新时代省级农业科学院信息公开调查研究

以省级农业科学院为研究对象,在深入调查研究省级农业科学院信息公开的现状后,分析了省级农业科学院信息公开方面存在的问题和不足,提出了进一步提高信息公开思想认识、优化公开平台建设、规范信息公开内容、健全信息公开长效机制等对策建议,以期为新时代省级农业科学院信息公开标准化规范化建设提供参考.     

Preliminary assessment of large‐scale co‐culture of sandfish (Holothuria scabra) with the Babylon snail (Babylonia areolata) in earthen ponds and in raceways

Holothuria scabra (sandfish) and Babylonia areolata were trialed in two large‐scale co‐culture experiments. Experiment 1 assessed co‐culture in 4 × 400 m² earthen ponds where Babylonia were cultured in a central pen at a density of 400 individuals/m² with sandfish occupying the remaining pond space at 1.1 individuals/m². Sandfish grew from 18.20 ± 6.67 g to 119.03 ± 17.74 g in 92 days and Babylonia (fed trash fish in both experiments) grew from 0.90 ± 0.38 g to 4.93 ± 1.44 g, but Babylonia growth was not increased in co‐culture compared to monoculture. Water and sediment quality varied between co‐culture and monoculture ponds. Neither showed clear improvement due to sandfish culture. Experiment 2 compared non‐segregated sandfish‐Babylonia co‐culture with Babylonia monoculture in 20 m² concrete raceways. Sandfish were cultured at 2 individuals/m² and Babylonia at 300 individuals/m². Sandfish grew up to 1.91 g.day^?1 with 100% survival. Babylonia weight gain was significantly greater in co‐culture raceways (3.35 ± 0.64 g over 61 days), which was double that of Babylonia in monoculture. Substrate total N was reduced by 20% in co‐culture compared with monoculture (p = .032). This provisional study of commercial scale sandfish‐Babylonia co‐culture demonstrates culture compatibility, providing a basis for further system development.     

基于卷积神经网络的玉米病害识别方法研究

为解决传统的玉米病害识别方法中特征提取主观性强及误识率高的问题,提出利用卷积神经网络对玉米病害进行识别。以玉米病害图像和健康图像共5种类别的玉米图像为研究对象,并采用LeNet模型进行试验。首先,按照8∶2的比例为每种玉米病害图像选择训练集和测试集。然后,通过试验组合和对比分析的方法比较不同卷积神经网络结构设置对准确率的影响,选出最佳参数。另外,选用Adam算法代替SGD算法来优化模型,通过指数衰减法调整学习率,将L2正则项添加到交叉熵函数中,并选择Dropout策略和ReLU激励函数。最后,确定了一个10层CNN网络结构。试验结果显示,玉米花叶病、灰斑病、锈病、叶斑病和玉米健康识别率分别为95.83%、90.57%、100%、93.75%、100%,平均识别率达96%,平均计算时间为0.15 s。经试验结果比较,该模型识别效果明显高于传统方法,为玉米病害的防治提供技术支持。     

Poorly crystalline iron and aluminium oxides contribute to the carbon saturation and sorption of dissolved organic carbon in the soil

Soil carbon (C) saturation implies an upper limit to a soil's capacity to store C depending on the contents of silt + clay and poorly crystalline Fe and Al oxides. We hypothesized that the poorly crystalline Fe and Al oxides in silt + clay fraction increased the C saturation and thus reduced the capacity of the soil to sorb additional C input. To test the hypothesis, we studied the sorption of dissolved organic carbon (DOC) on silt + clay fractions (<53 µm) of highly weathered oxic soils, collected from three different land uses (i.e., improved pasture, cropping and forest). Soils with high carbon saturation desorbed 38% more C than soils with low C saturation upon addition of DOC, whereas adsorption of DOC was only observed at higher concentration (>15 g kg^?1). While high Al oxide concentration significantly increased both the saturation and desorption of DOC, the high Fe oxide concentration significantly increased the desorption of DOC, supporting the proposition that both oxides have influence on the DOC sorption in soil. Our findings provide a new insight into the chemical control of stabilization and destabilization of DOC in soil.     

河南省农业干旱脆弱性分析

为减轻旱灾损失,根据2005、2015年河南省统计与气象数据,采用10项指标和灰色关联分析法,以最劣值为参照系列分析了该省农业旱灾脆弱性。结果表明,豫西的济源、三门峡、洛阳,豫东的开封、漯河与豫北的鹤壁是河南省干旱脆弱性较强的区域,而豫东南的商丘、驻马店、信阳,豫北的新乡、豫西南的南阳则脆弱性较弱,其他地区居于两者之间;2005—2015年河南省干旱脆弱性呈明显的增加趋势。河南省是中国粮食生产核心区,首先要依靠科技创新,大力发展节水农业、循环农业;其次要重视水资源的节约与保护、加大农业投入以降低干旱的脆弱性,确保粮食安全。     

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.     

气候变化情景下流苏香竹潜在分布区预测

流苏香竹（Chimonocalamus fimbriatus）是云南特有珍稀竹种，主要分布于云南西南部。文章以野外调查获取的流苏香竹分布信息为主，运用最大熵模型（MaxEnt）同时结合地理信息系统（ArcGIS），基于19个气候因子，预测其在当前及未来气候变化情景下的潜在分布区。结果表明：当前流苏香竹的高适生区和中适生区主要分布于德宏州、保山市和临沧市等地，除迪庆州、丽江市和昭通市外，云南其他区域均有低适生区零星分布。在未来2050s和2070s的2个时间段，基于2种不同共享社会经济路径（SSP1-2.6和SSP5-8.5），流苏香竹的高适生区面积呈减少的趋势，尤其是SSP5-8.5路径下，高适生区面积仅为当前的12.51%（2050s）和18.63%（2070s）；中、低适生区在SSP1-2.6路径下，显著扩张（2050s）或略微扩张（2070s），在SSP5-8.5路径下，则大幅收缩。流苏香竹野外实际分布区及其潜在分布区均以斑块状为主，可能与云南特殊的地形、地貌有关。影响流苏香竹分布的主导气候因子为最湿月份降水量、最暖月份最高温度、最干季度降水量和平均气温日较差。流苏香竹对气候变化比较敏感，根据其野外分布状况，建议以就地保护为主、迁地保护为辅，在其潜在适生区内适当引种栽培。     

Root distribution patterns of peanut genotypes with different drought resistance levels under early‐season drought stress

Drought severely limits crop yield of peanut. Yet cultivars with enhanced root development enable the exploration of a greater volume of soil for water and nutrients, helping the plant survive. Root distribution patterns of three genotypes (ICGV 98305, ICGV 98324 and Tifton‐8) were compared when grown in well‐watered rhizoboxes and when grown in rhizoboxes where an early‐season drought was imposed using rain‐exclusion shelters. The treatments were arranged in a completely randomized design with three replications, and the experiment was conducted during two seasons at the Field Crop Research Station of Khon Kaen University, in Khon Kaen, Thailand. The root system of ICGV 98305, when grown under drought, had a significantly higher root length in the 30–110 cm deep soil layers and less roots in the 0–30 cm soil layers when under drought than when grown under well‐watered conditions. Roots of Tifton‐8 had the largest reductions in root length in upper soil layer and reduced in most soil layers. Tifton‐8 grown under drought was smaller than under well‐watered control for all root traits, showing negative response to drought. The peanut genotypes with high root traits in deeper soil layer under early‐season drought might contribute to drought avoidance mechanism.     

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.