棉田土壤养分分析与土壤墒情监测系统应用

【目的】研究土壤养分的空间变异程度及分布规律,为该区域科学施肥提供依据。【方法】以新疆生产建设兵团第八师石河子总场六分场数字农业示范田为研究区域,应用土壤墒情监测系统、GIS与地统计学的方法,对棉田土壤含水量与温度进行实时采集、分析并存储在服务器里面,分析石河子总场土壤含水量和温度变化规律、棉田土壤养分空间分布特点及变异规律。【结果】(1)根据监测数据分析,随着灌水量增加和棉花生育期推进,上层0~30 cm比下层40~60 cm的土壤含水量变化趋势明显。0~20 cm土层土壤补偿水比较充分,各个监测点土壤含水量基本维持在比较适宜的范围内。土壤各层温度受大气温度影响并随着土层深度的加深而减弱,随着土层深度的逐渐加深滞后时间相对延长;受棉株逐渐长高变大以后遮阴等造成的影响,7月以后各土层温度逐渐持平,波动不大。(2)土壤全氮、速效磷和速效钾均呈现出中等程度变异;(3)土壤速效钾的块金值在25%~75%(块金值为0.497)表现为中等空间自相关性外,土壤全氮、速效磷指标的块金系数小于25%表现为强烈的空间自相关性。【结论】应用土壤墒情实时监测系统指导棉田灌溉,较往年没有任何减产减质的情况下,棉花灌溉在全生育期内比以往灌溉次数下降了1~3次,节约水资源约20%左右。研究区域内土壤全氮、速效磷和速效钾变异呈现中等程度变异特征,全氮、速效磷表现为极强空间自相关性,速效钾表现为中等强度的空间相关性。     

安徽沿江地区油麦后直播棉的品种选用策略

在目前安徽沿江地区不能实现棉花机采的情况下,提出了“植株高度既适于机采也适于人工采收,含絮力适中(不易落花便于集中采收),生育期适中(播种到采收为180天左右),纤维品质及产量性状较优(纤维长度30.0 mm以上,断裂比强度30.0 cN/tex以上,马克隆值5.0以下,籽棉产量3750 kg/hm 2以上,衣分在40%左右)”的油(或麦)后直播棉模式的人工采收品种选用策略。旨在促进安徽沿江地区棉花生产稳定发展。     

化学打顶对阿拉尔垦区主栽品种光合冠层的影响

化学打顶是指利用植物生长调节剂来打破作物顶端优势,进而保障作物的正常生长和生产。本文为探究化学打顶对作物的影响,利用摇钱素和棉花打顶剂处理新陆中70和新陆中82不同品种,同时测定不同化学打顶剂处理条件下,棉花的净光合速率、气孔导度、蒸腾速率、胞间CO₂浓度及棉花冠层叶面积指数指标。研究发现：不同化学打顶处理条件下,与人工打顶相比化学打顶的棉花的五种指标变化均不明显,但新陆中70和新陆中82品种的净光合速率平均值与对照相比分别高出3 μmol/(m2.s)和2 μmol/(m2.s),且冠层叶面积指数值比人工打顶的略高。试验结果表明化学打顶处理后没有造成棉花疯长,提高了光能利用率,进而增加作物群体的光合作用。     

松阳县古松树的松材线虫病现状调查与分析

古松树是历史的见证,是文化的承载,其保护工作具有重要意义,但因松材线虫的传播侵染,其生存状况不容乐观。本研究以松阳古松树为对象,基于分子检测技术,对其松材线虫病现状进行了调查与分析。结果表明,有12个乡镇近60%的古松树均已感病,疫情较为严重,需及时开展抗病保护工作。     

Relationships Among the Feeding Behaviors of a Mirid Bug on Cotton Leaves of Different Ages and Plant Biochemical Substances

Apolygus lucorum (Meyer-Dür) (Hemiptera: Miridae) tends to feed on young plant tissues. To explore the relationship between stylet probing behaviors of adult A. lucorum and conditions of cotton leaves, we conducted an experiment using electropenetrography (EPG). Behaviors were recorded on four cotton varieties, in relation to thickness and biochemical traits of differently-aged leaves. Cotton leaf age had a significant effect on the probing behavior of A. lucorum but cotton variety did not. One-day-old leaves of A. lucorum received the highest mean number of stylet probes (penetrations) per insect, and longest mean durations per insect of combined stylet probing or its components, cell rupture and ingestion behaviors. All of the leaf traits (thickness and biochemical substances) were similar among these four cotton varieties. Leaf thickness had a significantly negative effect on the same four variables above. Gossypol and tannin also had a negative impact on combined probing duration. Redundancy analysis showed that the four EPG variables were closely related to nutrient substances (amino acids, sugar, and water) while they had the opposite relationship with plant defense substances (gossypol and tannin). On cotton in the seedling stages, A. lucorum fed more readily on the youngest, thinnest leaves in our no-choice EPG experiments. Nutrients and chemical resistance substances determined the probing duration of A. lucorum. Our findings can contribute to better understanding of patterns of feeding and host consumption by A. lucorum, ultimately improving cotton resistance to A. lucorum.     

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.     

SSCP Marker Development and Analysis of Candidate Restorer Gene Rf1 for Cotton Cytoplasmic Male Sterility

[Objective] Locating the cotton cytoplasmic male sterility (CMS) restorer gene Rf₁ is important for investigating restorer gene mechanisms and improving restorer lines. In our previous study, a gene cluster, with nine Pentatricopeptide repeat(PPR) genes and nine other genes, was found within the 160-kb Rf₁ target region in Scaffold 333. The objective here was to improve the density of Rf1-linked markers in the target region and determine the expression profiles of candidate genes. [Method] Using the sequences of the 18 genes, we designed 155 single-strand conformation polymorphism (SSCP) primers covering all of the gene sequences to identify the polymorphic SSCP markers between the fertile and sterile pools. Additionally, real-time polymerase chain reaction(PCR) was performed to analyze the expression profiles of eight candidate genes in the four developmental stages of buds of sterile, maintainer and restoring lines, respectively. [Result] In total, 15 polymorphic primers were identified. A genotype analysis of the F₂ population was conducted using the 15 primers and 3 other polymorphic simple sequence repeats (SSR) markers. The markers were distributed in a 4.8 cM range. In addition, owing to the influence of sterile cytoplasm or restorer genes, most of the genes showed different expression patterns in the four developmental stages of the three lines' buds. [Conclusion] SSCP markers tightly linked to Rf₁ were identified and the expression profiles of candidate genes were determined. This study provides a basis for the further fine mapping of restorer genes and for candidate gene screening.     

Dynamics of Cotton Rhizosphere Bacterial Community Structure in Cotton Continuous Cropping Field Soil

[Objective] The aim of this study is to understand the dynamics of cotton rhizosphere bacterial community structure in cotton continuous cropping field soil. [Method] 16S rDNA genes were sequenced by high-throughput sequencing technology to determine the community structure of cotton rhizosphere bacteria in different developmental stages using an upland cotton cultivar (Gossypium hirsutum cv. TM-1). [Result] Four dominant phyla were found in the cotton rhizosphere bacterial community including Proteobacteria, Acidobacteria, Planctomycetes, and Bacteroidetes. The four dominant phyla and Firmicutes were largely influenced by cotton root. The relative abundances of Acidobacteria, Planctomycetes, Bacteroidetes were promoted, and Proteobacteria and Firmicutes were inhibited, by cotton root. There were significant differences in community structure, but not species richness or α-diversity among different developmental stages of the cotton rhizosphere bacterial community; the differences between the flowering stage and the budding stage were greater than the differences between the budding stage and the seedling stage. The diversity of the rhizosphere bacterial community in cotton continuous cropping field soil was significantly higher than that of the bulk soil; the β-diversity values of both the rhizosphere and bulk soil bacterial communities were highest in the flowering stage. [Conclusion] The structure and dynamics of the cotton rhizosphere bacterial community in cotton continuous cropping field soil was defined by high-throughput sequencing. The effect of cotton on the rhizosphere bacterial community structure was most significant in the flowering stage.     

星油藤青枯病病原菌鉴定

 星油藤(Plukenetia volubilis L.) 是一种重要的藤本油料植物,在我国华南地区广泛种植。青枯病是近两年在海南星油藤种植区发生的新病害,为探究星油藤青枯病菌的基本特性及种下分化情况,本研究对分离的6株代表菌株进行了相关分析。细菌学鉴定及致病性测定结果表明,该病害是由类茄科雷尔氏菌(Ralstonia pseudosolanacearum)侵染引起。同时,从传统分类及分子生物学不同层面分析了星油藤青枯病菌的遗传分化情况。生理小种及生化变种的测试结果表明,星油藤青枯病菌属于1号生理小种和生化变种Ⅲ;16S rDNA和egl基因部分序列聚类分析显示,星油藤青枯病菌属类茄科雷尔氏菌演化型Ⅰ即亚洲分支菌株,序列变种34。     

一株耐铝甜瓜枯萎病拮抗细菌的分离鉴定及其耐铝特性研究

从甜瓜根际酸性土壤中分离筛选到1株耐铝甜瓜枯萎病拮抗菌，命名为A2。根据表型、生理生化特征和16S rRNA基因序列相似性分析，将其鉴定为Pseudomonas sp.。菌株A2对甜瓜枯萎病病原菌的相对防效为68.3%，且拮抗能力具有遗传稳定性。相比AlCl3处理，菌株A2对Al2(SO4)3表现出了更好的耐受性，最高可耐受50mmol/L Al3+。在含有A13+的S-LB培养基中，菌株最适生长温度为30 ℃；培养基初始pH值的降低会加剧A13+对菌株A2的毒害作用。研究结果可为含活性铝的酸性土壤中甜瓜枯萎病的生物防治提供优良菌株资源和理论基础。