鱼类池塘养殖水质管理技术

春末夏初气温逐渐升高，鱼类活动活跃，食欲趋旺，而此时由于天气变化较大，水温常随天气变化而变化，易导致水质突变。因此这段时间是养殖氩类病害和缺氧泛塘多发季节。做好这一阶段鱼类养殖管理工作，直接关系到养殖成本、龟类成活率、养殖产量和经济效益的高低。笔者现根据我县许多养殖户成功经验和结合自己多年从事水产养殖经验，谈谈这一阶段鱼类养殖管理技术及应注意的关键问题，供同行参考。     

锦鲤池塘双茬养殖技术

<正>锦鲤为鲤科鱼类,是既可观赏又可食用的大型名贵鱼,被称为"好运鱼"和"风水鱼"。近几年,随着人们生活水平的不断提高,对观赏性鱼类锦鲤的需求量不断加大,使锦鲤的市场价格稳中有升,我们探索出上半年经过90d的时间快速养殖锦鲤,下半年约4     

海蜇的池塘养殖技术

<正> 从2000年起我国开始了海蜇的池塘人工养殖,并取得了一定的经验。现将有关海蜇养殖的技术资料,归纳成文,供养殖户参考。     

池塘养殖鱼类轮捕轮放技术要点

一、捕大留小放养不同规格或相同规格的鱼种,饲养一定时间,分批捕出一部分达到食用规格的鱼类,而让较小的鱼留池继续饲养,不再补放鱼种。二、捕大补小分批捕出食用鱼后,同时补放鱼种或夏花。这种方法的产量较上一种高。补放鱼种,视规格大小和生产的目的,养成大规格鱼种。近年来     

浅水池塘的实用养殖技术

经过几年的池塘养殖．池底淤积越来越严重，特别是广大的农村坑塘本来就不够深，致使许多养殖池塘的水位过浅，养殖空间窄小。这些池塘如果不加以改造整修，养殖环境就会恶化，养殖效率也会降低。但是，在生产过程中，由于受资金、时间、人力等客观条件的限制，及时整修这些浅水池塘而使其达到理想的水深又不太实际。如何使这些浅水池塘发挥作用，以取得较好的生产效益，我们近几年对浅水池塘养殖进行了试验研究，总结出以下几点。     

浅水池塘的实用养殖技术

经过几年的池塘养殖，池底淤泥会越积越严重，特别是广大的农村坑塘本来就不够，致使许多养殖池塘的水位过浅，养殖空间窄小，这些池塘如果不加以改造整修，养殖环境就会恶化，养殖效率也会降低，因此在生产中我们提倡改浅塘为深水塘。在生产过程中，受资金、时间、人力等客观条件的限制，不能及时整修的浅水池塘，     

丁鱥池塘高产养殖试验

丁鱥鱼属鲤科鱼类，主要分布于北冰洋区以外的欧洲平原河川和湖泊中，在我国仅分布于额尔齐斯河流域。丁鱥鱼具有肉质细嫩，味道鲜美，营养价值高，适应水温范围广，耐低氧，食性杂，易驯化等优点，正逐渐成为我国池塘养殖的优良品种之一。为了探索该鱼的池塘养殖技术，我们于2004年～2005年开展了丁鱥鱼的池塘高产养殖试验，项目实施两年来，取得了较好的成效，现将项目2005年度的试验情况总结如下：     

白斑狗鱼的池塘养殖技术

白斑狗鱼隶属鲑形目，狗鱼亚目，狗鱼科。在自然条件下生活于寒冷地带的河流、湖泊中，为亚冷水性鱼类。适宜生长的温度为0～30℃，最适生长温度为20～23℃。体色银灰色，体表较均匀分布淡蓝色白斑。体细长，稍侧扁，尾柄短小、头尖，吻部特长而扁平似鸭嘴，口裂极宽大。鳞细小，侧线不明显。该品种是当前非常受消费者欢迎的优质经济鱼类。为开发利用这一优良品种，2006年5月，郯城县渔技站从新疆引入一批白斑狗鱼进行试养，获得初步成功。现将有关情况总结如下：     

鳜鱼 池塘健康养殖技术

<正>鳜鱼属名贵的经济鱼类,但由于受饲料鱼的制约,难以获得较高的单产,即使采用4:1的饲料鱼与主养鳜鱼池塘配比,存在养殖     

池塘养殖鲈鱼技术要点

鲈鱼，又名四鳃鱼、真鲈，是近岸浅海肉食性鱼类，喜栖息河口淡水处，亦可生活于淡水中，是黄河三角洲地区重要的养殖品种。鲈鱼不仅味道鲜美，而且营养丰富，风味极佳，是我国四大名鱼之一。鲈鱼的池塘养殖，时间短、见效快，此项养殖技术正在大面积推广。     

Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach

The pig meat production plays a significant role in the Spanish agrofood system. The assessment of the efficiency performance with which farmers are operating is necessary to define adequate policy and management strategies. In this context, this study aimed to determine the technical efficiency (TE) performance of pig farms and to examine the key factors that may affect the production system in Spain. To do so, the analysis relies on the quantile stochastic frontier model using a sample of Spanish pig farms. Results show a significant difference between production frontier parameters across the selected quantiles, which support the relevance of using the quantile regression approach. The optimal quantile for the stochastic frontier indicates an average TE level of 75%. In addition, empirical findings suggest that pig farmers in Spain give more importance to the adoption of high technology to improve their economic and technical performance as well as their competitiveness at the European pig market.     

Sawmill production in the interior of British Columbia: A stochastic ray frontier approach

We examined the productive efficiency of the interior sawmilling industry in British Columbia using stochastic frontier analysis. Prior sawmilling studies using this method have neglected the multi-output nature of sawmills. To accommodate both lumber and chips as outputs, we used a ray production function and adopted it into the stochastic frontier framework. A translog functional form was specified with three inputs (i.e., capital, labour, and roundwood) and applied to five years (2003–2007) of mill specific production data. The ray production function is flexible allowing factor productivity to vary with the output mix. Results indicated the presence of both economies of scale and technical inefficiency. This suggested that a long-run equilibrium had not yet been reached during this time and might explain recent restructuring occurring in this region.     

Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms

This article uses panel data estimation techniques to examinetechnical efficiency of individual dairy farms in northern Germany.To the extent that agricultural production is characterisedby heterogeneous production conditions, estimation techniquesthat do not account for unobserved heterogeneity produce biasedefficiency estimates. We therefore estimate a number of conventionalpanel data models and Greene's recently proposed ‘true’random-effects model, as well as an extension of the model toascertain the effects of different specification on the productionfunction and efficiency estimates. Our results appear to supporttheoretical expectations and previous findings according towhich a specification that is both time-variant and also controlscorrelations between unobserved heterogeneity and the explanatoryvariables avoids heterogeneity bias and thus ensures consistentefficiency estimates.     

Efficiency and technical progress in traditional and modern agriculture: evidence from rice production in China

Productive efficiency for Chinese hybrid and conventional rice production is estimated using a dual stochastic frontier efficiency decomposition model. Results reveal significant differences in technical and allocative efficiency between conventional and hybrid rice production, and indicate significant regional efficiency differences in hybrid rice production, but not in conventional rice production.     

Technical efficiency in the Spanish agrofood industry

This study estimates frontier production functions with cross-section data lor the Spanish agrofood industry by using deterministic and stochastic parameuic approaches. We compute the individual technical efficiency for each firm, compare the results and explain the relationship between technical efficiency and other relevant quantitative variables. The results indicate that the Spanish agrofood industry has a level of efficiency between 68% and 93%; which means that it is potentially capable of increasing production without increasing its Consumption of inputs. This efficiency level is positively related to factor productivity and unitary labour costs.     

Stochastic frontier analysis of productive efficiency in China's Forestry Industry

Forest resources are vital to the development of green economics. Given the booming development of China's forestry industry and its ambitious reforestation efforts in the developing world, this paper is the first to use the output distance function to synthetically consider the economic and ecological outputs of China's forestry industry, and discuss its productive efficiency with a stochastic frontier model. Control and environmental variables are incorporated to capture heterogeneity in China's forestry industry, which helps us get an unbiased estimation. The empirical results show that there was no obvious efficiency disparity among China's economic regions except Northeastern China, and the state-owned forestry structure has a significantly negative effect on productive efficiency in China's forestry industry. Moreover, provinces with poor productive performance in the forestry industry such as Inner-Mongolia, Heilongjiang, and Hebei have been identified and their individual characteristics regarding productive efficiency have also been analyzed. The findings in this paper have targeted and practical implications for the development of China's forest green economy.     

Estimation of input-oriented technical efficiency using a nonhomogeneous stochastic production frontier model

Technical inefficiency can be modeled as either input‐oriented (IO) or output‐oriented (OO). However, in the estimation of parametric stochastic production frontier models which use maximum likelihood method only the OO measure is used. In this article we consider a simple nonhomogeneous production function and estimate it with both IO and OO specifications. A sample of 80 Spanish dairy data (1993–1998) is used to estimate both models. We consider one output (liters of milk) and four variable inputs (viz., number of cows, kilograms of concentrates, hectares of land, and labor [measured in man‐equivalent units]). We find that returns to scale (RTS) and technical efficiency results derived from these models are different because either estimated technologies are different, or they are evaluated at different points. Using a Monte Carlo analysis we show that if RTS is close to unity differences in the estimates of RTS and technical efficiency are smaller. This holds true for estimates of both RTS and technical efficiency.     

Off‐farm work,technical efficiency,and rice production risk in Taiwan

This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off‐farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off‐farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off‐farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off‐farm work are more efficient than their counterparts without off‐farm work. In addition, farmers with off‐farm work face higher production risk and this result is robust for the entire distribution.