Implementation of an easily reconfigurable dynamic simulator for recirculating aquaculture systems

Methodology of Programmable Process Structures has been implemented and applied for the flexible automatic generation and simulation of Recirculating Aquaculture Systems. First, we implemented and validated the model for a pilot unit, based on short time experiments with Common carp (Cyprinus carpio), utilizing data and functionalities from the literature. Afterwards, starting from this model we generated a hypothetical single tank model of simulated increasing volume, to demonstrate how it supports the simplified, preliminary analysis, design and control of the possible multi-stage systems. We showed that the simulation of a single tank with an appropriately increasing volume makes possible to study the various control strategies, as well as to design the structure and the grading strategy of the multi-stage systems, without an increased combinatorial complexity. In the knowledge of the simulated increasing volume, we determined the volumes of subsequent stages by equidistant partitioning of the rearing time, algorithmically. Considering the available (or planned) tank volumes, this method makes possible to design a multi-stage system that approximately corresponds to the previously optimized single tank model. This conclusion was illustrated by the generation and simulation of the model for the respective multi-stage system.     

基于大型渔业平台的深远海渔业发展现状与思考

基于渔业产业现状,分析国内外在大型渔业平台、深海网箱和养殖工船方面的发展现状,提出“游弋式”养殖工船及深远海渔业的基本概念。受限于投资成本、技术发展水平等客观因素,中国深远海养殖发展速度缓慢,但近年来取得了一定的发展成效。笔者针对现阶段渔业粗放型生产方式的现状,从国家战略、渔业改革和产业需求等角度分析深远海渔业发展的必要性,认为发展以养殖工船为代表的深远海大型渔业平台是实现渔业强国之路的有效途径之一,走出一条符合中国国情的深远海渔业平台的开发之路势在必行。     

Research of dissolved oxygen prediction in recirculating aquaculture systems based on deep belief network

Recirculating aquaculture has received more and more attention because of its high efficiency of treatment and recycling of aquaculture wastewater. The content of dissolved oxygen is an important indicator of control in recirculating aquaculture, its content and dynamic changes have great impact on the healthy growth of fish. However, changes of dissolved oxygen content are affected by many factors, and there is an obvious time lag between control regulation and effects of dissolved oxygen. To ensure the aquaculture production safety, it is necessary to predict the dissolved oxygen content in advance. The prediction model based on deep belief network has been proposed in this paper to realize the dissolved oxygen content prediction. A variational mode decomposition (VMD) data processing method has been adopted to evaluate the original data space, it takes the data which has been decomposed by the VMD as the input of deep belief network (DBN) to realize the prediction. The VMD method can effectively separate and denoise the raw data, highlight the relations among data features, and effectively improve the quality of the neural network input. The proposed model can quickly and accurately predict the dissolved oxygen content in time series, and the prediction performance meets the needs of actual production. When compared with bagging, AdaBoost, decision tree and convolutional neural network, the VMD-DBN model produces higher prediction accuracy and stability.     

EM菌在水产养殖中的应用概述

为了能改善水质、渔业增殖和修复生态环境,EM菌的应用得到了广泛的关注,成为近几年研究的热点。鉴于此,本研究系统梳理了EM菌的定义及来源,综述了国内外近几十年EM菌在水产养殖中的作用效果及其作用机理,阐述了影响EM菌作用效果的因素等;发现EM菌在调控微生物生态结构、降低水环境中有害物质、提高免疫、增重增产等方面有着显著的效果,但EM菌技术的基础理论研究还比较薄弱,且生产技术及应用过程等还存在着不足。因此今后应提高生产技术,建立和提高筛选系统,并开发EM菌在水产养殖研究和应用的新领域,为水产养殖创造更大的经济价值,并为可持续养殖提供可能。     

Sporophytic photosynthesis and gametophytic growth of the kelp Ecklonia stolonifera affected by ocean acidification and warming

Juvenile sporophytes and gametophytes of Ecklonia stolonifera were incubated in combinations of three pCO₂ levels (360, 720 and 980 ppmv) and two temperatures (10 and 15°C for sporophytes; 15 and 20°C for gametophytes) to examine potential effects of climate change on photosynthesis and growth. Sporophytes had significantly higher maximum quantum yields (F_v/F_m) and maximum relative electron transport rates (rETR_max) at 720 ppmv than 360 and 980 ppmv. Also, these parameters were significantly lower at higher temperature of 15°C than at 10°C. Growth of female gametophytes was maximal at 360 ppmv rather than enriched pCO₂ levels. Female gametophytes had significantly lower growth at higher temperature of 20°C than at 15°C. These results indicate effects of elevated pCO₂ varied between generations: stimulating sporophytic photosynthesis and inhibiting gametophytic growth. Ocean acidification and warming would constitute a grave threat to seedling cultivation of E. stolonifera caused by growth inhibition of gametophytes at high pCO₂ levels and temperatures.     

Performance of Mixed Species and Mono‐specific Algal Diets for Culture of Larval Western School Prawns,Metapenaeus dalli

The effect of three mono‐specific and four combinations of the diatoms Chaetoceros muelleri, Chaetoceros calcitrans, and the chlorophyte Tetraselmis suecica on survival, development, and dry weight of the western school prawn, Metapenaeus dalli, was assessed from protozoea I until mysis I. The development and dry weight of larvae were significantly greater when fed diets comprising C. muelleri and/or T. suecica. A fourth diet, consisting of all three microalgal species also performed just as well. Survival alone was a poor measure of the performance of the various diets. Larvae fed with C. calcitrans, either alone or in a mixed diet with either C. muelleri or T. suecica, had significantly slower development and lower dry weight. Overall performance, assessed using the normalized biomass development index, determined that both mono‐specific and mixed diets containing C. muelleri and T. suecica were among the best for M. dalli larvae. These results for M. dalli are consistent with those found for commercially grown penaeid prawns. This study enhances the limited knowledge on the feeding requirements of metapenaeid prawn larvae. Moreover, the results will help improve hatchery methods for the aquaculture‐based enhancement of M. dalli in the Swan‐Canning Estuary and potentially increase the abundance of this iconic recreational species.     

浙江水产养殖环境中铬的形态分析和污染情况调查

本文对浙江省池塘养殖、滩涂养殖、浅海筏式养殖、工厂化养殖和网箱养殖等典型养殖模式 环境中铬的污染情况进行抽样调查，根据本单位开发方法对总铬和有效态铬中的两种价态铬进行测 定。结果表明，我省水产养殖环境中，水质中总铬和毒性较大的Cr6+含量较小，均在《生活饮用水卫 生标准》（0.05mg/L）限量标准以下，未发现超出渔业水质标准的情况。     

淡水养殖环境中氨氧化微生物的研究进展

随着水产养殖业的快速发展,养殖水体氮素污染日益突出,硝化微生物在水产养殖环境氮循环中具有重要作用。本文主要综述我国淡水养殖环境中硝化微生物的多样性、作用机理、厌氧氨氧化过程和机理等研究进展,并展望今后的研究工作:(1)淡水养殖水域硝化作用和氨氧化微生物的时空分布特征及影响因子;(2)淡水养殖环境氨氧化微生物及其他氮素转化关键微生物的过程与机理;(3)深入研究特定生态系统中如池塘生态系统、氮循环的各个过程,构建相关氮素转化和氮素平衡模型,为完善淡水池塘生态系统氮循环理论、水产养殖环境的氮素污染治理和生态修复提供参考。     

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。     

3种填料对集装箱循环水养殖废水处理的初步研究

为探讨聚丙烯塑料发泡材料(EPP)、悬浮球填料和海绵填料对集装箱循环水养殖废水中细菌吸附性能的差异,以及3种填料挂膜启动和挂膜成熟后对氨氮(NH_4~+-N)、亚硝酸盐氮(NO_2~--N)和硝酸盐氮(NO_3~--N)的净水效果,以集装箱循环水养殖废水为研究对象,采用自然挂膜的方式进行了为期3个月的试验,并对相关指标进行测定。结果显示:EPP填料对养殖废水中细菌的吸附能力最好,另外两种填料对细菌的吸附能力次之并且差异不显著(P0.05);3种填料自然挂膜成熟的时间分别为21 d、26 d和30 d;各填料挂膜成熟后处理高浓度NH_4~+-N养殖废水时,NH_4~+-N浓度与NO_2~--N浓度之间的关系可以用多项式y=ax~2+bx+c进行拟合,NH_4~+-N浓度与NO_3~--N浓度之间的关系可以用对数式y=aln(x)+b进行拟合。研究表明:EPP填料、悬浮球填料和海绵填料均可作为生物填料用于集装箱循环水养殖系统。