初级生产力的不同测定方法

初级生产力 (ｐｒｉｍａｒｙｐｒｏｄｕｃｔｉｖｉｔｙ) ,即自养生物通过光合作用或化学合成制造有机物的速率。初级生产力包括总初级生产力 (ｇｒｏｓｓｐｒｉｍａｒｙｐｒｏｄｕｃｔｉｖｉｔｙ)和初级生产力 (ｎｅｔｐｒｉｍａｒｙｐｒｏｄｕｃｔｉｖｉｔｙ)。前者是指自养生物生产的有机总碳量 ;后者是总初级生产力扣除自养生物在测定阶段中呼吸消耗掉的量 (沈国英 ,施并章 ,1996 )。初级生产力是食物链的基础环节 ,是反映生态系统生产潜力的基本参数 ,对于水域生态系统而言 ,它不仅决定该系统的溶氧状况 ,还直接或间接地影响其它生物和…     

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。     

Technical efficiency of carp production in Nepal: An application of stochastic frontier production function approach*

Abstract

Modern aquaculture is a relatively new activity among Nepalese farmers and a small contributor to the economy. Given the abundance of water resources and fish species, rising demand for fish, and its high profitability, aquaculture has potential for future expansion if it is given appropriate attention from the government. In Nepal, productivity in aquaculture is much lower compared to other countries in the region, which suggests that there is potential for increased fish production through technological progress and improvement in farm‐level technical efficiency. However, no formal analysis has yet been conducted to assess the productive performance of Nepalese aquaculture and its potential for future improvement. Against this background, this paper examines the technical efficiency and its determinants for a sample of fish pond farms from the Tarai region of the country using a stochastic production frontier involving a model for technical inefficiency effects. The estimated mean technical efficiency is 77%, with intensive farms being more efficient than extensive farms. The adoption of regular fish, water, and feed management activities has a strong positive effect on technical efficiency.     

A review of production frontier analysis for aquaculture management

Abstract

This paper examines recent advances in production economics with special reference to efficiency measurement using production frontiers and its implications for aquaculture management. Compared with agriculture and other industries, the use of production frontiers in aquaculture is still very limited. However, in recent years several frontier applications in aquaculture have appeared in the literature, suggesting potential applications of these techniques in aquaculture. A synopsis of stochastic frontier production function model and data envelopment analysis (DEA), the two most popular approaches to efficiency measurement, is presented, followed by a review of recent frontier studies in shrimp, carp and tilapia production. The paper concludes with a brief discussion of future development and prospects of frontier applications for aquaculture management.     

湘中农区壶天山羊的生产性能及生态养殖技术研究

通过采用测定200只壶天山羊的体尺体重,统计66胎产仔情况、屠宰6只成年羊,将8只成年杂交羊(壶天羊×马头羊)和50只成年壶天羊作对比等办法,从而真实系统地总结了该山羊的各项生产性能.对以"七化四结合"为主要内容的山羊生态养殖关键技术进行了研究,提出了"羊→沼→稻(菜或草)"生产模式和"企业 农户"的经营模式.     

渔业数据失真对两种非平衡剩余产量模型评估结果的影响比较

为了研究渔业数据失真对两种非平衡剩余产量模型评估结果的影响,以南大西洋长鳍金枪鱼渔业产量和单位捕捞努力量渔获量(CPUE)数据作为基础数据,加入5种不同程度[变异系数(CV)=1%、5%、10%、20%和30%]的随机误差,模拟了(1)无数据失真,(2)仅产量数据失真,(3)仅CPUE数据失真,(4)产量和CPUE数据均失真等4种情况。利用基于ASPIC的非平衡剩余产量模型(ASM)和基于贝叶斯状态空间建模方法的非平衡剩余产量模型(BSM)分别评估了最大可持续产量(MSY)、B_(MSY)、F_(MSY)、B_(2011)/B_(MSY)、F2011/F_(MSY)等5种生物学参考点和管理指标。结果显示,在无数据失真情况下,ASM和BSM评估的MSY分别为2.866×10~4 t和2.836×10~4 t,B_(2011)/B_(MSY)分别为1.366和1.324,F2011/F_(MSY)分别为0.627和0.667,均相差不大,表明该渔业目前状态良好,ASM得到了较大的B_(MSY)(31.48×10~4 t)和较小的F_(MSY)(0.091);数据失真对ASM评估的B_(MSY)和F_(MSY)分别产生了严重的过低估计和过高估计,且CPUE数据失真产生的影响要比产量数据失真大;随着随机误差的增大,BSM评估的生物学参考点和管理指标的绝对百分比偏差有增大趋势;与ASM相比,BSM能够更好地处理渔业数据中存在的随机误差,除了MSY以外,BSM评估的生物学参考点和管理指标绝对百分比偏差均要比ASM的评估结果低,尤其是B_(MSY)和F_(MSY)。因此,在使用存在较大随机误差的渔业数据进行资源评估时,BSM具有一定的优势。     

Effect of carbon/nitrogen ratio manipulation in feed supplements on Artemia production and water quality in solar salt ponds in the Mekong Delta,Vietnam

The effect of carbon/nitrogen (C/N) ratio manipulation in feed supplements on Artemia production and water quality was investigated in solar salt ponds in the Mekong Delta, Vietnam. It was assumed that development of bacterial bioflocs through C/N manipulation would improve Artemia production and water quality as demonstrated in freshwater and marine aquaculture. Twelve ponds were used for three treatments and the control, in triplicates. Green water (GW) was supplied to all ponds, with the standard Vietnamese procedure of supplying GW and chicken manure (CM) as the control (C/N 1.8). Treatment ponds were supplemented with tapioca (TAP) as carbon source, combined with either CM, pig manure (PM) or rice bran (RB), with C/N ratios of 7.4, 10.5 or 20.1 respectively. After 6 weeks of culture, no single treatment supported both improved water quality and enhanced Artemia production. Overall, improved water quality was observed at C/N 20.1 and higher Artemia production at C/N 7.4. Although external field factors could have interfered with the set‐up, this is the first study on the effect of C/N manipulation in feed supplements in Artemia pond production systems and provides the basis for development of bacterial bioflocs as a technology to improve water quality and Artemia production.     

我国蓝色粮仓科技创新的发展思路与实施途径

蓝色粮仓建设对保障食物安全、推动经济发展、催生新兴产业、彰显国家权益、改善生态环境以及突破产业瓶颈具有重要意义。在当前科技和产业背景下,如何卓有成效地构建蓝色粮仓已成为社会各界关注的热点。本文明确了蓝色粮仓的概念和特点,分析了蓝色粮仓构建的必要性和可行性,提出了实现渔业产业由大国向强国跨越以及提升科技创新和产业发展能力的总体目标,从聚焦重大需求、构建科技创新链,坚持原创驱动、突破重大科学问题,强化集成示范、支撑产业健康持续发展等方面论述了实施途径,即按照基础研究、重大共性关键技术、典型应用示范全链条布局的要求,坚持生态优先谋划,陆海统筹布局,针对种质创制、健康养殖、资源养护、友好捕捞、流通加工五大产业类型需求,实施良种引领、空间拓展、技术升级、产业示范四大行动,建立智慧养殖、智能捕捞、绿色加工三大体系,满足优质蛋白供给和产业转型升级两大需求,最终构建中国特色的蓝色粮仓。     

中国对虾亲虾的能量代谢研究

本试验测定了中国对虾亲虾在禁食和静息状态下的耗氧率、二氧化碳排出率和氨氮排泄率,研究了它们的呼吸商、氧氮比、能源的化学本质及其消耗量之比。结果表明,体重为85.1±14.8克的亲虾,在水温19～22℃时的耗氧率为0.25±0.08毫克/克·小时,二氧化碳排出率为0.28±0.09毫克/克·小时,氨氮排泄率为8.86±3.53微克/克·小时;亲虾以蛋白质、脂肪和碳水化合物的混台物为能源,其中以蛋白质为主,脂肪次之,碳水化合物的利用最少;亲虾的耗氧率(Y)与体重(W)呈负相关,Y=1.89W~(-1.3),而与性腺发育的影响则相反,性腺发育好的亲虾代谢率高,性腺发育差的亲虾代谢率低。     

广东省水稻生产机械装备水平灰色预测与分析

利用广东省水稻生产主要环节机械装备保有量的历史数据,建立了灰色GM(1,1)预测模型,对2006-2020年广东省水稻生产机械装备水平进行了预测,并参考广东省水稻生产机械化作业水平值,对其预测结果进行了修正,以便能为政府主管部门制定提高水稻生产机械装备水平的政策措施提供参考依据.