深化种子机构改革,建立数字化品种示范新模式

深化种子机构改革，建立数字化品种示范新模式，引导品种示范走向科学化、规范化，助力农业生产上台阶。     

蛋鸡脂肪肝综合征模型的建立

试验旨在建立蛋鸡脂肪肝综合征病理模型。选取5日龄的海兰褐蛋鸡公雏280只，随机分为对照组（基础日粮组）和3个模型组（A、B、C组），试验第1~10天给模型组饲喂不同配比的高脂饲料，第11~20天饲喂常规基础日粮，每天观察并记录试验鸡精神状态、外观体征、饮水量和食欲情况，试验第0、10、20天从各组随机抽取15只鸡进行翅静脉采血并剖取肝脏和腹脂，测定肝脏系数、肝脂率、腹脂率，血清总胆固醇（TC）、甘油三酯（TG）、谷丙转氨酶（ALT）和谷草转氨酶（AST）水平。结果显示，试验第10天，3个模型组剖检时可见腹腔和肠系膜有大量的脂肪沉积，肝脏系数、肝脂率和腹脂率，以及血清中总胆固醇、甘油三酯、谷丙转氨酶和谷草转氨酶指标均符合鸡脂肪肝综合征模型的诊断标准；试验第20天，模型A、B组谷丙转氨酶和谷草转氨酶水平有所恢复，其他指标仍高于对照组，而模型C组的临床症状和各项检测指标仍符合鸡脂肪肝综合征模型的诊断标准。因此采用连续饲喂高脂饲料C（74.5%基础日粮、6%胆固醇、14%猪油、5%蔗糖、0.5%丙基硫氧嘧啶）可成功建立蛋鸡脂肪肝综合征模型。     

Comparative proteomics analysis of maize (Zea mays) leaves infected by small brown planthopper (Laodelphax striatellus)

Maize rough dwarf disease (MRDD) is a viral disease caused by brown planthopper infestation, and leads to great yield loss, especially in China. Comparative proteomics was performed using maize inbred line Zheng 58 and LN 287. MRDD pathogen was detected as rice black-streaked dwarf virus (RBSDV) by quantitative real time PCR (qRT-PCR) in Shandong Province, China. The modified trichloroacetic acid (TCA)/acetone method was used for soluble protein extraction from leaves. Two-dimensional electrophoresis (2-DE) analysis was performed on 24-cm long, pH 4–7 linear immobilized pH gradient (IPG) strips, and gels were stained with silver and coomassie brilliant blue. We identified 944 proteins expressed in RBSDV infected maize leaves by proteomics approaches. Among these, 44 protein spots that revealed a 1.5-fold difference in intensity were identified by mass spectrometry between mock-inoculated and RBSDV infected samples. Among these, 17 and 26 spots were up-regulated, and 27 and 18 spots were down-regulated in the virus infected samples of Zheng 58 and LN 287, respectively. Differential protein spots were analyzed by mass spectrometry identification, which could be divided into six categories. Furthermore, the expression of stress-related proteins was detected and confirmed by qRT-PCR. This study lays the foundation for further investigations, enabling the enhancement of MRDD resistance in maize.     

Factors determining the adoption of laser land leveling in the irrigated rice–wheat system in Haryana,India

Laser land leveling has been increasingly adopted in the irrigated rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system in the state of Haryana (India), located in the north-western Indo-Gangetic Plains. Still, many farmers have applied it to only a fraction of their land. In this study, we used data collected from 621 farm households in Haryana and applied a double-hurdle model for assessing the factors that determine the adoption and intensity of laser-leveling technology. The results show that large land holders are more likely to laser level their farm land; however, we found a negative association between land holdings and the proportion of laser-leveled land. Information about technology through farmer-to-farmer communication and through private traders, participation in agricultural training and membership in local agricultural institutions increased both the likelihood and the intensity of adoption. Our findings call for a closer collaboration among the various stakeholders, specifically to promote farmer-to-farmer communication through increased participation in local institutions and increase the rate of adoption of laser leveling technology.     

苏粳815机插高产形成特点及其配套精确定量栽培技术

通过综合高产试验和机插行株距规格与氮肥组合试验,分析了苏粳815高产形成的特点,明确了其高产产量结构及其形成的主要生育指标,提出了目标产量650~700 kg/667 m~2相配套的精确定量栽培技术。     

基于PSR模型的黄河陕西段鱼类增殖放流生态安全评价

基于压力、状态、响应模型(PSR)和层次分析法(AHP),确定17项指标通过数据的标准化处理,指标权重赋值、权重一致性检验、评价等级确定以及评价模型的构建,用生态安全评价黄河陕西段鱼类增殖放流效果,分析生态安全所面临的主要问题。结果表明:黄河陕西段2013年增殖放流生态安全度(ESI)评价等级为Ⅱ级,为良好状态;2014年评价等级为Ⅲ级,处于一般状态;2015年评价等级为Ⅳ级,处于较差状态,属于临界不安全状态以下水平。生态安全形势呈现出逐年下降局势。不安全状态受到影响较大的前3个指标是:黄河径流量变化影响、重要生境保持率和公众资源环境保护意识的影响,3个指标下降值占到下降ESI值的64.93%。其次还受到污水排放达标率、鱼类增殖放流量、政策和管理水平、鱼类生物多样性指数、保护区建设、水质综合污染指数、群落结构等诸多因素影响。研究显示,现阶段增殖放流对黄河生态安全有一定影响,还存在一定提升空间。     

基于启发式Johnson算法优化BP神经网络的水产养殖产量预测模型

针对水产养殖产量预测难的现状,提出一种基于启发式Johnson算法优化的反向传播神经网络(BPNN)的产量预测模型。该模型在传统BP神经网络的基础上,针对网络训练时间长、易陷入局部最优的问题,通过启发式Johnson算法降低输入神经元维度,再结合试凑法确定神经网络隐层个数,构建启发式Johnson反向传播神经网络(HJA-BPNN)学习预测模型。实验结果表明,该模型在山东省对虾海水养殖产量预测中,预测的均方根误差小于传统BP神经网络和GM(1,1),且学习效率相比传统BP神经网络有所提升。研究表明,该学习预测模型在大量历史数据的模型构造上有更大的优势,能够缩短建模时间,同时获得良好的预测效果,为水产养殖产量预测提供了一种可行的新方法。     

Conservation needs for the endangered New Zealand sea lion,Phocarctos hookeri

1. Understanding population size and trend is critical information in species management and conservation. To enable accurate population trend estimates, consistent robust monitoring of a species is essential, particularly for a species such as the New Zealand (NZ) sea lion, Phocarctos hookeri , which has experienced an almost continuous decline in pup production since the late 1990s.
2. This research examines the pup production estimates for all known breeding sites for this species, and using a stage‐structured matrix population model, estimates population size and trend between 1995 and 2015.
3. Overall, it is estimated that 2,316 pups were born in 2015, a decrease of 13% since 1995 and a 27% decline since the highest pup production estimate in 1998. This decline has been driven by the significant decline of 48% at the main breeding area, the Auckland Islands since 1998.
4. Using the stage‐structured matrix population model a total species population size of 11,767 sea lions (95% CrI: 10,790–12,923) was estimated. This is the lowest population size of any sea lion species. Trend data for the Auckland Islands indicated that pup and population numbers have decreased at 1.9% yr^?1 in the last 20 yr, while total species population decline is 0.6% yr^?1.
5. Estimates of population trends for this species have been hindered by inconsistent monitoring at most breeding sites. This study strengthens the growing field of research highlighting the need for consistent long‐term monitoring for the conservation management of endangered species.

     

Finding suitable growth models for turbot (Scophthalmus maximus L.) in aquaculture 1 (length application)

Growth data of two different commercial turbot (Scophthalmus maximus) strains reared in recirculating aquaculture systems were analysed with the aim to determine the most suitable model for turbot. To assess the model performance three different criteria were used: (1) The mean percentage deviation between the estimated length and actual length; (2) the residual standard error with corresponding degrees of freedom and (3) the Akaike information criterion. The analyses were carried out for each strain separately, for sexes within strains and for a pooled data set containing both strains and sexes. We tested a pre‐selection of six models, containing three to four parameters. Models were of monomolecular shape or sigmoid shape with a flexible point of inflection including the special case of monomolecular shape in defined cases of their parameters. The 4‐parametric Schnute model achieved best fit in 62% of all cases and criteria tested, followed by the also 4‐parametric generalized Michaelis–Menten equation in 48% and the 4‐parametric Janoschek model (38%). The von Bertalanffy growth function achieved only 29%, Brody 24% and a new flexible function 19% best fit. In a 1–1000 day growth‐simulation sigmoid shaped curves were produced by the Schnute model in 71% of cases. The Janoschek and the Michaelis–Menten model each produced sigmoid curves in 57% of all cases. This indicates that a flexible 4‐parametric function reflects the growth curve of turbot the best and that this curve is rather sigmoid than monomolecular shaped.