基于线性混合模型的蓝点马鲛叉长和体重关系的月间及性别差异

为了研究蓝点马鲛（）生活史特征的异质性,根据2018年10月至2019年3月在东海外海渔场的拖网调查采样数据,对其叉长和体重关系的月间及性别差异进行了研究。依据收集的367尾蓝点马鲛样本,求得其叉长和体重关系（b的估计均值为2.794。本研究构建了广义线性模型和9个线性混合模型,用于研究蓝点马鲛的叉长和体重关系（）在时间及性别上的差异。贝叶斯信息准则（BIC）值和均方根误差值均表明,最复杂的线性混合模型（即月份和性别对两个参数P<0.01）。在最优模型中,a值则与此相反。本研究表明,月份和性别对蓝点马鲛叉长和体重关系具有显著的影响,线性混合模型能把月份和性别的异质性通过随机效应在单个模型中更准确、快速地体现,从而进一步证实了此模型在数据来源异质性研究中的优势。     

养殖水环境中氮的循环与平衡

养殖水环境中，由于人为的介入和影响。使得水体中氮的各种形态转化和循环过程中发生了改变。笔者详细地介绍了养殖水环境中氮的各种存在形态，及其相互之间的转化和循环过程，同时总结了前人研究和提出的各种养殖水环境中氮的物质平衡模型，为优化水产养殖和保护水环境提供科学依据。     

Plasma levels of vitamin D3 metabolites during parr-smolt transformation of Atlantic salmon Salmo salar L.

Plasma vitamin D and vitamin D metabolites were measured in Atlantic salmon parr during smoltification and after transfer to seawater. The fish were fed commercial feed for 5 months under natural light, and Na⁺/K⁺ ATPase was measured as an indicator of the smoltification status. No significant differences were recorded in the level of plasma vitamin D metabolites. However, a tendency of increasing plasma concentration of 25OHD₃ and also a temporary increase in plasma 1,25(OH)₂D₃ and 24,25(OH)₂D₃ were recorded prior to seawater transfer. The minor changes in plasma levels of the metabolites indicate a role of the vitamin D metabolites during parr–smolt transformation, although we do not know whether the increased levels are caused by increased synthesis of the metabolites or by decreased binding to receptors or decreased excretion.     

基于改进Hough变换的农田作物行快速检测算法

选取苗期农田作为研究对象,采集了包含行栽作物和土壤背景的农田图像,针对现有作物行定位方法易受外界干扰和处理速度较慢的不足,提出将投影法和直接Hough变换法相结合检测作物行的算法.采用2G-R-B 法和OTSU法将图像二值化,通过快速中值滤波算法去除噪声,再利用垂直直方图投影将图像进行水平条划分获取作物垄平均定位点,最后通过Hough变换检测垄定位点,得到作物行中心线.试验结果表明:基于垂直直方图投影的Hough变换检测作物行中心线的算法在保证高定位精度的同时,算法处理速度比直接Hough变换检测法提高了3倍,得到的定位基准线能代表作物行走向.     

Predicting the age of fish using general and generalized linear models of biometric data: A case study of two estuarine finfish from New South Wales, Australia

Direct ageing of fish can be a laborious and expensive task when age estimates from a large population are required, and often involves a degree of subjectivity. This study examined the application of general and generalized linear models that predict the age of fish from a range of efficiently and objectively measured covariates. The data sampled were from yellowfin bream (Acanthopagrus australis (Sparidae) (Owen, 1853)) and sand whiting (Sillago ciliata (Sillaginidae) Cuvier, 1829) populations from New South Wales, Australia. The covariates evaluated in the models were fish length, otolith weight, sex and location (the estuary from which the fish were sampled). Akaike Information Criteria were used for model selection and residual plots of the final models revealed a satisfactory fit to the observations. The best fitting model for each species included all covariates. An additional investigation considered whether general and generalized linear models that predict age from two different categories of biometric information outperform age-length keys with respect to subsequent estimates of total mortality from catch-curve analysis. The two categories of biometric information differed in the ease and cost with which the information could be collected. The first category only included fish length and location as covariates, whilst the second category also included otolith weight and sex. It was found that traditional age-length keys outperformed the predictive models that estimated age from only fish length and location, because the results from the models were prone to significant bias. However, when otolith weight and sex were added as covariates to the predictive models, some of them, including a generalized linear model with a Poisson-distributed response variable, performed similarly to the age-length key. Given that otolith weight and the sex of fish are cheaper to quantify than age from a sectioned otolith in many situations, general or generalized linear models may represent a cheaper and faster method of estimating mortality compared to age-length keys. Such models can also easily incorporate the influence of spatial, temporal and demographic variation.     

Application of the Tweedie distribution to zero-catch data in CPUE analysis

We focus on the zero-catch problem of CPUE (catch per unit effort) standardization. Because the traditional CPUE model with a log-normal error structure cannot be applied in this case, three methods have often been utilized as follows:

(1) Ad hoc method adds a small constant value to all response variables.

(2) Catch model with a Poisson or negative-binomial (NB) error structure.

(3) Delta-type two-step method such as the delta-normal model (after estimating the ratio of zero-catch using a logit or probit model, a model such as CPUE log-normal or Catch-Poisson is applied to CPUE without zero-data).

However, there are some statistical problems with each of these methods.In this paper, we carried out the CPUE standardization mainly using the Tweedie distribution model based on the actual by-catch data (silky shark, Carcharhimus falciformis, in the North Pacific Ocean caught by Japanese training vessels) including many observations with zero-catch (>2/3rd) and tuna fishery data as a target (yellowfin tuna, Thunnus albacares, in the Indian Ocean caught by Japanese commercial vessels) where the ratio of zero-catch is not so high (<1/3rd). The Tweedie model is an extension of compound Poisson model derived from the stochastic process where the weight of the counted objects (i.e., number of fish) has a gamma distribution and has an advantage of handling the zero-catch data in a unified way.We also compared four candidate models, the Catch-NB model, ad hoc method, Delta-lognormal model (delta-type two-step method) and Tweedie distribution, through CPUE analyses of actual fishery data in terms of the statistical performance. Square error and Pearson's correlation coefficient were calculated based on the observed CPUE and the corresponding predicted CPUE using the n-fold cross-validation.As a result, the differences in the trend of CPUE between years and model performance between the ad hoc method and Tweedie model were found to be not so large in the example of yellowfin tuna (target species). However, the statistical performance of Tweedie distribution is rather better than Delta-lognormal model, the Catch-NB distribution and ad hoc method in the example of silky shark (by-catch species). Standardized CPUE year trend of ad hoc method was found to be quite different from that of the Tweedie distribution and other two models. Model performance of the Tweedie distribution is good judging from the 5-fold cross-validation using the fishery data if including many zero-catch data such as by-catch species.     

云南镇雄县金佛山方竹低效林改造效果

金佛山方竹是中国西南地区特有竹种,云南省镇雄县有金佛山方竹林面积为3.23万hm²。多年来,由于竹农过度采笋,而忽视竹林的科学经营,导致大面积竹林低产低效。文章分析了镇雄县金佛山方竹低效林的成因,提出了具体的改造措施,评估了低效林改造效果,以期为提升竹林质量、提高竹林生产力提供技术支撑。     

油菜黑胫病菌T-DNA插入诱变因素优化及突变体筛选

油菜黑胫病是由Leptosphaeria biglobosa引起的一种真菌病害。这种病害在我国油菜产区广泛发生,并造成一定的经济损失。为通过获取突变体来研究L. biglobosa的生态适应性机制及致病机制,本文优化了影响农杆菌介导转化（ATMT）油菜黑胫病菌L. biglobosa菌株Lb731的因素,评估转化子质量,并筛选相关突变体。结果明确了农杆菌介导转化菌株Lb731的最佳因素：潮霉素B浓度为50 μg/mL,转化受体（分生孢子）培养时间为15 d (20℃),浓度为2 × 10^7~8孢子/mL,农杆菌-受体共培养温度为25℃,共培养时间为72 h。在最适条件下的转化效率达到80个转化子/百万分生孢子。T-DNA插入基因组的频率为100%,单拷贝插入频率为72.7%,转化子抗潮霉素性状能稳定遗传。从2136个转化子中获得了11个菌丝生长减缓突变体,7个色素产生缺陷突变体和14个分生孢子产生缺陷突变体,并从这些突变体中鉴定出7个致病力丧失突变体。采用hiTAIL-PCR技术,从3个突变体中获得了T-DNA插入位点侧翼序列。上述结果为深入研究L. biglobosa的生态适应性机制及致病机制提供了材料和线索。     

小球藻遗传转化技术研究进展

小球藻(Chlorella)是一种单细胞真核藻类,属绿藻门、绿藻纲、绿球藻目、小球藻科、小球藻属[1].作为最早开发的真核微藻之一,具有高营养价值、生长快速、结构简单、易工业化集成等显著优点.其细胞形态为球形或椭圆形,直径 3～12μm,呈单生或聚集成群状生长[2],分布广泛,多见于淡水、咸水和土壤中.作为地球上最早的...     

提高甜菜遗传转化频率的研究

以甜菜叶柄为外植体，通过农杆菌介导转化，将玉米胚乳核糖体失活蛋白基因(cRIP)导入甜菜，对影响转化频率的因素：卡那霉素的浓度、头孢霉素的浓度、农杆菌感染时间和浓度等进行了探讨，初步建立了转化频率较高的转化系统．当卡那霉素浓度为100mg／L，头孢霉素浓度为500mg／L，农杆菌浓度OD值为0.3-0．4，感染时间为8～10min时．抗性不定芽分化率可达36．5％。该转化系统为转基因植株的获得奠定了基础。