Evaluating input use efficiency in shrimp farming by stochastic production frontier approach

Radhakrishnan, Kalidoss; Sivaraman, Iyemperumal; Krishnan, M.

doi:10.1111/are.14940

Cited by 5 publications

(8 citation statements)

References 49 publications

(65 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, a net profit of USD $ 6736.22 was observed in the present study which is higher than the net return of shrimp farming in Gujarat (Nisar et al, 2021). It is also observed that the cost of seeds, feeds, labours, chemicals, electricity and fuel significantly influenced the overall shrimp farm production as same as reported in another study (Radhakrishnan et al, 2021). The shrimp production heavily relies on farm's access to quality inputs (like seeds and feeds) and infrastructure (like equipment and power supply).…”

Section: Discussionsupporting

confidence: 75%

“…Studies showed that shrimp production was influenced by various characteristics including farm size, the quantity of feed offered to shrimp, days of culture (Radhakrishnan et al, 2021) and stocking density (Engle et al, 2017; Nisar et al, 2021). The size of the pond varies with the type of farming practices, that is, extensive, semi‐intensive and intensive.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Factors determining the economic performance of Litopeneaus vannamei (whiteleg shrimp), aquaculture in Tamil Nadu, India

Durai

Chrispin

Bharathi

et al. 2022

Aquaculture Research

View full text Add to dashboard Cite

Shrimp aquaculture has gained significant attention to meet the animal protein need of the growing world population and is widely cultured in semi-intensive methods around the world including India. Here, we examined the growth performance and enterprise budget of shrimp farming using field-level survey data from 194 farms in Tamil Nadu for successive two crops of a year. An estimated shrimp production was 5880 kg/ha/crop from an average pond size of 2.93 ha and stocking density of 39 numbers m −2 for a culture period of 92 days. Similarly, in terms of feed, a total of 9117 kg/ha/crop was found to be used with an average food conversion ratio of 1.55 kg. An initial capital investment requirement of USD $ 22062.11 was observed.The fixed cost of USD $ 2984.21 and variable cost of USD $ 40685.13 were recorded in the production process of shrimp. The harvested shrimp quantity (5880 kg/ha/crop) generated gross revenue of USD $ 50405.56 ha/yr. The calculated net revenue for the shrimp farms of Tamil Nadu was USD $ 6736.22. The Cobb-Douglas production function results showed that water salinity, culture days, stocking density, quantity of feed used, shrimp harvest size, harvest count, daily weight gain, specific growth rate and survival rate was positively influencing the economic performance of the shrimp but not statistically significant. Whereas, the food conversion ratio statistically negatively influenced the economic performance of shrimp production in Tamil Nadu.

show abstract

Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Factors determining the economic performance of Litopeneaus vannamei (whiteleg shrimp), aquaculture in Tamil Nadu, India

Durai

Chrispin

Bharathi

et al. 2022

Aquaculture Research

View full text Add to dashboard Cite

show abstract

“…Regarding farming efficiency measurement, stochastic frontier analysis (SFA) is a widely applied methodology in many aquaculture studies of developing countries in the last decade (Alam, Guttormsen, & Roll, 2019; Alam, Khan, & Anwaru Huq, 2012; Asamoah, Nunoo, Osei‐Asare, Addo, & Sumaila, 2012; Folorunso et al, 2021; Begum, Hossain, Tsiouni, & Papanagiotou, 2015; Begum, Hossain, & Papanagiotou, 2013; Bimbao, Paraguas, Dey, & Eknath, 2000; Bukenya, Hyuha, Molnar, & Twinamasiko, 2013; Dey, Paraguas, Bimbao, & Regaspi, 2000; Dey et al, 2005; Ghee‐Thean, Islam, & Ismail, 2016; Hukom, Nielsen, Asmild, & Nielsen, 2020; Irz & Victoria, 2003; Islam, Tai, & Kusairi, 2016; Kareem, Aromolaran, & Dipeolu, 2009; Kumar, Birthal, & Badruddin, 2004; Kumaran et al, 2017; Le, Le, & Nguyen, 2020; Nagothu et al, 2012; Ogundari, 2014; Ogundari & Aklnbogun, 2010; Radhakrishnan, Sivaraman, & Krishnan, 2021; Sadika, Siegfried, Madan, Nazmul, & Puran, 2012; Sharma & Leung, 2000a, 2000b; Singh, 2008; Singh, Dey, Rabbani, Sudhakaran, & Thapa, 2009; Yuan, Yuan, Dai, Zhang, & Gong, 2019). There are some efficiency studies of Vietnamese aquaculture, such as Dey et al (2000, 2005), Dey, Kamaruddin, Paraguas, and Bhatta (2006), Folorunso et al (2021), Long, Van Thap, Hoai, and Thuy (2020), Nguyen et al (2020), and Nguyen and Fisher (2014), but very few that include the impact of climate change (see however Folorunso et al (2021) and Nguyen et al (2018, 2020) for catfish and shrimp aquaculture).…”

Section: Introductionmentioning

confidence: 99%

“…Ghee-Thean, Islam, & Ismail, 2016;Hukom, Nielsen, Asmild, & Nielsen, 2020;Irz & Victoria, 2003;Islam, Tai, & Kusairi, 2016;Kareem, Aromolaran, & Dipeolu, 2009;Kumar, Birthal, & Badruddin, 2004;Kumaran et al, 2017;Le, Le, & Nguyen, 2020;Nagothu et al, 2012;Ogundari, 2014;Ogundari & Aklnbogun, 2010;Radhakrishnan, Sivaraman, & Krishnan, 2021;Sadika, Siegfried, Madan, Nazmul, & Puran, 2012;Sharma & Leung, 2000a, 2000bSingh, 2008;Singh, Dey, Rabbani, Sudhakaran, & Thapa, 2009;Yuan, Yuan, Dai, Zhang, & Gong, 2019). There are some efficiency studies of Vietnamese aquaculture, such as Dey et al (2000Dey et al ( , 2005, Dey, Kamaruddin, Paraguas, and Bhatta (2006), Folorunso et al (2021), Long, Van Thap, Hoai, and Thuy (2020), Nguyen et al (2020), and Nguyen and Fisher (2014), but very few that include the impact of climate change (see however Folorunso et al (2021) and Nguyen et al (2018Nguyen et al ( , 2020 for catfish and shrimp aquaculture).…”

mentioning

confidence: 99%

Determinants of inefficiency in shrimp aquaculture under environmental impacts: Comparing shrimp production systems in the Mekong, Vietnam

Hestvik

Armstrong

et al. 2022

J World Aquaculture Soc

View full text Add to dashboard Cite

Shrimp aquaculture systems vary from primitive (extensive/ improved extensive) to more industrialized (intensive/semiintensive) farms, and the impacts of environmental shocks may differ between them. This article applies the Cobb-Douglas stochastic production frontier function to evaluate the determinants that impact the inefficiency of these intensive and extensive systems in Vietnam. Data is from a survey of 436 white-leg shrimp (Litopenaeus vannamei) farms in the Mekong Area. Our findings show that farmers with self-reported experiences of drought have higher production efficiency, while experiences of irregular weather reduce efficiency. In addition, education and feeding practice/stocking density adjustment measures increase extensive efficiency. Furthermore, longer crop duration impacts the two systems differently, increasing intensive farm efficiency but decreasing extensive farm efficiency. Interestingly the efficiency effects differ for the two technologies, with two exceptions; efficiency increases for both locations further from the sea and decreases with disease occurrence.

show abstract

“…Radhakrishnan et al [ 27 ] evaluated the input use efficiency of shrimp farming using stochastic product frontier approach. The model was applied to 150 shrimp farmers of India, and the mean efficiency score of 0.95 revealed the high technical efficiency of the farmers.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of profitability and resource use efficiency between Penaeus monodon and Litopenaeus vannamei in India

Nisar

Zhang²,

Navghan

et al. 2021

PLoS ONE

View full text Add to dashboard Cite

The study aimed to highlight the profitability and production function analysis of Penaeus monodon and Litopenaeus vannamei in intensified shrimp farms in Gujarat (India). Two hundred and twenty (220) shrimp farm households were used to identify (principal component and cluster analyses) 8 clusters of management practices that reflected various scales of production intensity ranging from 0–2999 kg/ha/crop to 9000kg/ha/crop and above for both the species. The Cobb-Douglas production function, which relates production output to several independent input variables, was used to determine productivity. The budgeting analysis for both the species showed that more intensively managed farms performed more than the less intensive farm. Empirical results show feed as most significant input for Penaeus monodon and Litopenaeus vannamei seed and labor that affected production. Average net returns/ha/year for Penaeus monodon was $16313.13 and for Litopenaeus vannamei $41640.99. Aquaculture exhibited decreasing returns to scale for both the species and estimates on resource use efficiency revealed that in Penaeus monodon the resources were economically utilized and in case of Litopenaeus vannamei the output was likely to increase if more of seed and less of labor would have been used. The major constraint for the shrimp farmers was diseases which can be mitigated by optimum stocking densities and proper feed management.

show abstract

Evaluating input use efficiency in shrimp farming by stochastic production frontier approach

Cited by 5 publications

References 49 publications

Factors determining the economic performance of Litopeneaus vannamei (whiteleg shrimp), aquaculture in Tamil Nadu, India

Factors determining the economic performance of Litopeneaus vannamei (whiteleg shrimp), aquaculture in Tamil Nadu, India

Determinants of inefficiency in shrimp aquaculture under environmental impacts: Comparing shrimp production systems in the Mekong, Vietnam

Comparative analysis of profitability and resource use efficiency between Penaeus monodon and Litopenaeus vannamei in India

Contact Info

Product

Resources

About