Profitability and Technical Efficiency of Pineapple Production in Ogun State, Nigeria

Balogun, Olubunmi Lawrence; Adewuyi, S. A.; Disu, Olayiwola Raheem; Afodu, John Osagie; Ayo-Bello, Taofeek Ayodeji

doi:10.1080/15538362.2018.1470594

Cited by 16 publications

(18 citation statements)

References 8 publications

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“…Production of pineapple could be increased by increasing human labour cost as the coefficient is significantly positive, the average increase being 0.34% for a 1% increase in human labour cost. Similar findings have been reported by several researches [31,32,33]. Again, Table 2 exhibits that the sigma square (0.052) of the estimated model is statistically significant at 1% level of probability.…”

Section: Empirical Results Of the Stochastic Production Frontier Modelsupporting

confidence: 88%

“…Advisory service rendered to the farmers in general can help farmers to improve their average performance in the overall farming operation as the service widens the household's knowledge with regard to the use of improved agricultural inputs and agricultural technologies. This result is also similar to those obtained by [31] and [33].…”

Section: Determinants Of Technical Inefficiency Among Pineapple Farmesupporting

confidence: 92%

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Technical Efficiency Analysis of Pineapple Production at Madhupur Upazila of Tangail District, Bangladesh

Akter

Majumder

Islam

et al. 2020

ARJASS

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The main objective of this study is to analyse the technical efficiency and its determinants of pineapple production at Madhupur upazila of Tangail district in Bangladesh. Cross-section data from a sample of 100 pineapple producers during the 2016-17 cropping season were collected by applying multistage random sampling technique. Farm specific technical efficiency scores were estimated using the Cobb-Douglas stochastic frontier production function approach. Empirical findings show that the estimated technical efficiencies of the sampled farmers’ range from 61.61% to 99.95% with the mean technical efficiency of 91.14%. The result suggests that, on an average, farmers in the study area can potentially increase their productivity by 8.86% through more efficient use of inputs. The estimated stochastic production frontier model indicates that input variables such as area, tillage cost, seedling cost and human labour cost were statistically significant variables to increase the quantity of pineapple production. Technical inefficiency effect model identifies that age of farmers had significant positive, but years of schooling and extension contact had significant negative effect on farmers’ inefficiency. The study therefore recommends that government should focus on the ways of attracting and encouraging the youths as they are more efficient and are likely to be able to properly allocate resources and are willing to adopt new technical innovations. Besides, policies and strategies should be directed towards increasing farmers’ formal as well as informal education through the implementation of effective training programmes by the well-trained extension workers.

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Section: Empirical Results Of the Stochastic Production Frontier Modelsupporting

confidence: 88%

Section: Determinants Of Technical Inefficiency Among Pineapple Farmesupporting

confidence: 92%

Technical Efficiency Analysis of Pineapple Production at Madhupur Upazila of Tangail District, Bangladesh

Akter

Majumder

Islam

et al. 2020

ARJASS

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“…The BCR was found as 1.60, which revealed that pineapple production was profitable. The result is similar with Suhaimi and Fatah (2019) and Balogun et al (2018) where the authors declared that being a profitable business, pineapple production could contribute to livelihood improvement of smallholder farmers.…”

Section: Resultssupporting

confidence: 88%

“…Suhaimi and Fatah (2019) conducted a study on pineapple profitability among smallholders in Malaysia and revealed that pineapple production was profitable in the study area with a BCR of 1.72. Similarly, Balogun et al (2018) estimated the pineapple profitability in Ogun State, Nigeria, and found that pineapple production resulted in returning more to the farmers than the original investment in terms of purchased inputs. CDAIS (2018) performed a study on building a public-private pineapple partnership in the Chittagong hill tracts, which resulted in an effective new pineapple grower's association with competent and confident leaders and better-off members.…”

Section: Introductionmentioning

confidence: 99%

Financial profitability and value chain analysis of pineapple in Tangail, Bangladesh

2022

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This study was undertaken to estimate the financial profitability and assess the value chain of pineapple in Madhupur upazila of Tangail, Bangladesh. A total of 100 stakeholders were interviewed randomly using a structured questionnaire to collect primary data. A combination of descriptive, mathematical, and statistical techniques was used to analyze the data. The study depicts that 76.7% farmers used Giant Kew variety for pineapple production. Profitability analysis shows that pineapple production was profitable in the study area. The study reveals that the total value added by the stakeholders to a piece of pineapple was Tk. 38. Among the market actors, wholesalers added the highest value of Tk. 13 per piece (34.2% of total value addition). The study also identified six significant factors, namely, income, farming experience, credit access, market price, labor availability, and lower production of paddy having positive influence on farmers' decision to adopt pineapple production. The study found higher price of inputs, lack of preservation and processing facilities, and lack of operating capital as the major problems for production, value addition, and marketing of pineapple, respectively. The study recommended to ensure reasonable price of the inputs along with better infrastructure, transportation, and processing facilities to overcome the problems. Furthermore, monitoring facilities of government and non‐government organizations should be increased to improve quality of pineapple.

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“…Mango was found to be the least technically efficient crop among the studied, with a mean TE of 0.596±0.11 [52]. Pineapple is the most unpredictable crop among the fruits studied resulting an average TE of 0.67 with a standard error of 0.25 [53][54][55][56][57].…”

Section: Resultsmentioning

confidence: 99%

Meta-analysis of Technical Efficiency in Selected Agricultural Sub-sectors: Implications for Policy Making in Developing Countries like Sri Lanka

Senevirathne

Hettiarachchi

Dilrukshi

et al. 2021

AJRAF

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Aims: To evaluate the technical efficiency (TE) in selected agricultural sub-sectors and to propose possible policy interventions to the government with the aim of reducing the poverty of farmers in the developing world. Study design: A meta-analysis based on empirical studies conducted by various scientists throughout the developing world. Methodology: Research articles for the meta-analysis were selected using a thorough screening process based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) concept. Selected 94 articles were sub-divided in to three main agriculture sub-sectors for detailed analysis; (a) paddy, other field crops-OFC and vegetables, (b) fruits, and (c) livestock. Mean TE of each crop or livestock type was calculated by averaging the TE values for a particular crop or livestock type across different studies included in this study. Results: TE data presented in the original articles showed a considerable dispersion within a given study. The highest mean TE was recorded in B-onion (0.83±0.15) whereas the lowest was recorded in maize (0.703±0.09) and in soybean (0.705±0.13). The TE of chili cultivation was 0.78 with the greatest variability (standard error of mean [SEM] 0.19) among the crops considered, which signifies the unpredictable nature of the chili cultivation. Mango was found to be the least technically efficient crop among the studied, with a mean TE of 0.596±0.11. Dairy, poultry and aquaculture farming operations were found to be highly technically efficient having mean TE values of 0.80±0.16, 0.89±0.02 and 0.88±0.08 respectively. Conclusion: Findings of this study will lead to several key policy implications including, improvement of the socioeconomic characteristics of farmers, implementation of farmer field schools (FFS) and establishment of a cautious and gradual strategy for expansion of the rural financial institutions.

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Profitability and Technical Efficiency of Pineapple Production in Ogun State, Nigeria

Cited by 16 publications

References 8 publications

Technical Efficiency Analysis of Pineapple Production at Madhupur Upazila of Tangail District, Bangladesh

Technical Efficiency Analysis of Pineapple Production at Madhupur Upazila of Tangail District, Bangladesh

Financial profitability and value chain analysis of pineapple in Tangail, Bangladesh

Meta-analysis of Technical Efficiency in Selected Agricultural Sub-sectors: Implications for Policy Making in Developing Countries like Sri Lanka

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