砒砂岩水泥土的应力-应变曲线呈应变软化趋势,随水泥掺量的增加其黏聚力和内摩擦角呈线性增长的趋势.砒砂岩水泥土的内摩擦角受冻融循环影响较小,而黏聚力受冻融循环影响较大.水泥掺量越多,砒砂岩水泥土的抗冻性越好,但其脆性特征越明显.对细观结构的观测进一步验证了冻融使得低掺量水泥的固化土细观结构发生较大改变,导致内部空隙增大,而水泥土随水泥掺量的增加其内部结构更加致密,从而提高了水泥土的抗冻性.     

YX106系杜洛克种猪有效精子数遗传改良

公猪在养猪生产中占据着最重要的位置，公猪的优秀遗传基因可通过精液快速传递到商品群中，从而快速获得效益。因此公猪精液的好坏关系着公猪的价值。在高成本的选育前提下，选育出1头精液品质优良的公猪具有重要的意义。研究将公猪精液品质指标加入到公猪选育性状中进行对比分析。研究结果表明：对公猪进行精液有效精子数选育可提高选育质量，正向促进公猪选育效果，提升种公猪利用效率。     

微流控芯片在农产品安全检测中的应用

近年来,随着食品工业的迅猛发展,国内外食品安全事故也频繁发生。开发安全可靠、便携有效的检测方法对食品安全至关重要。微流控芯片集样品前处理、分离和检测等过程为一体,实现了样品前处理和检测分析的自动化、集成化、小型化、低消耗、高效率和便携化,满足了现场、实时检测的需求。本研究对微流控芯片在食品成分、农药残留、兽药残留、食品添加剂和重金属检测中的应用进行归纳总结,为农产品安全检测提供参考。     

基于工作过程的南疆高职院校园艺技术专业农业应用化学教学改革探析

分析了从南疆职业院校园艺技术专业农业应用化学教学中存在的问题,以提高该课程教学要求及园艺技术人才专业人才培养规格为目标,提出了对接教学领域与职业技能、职业素养,改革教学内容、课程体系、优化教学的方法和手段,为提高园艺技术专业服务育人本质,培养更多更好服务地方经济社会发展的高素质、高技能的园艺技术专业人才奠定重要的基础。     

守法合规乃农机企业营商之本

2020年底以来,农机行业的K值问题掀起一轮关注的声浪。不少地方农机化主管部门出台了针对拖拉机K值管理的细化举措,从制度上堵住企业钻政策空子获得不正当得利的漏洞。饶是如此,目前仍有农机企业并未把这个管理举措当一回事,有的还在想着如何采取措施规避K值管理,而不是真正从底盘设计的角度去达到拖拉机产品的正常、规范标准要求。     

Improvement,identification, and target prediction for miRNAs in the porcine genome by using massive,public high-throughput sequencing data

Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information.     

Cotton Image Segmentation Algorithm Based on Fusion Method of Markov Random Field and Quantum Particle Swarm Cluster

[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested.