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Effects of input intensification and cost efficiency on the productivity of irrigated tomato farmers in Kaduna State, Nigeria

Yıl 2024, Cilt: 7 Sayı: 1, 39 - 59, 30.06.2024
https://doi.org/10.54186/arhuss.1351542

Öz

: A ergonomics a diverse range of production-limiting variables ranging from biophysical to agronomic restrictions, as well as socioeconomic and institutional barriers constrained tomato production. It is pertinent to note that Adoption of contemporary agricultural methods is required for optimal productivity under such limits. This study aims to analyze the effect of input intensification and cost efficiency on the productivity of irrigated tomato farmers in Kaduna state, Nigeria. The study used a cross sectional data of 268 irrigated tomato farmers for 2021 cropping season. Descriptive statistics, net farm income, Ordinary Least Square (OLS) regression, Tobit regression model and stochastic frontier cost function were used to analyze the data. The result established that with the net farm income of ₦401,331 ($994.43USD) and return on investment (1.91), tomato production is profitable. The result of OLS regression showed that normalized input intensification (-0.226) is statistically significant at 1% level of probability and is negatively inelastic. This revealed that the input intensification been adopted as a complete package in the study area had negative influence on productivity of tomato. The result of the Tobit model regression showed that the intensity of input use was significantly influenced by the coefficients of age of household head (-0.079), number of extension contact (0.661), farm size (11.257), and distance to input market (0.262). The result of the estimated stochastic frontier cost function showed that costs of labour (0.03), fertilizer (0.35), seed (0.08), agrochemicals (0.06), annual depreciation (0.36) and transportation (0.07) were statistically significant. The inefficiency variables that influenced the cost of the tomato farmers include farm size (0.47), educational status (0.22), access to credit (0.59) and distance to input market (-0.02). The study established that input intensification package adopted by tomato farmers requires modification to enhance tomato productivity in Kaduna state, Nigeria. There is urgent need for training of farmers by extension agent particularly on input intensification, adoption of modern innovations and technologies that could enhance increase output and income.

Destekleyen Kurum

Ahmadu Bello University Zaria Kaduna State Nigeria

Kaynakça

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  • Adedibu, P. A., Opeyemi, A. A., Lawrence, A. L., John Iyanu Paul, J. I., and Oguntoye, E. (2022). Savanna biomes in Nigeria: Indicator species and plant adaptation strategies. ScienceOpen. doi: 10.14293/S2199-1006.1
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  • Ali, A., and Erenstein, O. (2017). Assessing farmer use of climate change adaptation practices and impacts on food security and poverty in Pakistan. Climate Risk Management, 16, 183–194.
  • Alia, D. Y. (2017). Agricultural input intensification, productivity growth, and the transformation of African agriculture, University of Kentucky: 1-170.
  • Al-Mustapha, I. I., and Ashiru, A. A. (2021). Challenges faced by crop farmers: A survey of subsistent farmers in Kwara State, Nigeria. Journal of Agric Sc Food Technol 7(2): 207-211. DOI: 10.17352/2455-815X.
  • Anang, B. T., Amesimeku, J., and Fearon, J. (2021). Drivers of adoption of crop protection and soil fertility management practices among smallholder soybean farmers in Tolon district of Ghana. Elsevier Ltd: 1–7. https://doi.org/10.1016/j.heliyon.2021.e06900.
  • Ayanlere, A. F., Omotesho, O. A., and Muhammad-Lawal, A. (2018). Social capital dimensions and intensity of fertilizer usage among farming households in Kogi State, Nigeria. Applied Tropical Agriculture, 23(1): 17-24.
  • Ayerh F. (2015). Technical efficiency of tomato farmers in the Ashanti region of Ghana. Doctoral dissertation, University of Ghana, Legon
  • Bamiro,O., Adeyonu, A., Ajiboye, O. B., and Solaja, S. (2020). Effects of climate change on grain productivity in Nigeria (1970-2014). IOP conference series. Earth and Environmental science, 445(1):012058
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  • Chepngetich, M., and John, K. (2015). Application of Vector Autoregressive (VAR) Process in Modelling Reshaped Seasonal Univariate Time Series. Science Journal of Applied Mathematics and Statistics. Vol. 3, No. 3, 2015, pp. 124-135. doi: 10.11648/j.sjams.20150303.15
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  • Gollin, D., Parente, S., and Rogerson, R. (2002). The role of agriculture in development. American Economic Review, 92 (2): Pp. 160-164.
  • Hassan, M. H. (2020). Impact of climate change on life. Environmental change and sustainability.
  • Husna, N., and Desiyanti, R. (2016). The analysis of financial performance on net profit margin at the coal company. International Journal of Management and Applied Science, Vol 2, 4, Pp. 2394-7926
  • Ibitoye, S. J., Shaibu, U. M., and Omole, B. (2015). Analysis of resource use efficiency in tomato (Solanum Lycopersicum) production in Kogi state, Nigeria. Asian Journal of Agricultural Extension, Economics and Sociology, 220-229.
  • Jahangirpour, D., and Zibaei, M. (2022). Farmers’ Decision to Adoption of Modern Irrigation Systems Under Risk Condition: Application of Stochastic Efficiency with Respect to a Function Approach. Front. Water 4:931694.
  • Jeetendra, P. A., Jat, M. L., Sapkota, T. B., Khatri-Chhetri, A., Kassie, M., Rahut, D. B., and Maharjan, S. (2018) Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. International Journal of Climate Change Strategies and Management, 10, 3, 407-427.
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  • Kebedom, A., and Ayalew, T. (2012). Analyzing adoption and intensity of use of coffee technology package in Yergacheffe District, Gedeo Zone, SNNP Regional State, Ethiopia. International Journal of Science and Research, vol. 3(10): 1945 – 1951.
  • Kiet, T. H., Thoa, N. T., and Nguyen, P. T. (2020). Applying Cobb-Douglas stochastic frontier profit function: A case study of Hoaloc-Mango in the Mekong Delta, Vietnam. Journal of Sustainable Development and Planning, XI: 493 – 502.
  • Kodde, D. A., and Palm, F. C. (1986). Wald criteria for jointly testing equality and inequality restrictions. Econometrica, 54: 1243-148
  • Koussoube, E., and Nauges, C. (2017). Returns to fertiliser use: Does it pay enough? Some new evidence from Sub-Saharan Africa. European Review of Agricultural Economics, 44(2), 183-210.
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Effects of input intensification and cost efficiency on the productivity of irrigated tomato farmers in Kaduna State, Nigeria

Yıl 2024, Cilt: 7 Sayı: 1, 39 - 59, 30.06.2024
https://doi.org/10.54186/arhuss.1351542

Öz

: A ergonomics a diverse range of production-limiting variables ranging from biophysical to agronomic restrictions, as well as socioeconomic and institutional barriers constrained tomato production. It is pertinent to note that Adoption of contemporary agricultural methods is required for optimal productivity under such limits. This study aims to analyze the effect of input intensification and cost efficiency on the productivity of irrigated tomato farmers in Kaduna state, Nigeria. The study used a cross sectional data of 268 irrigated tomato farmers for 2021 cropping season. Descriptive statistics, net farm income, Ordinary Least Square (OLS) regression, Tobit regression model and stochastic frontier cost function were used to analyze the data. The result established that with the net farm income of ₦401,331 ($994.43USD) and return on investment (1.91), tomato production is profitable. The result of OLS regression showed that normalized input intensification (-0.226) is statistically significant at 1% level of probability and is negatively inelastic. This revealed that the input intensification been adopted as a complete package in the study area had negative influence on productivity of tomato. The result of the Tobit model regression showed that the intensity of input use was significantly influenced by the coefficients of age of household head (-0.079), number of extension contact (0.661), farm size (11.257), and distance to input market (0.262). The result of the estimated stochastic frontier cost function showed that costs of labour (0.03), fertilizer (0.35), seed (0.08), agrochemicals (0.06), annual depreciation (0.36) and transportation (0.07) were statistically significant. The inefficiency variables that influenced the cost of the tomato farmers include farm size (0.47), educational status (0.22), access to credit (0.59) and distance to input market (-0.02). The study established that input intensification package adopted by tomato farmers requires modification to enhance tomato productivity in Kaduna state, Nigeria. There is urgent need for training of farmers by extension agent particularly on input intensification, adoption of modern innovations and technologies that could enhance increase output and income.

Kaynakça

  • Abate, T. M., Dessie, A. B., and Mekie, T. M. (2019). Technical efficiency of smallholder farmers in red pepper production in North Gondar zone Amhara regional state, Ethiopia. Journal of Economic Structures, 8(1), 18.
  • Abaje, I. B., Achiebo, P. J., and Matazu, M. B. (2018). Spatio‐Temporal Analysis of Rainfall Distribution in Kaduna State, Nigeria. Ghana Journal of Geography. Vol. 10(1), pp 1–21
  • Abay, K. A., Berhane, G., Taffesse, A. S., Abay, K., and Koru, B. (2018). Estimating input complementarities with unobserved heterogeneity: Evidence from Ethiopia. Journal of Agricultural Economics, 69, 2, 495–517.
  • Adedibu, P. A., Opeyemi, A. A., Lawrence, A. L., John Iyanu Paul, J. I., and Oguntoye, E. (2022). Savanna biomes in Nigeria: Indicator species and plant adaptation strategies. ScienceOpen. doi: 10.14293/S2199-1006.1
  • Adeola, R. G. (2010). Influence of Socio-Economic Factors on the Adoption of Soil Conservation Measures in Ibadan/Ibarapa Agricultural Zone of Oyo State, Nigeria. Reports and opinion. Vol 2 (7).
  • Akinola, A. A., Arega, D. A., Adeyemo, R., Sanogo, D., Olanrewaju, A.S., Nwoke, C., and Nziguheba, G. (2010). Determinants of adoption and intensity of use of balance nutrient management systems technologies in the northern Guinea savanna of Nigeria. Quarterly Journal of International Agriculture, 49, 1, 25-45.
  • Ali, A., and Erenstein, O. (2017). Assessing farmer use of climate change adaptation practices and impacts on food security and poverty in Pakistan. Climate Risk Management, 16, 183–194.
  • Alia, D. Y. (2017). Agricultural input intensification, productivity growth, and the transformation of African agriculture, University of Kentucky: 1-170.
  • Al-Mustapha, I. I., and Ashiru, A. A. (2021). Challenges faced by crop farmers: A survey of subsistent farmers in Kwara State, Nigeria. Journal of Agric Sc Food Technol 7(2): 207-211. DOI: 10.17352/2455-815X.
  • Anang, B. T., Amesimeku, J., and Fearon, J. (2021). Drivers of adoption of crop protection and soil fertility management practices among smallholder soybean farmers in Tolon district of Ghana. Elsevier Ltd: 1–7. https://doi.org/10.1016/j.heliyon.2021.e06900.
  • Ayanlere, A. F., Omotesho, O. A., and Muhammad-Lawal, A. (2018). Social capital dimensions and intensity of fertilizer usage among farming households in Kogi State, Nigeria. Applied Tropical Agriculture, 23(1): 17-24.
  • Ayerh F. (2015). Technical efficiency of tomato farmers in the Ashanti region of Ghana. Doctoral dissertation, University of Ghana, Legon
  • Bamiro,O., Adeyonu, A., Ajiboye, O. B., and Solaja, S. (2020). Effects of climate change on grain productivity in Nigeria (1970-2014). IOP conference series. Earth and Environmental science, 445(1):012058
  • Burke, W. J., Jayne, T. S., and Black, J. R. (2017). Factors explaining the low and variable profitability of fertilizer application to maize in Zambia, 2017. The Journal of the International Association of Agricultural Economists. Vol 48 (1) Pp 115-126. https://doi.org/10.1111/agec.12299.
  • Chepngetich, M., and John, K. (2015). Application of Vector Autoregressive (VAR) Process in Modelling Reshaped Seasonal Univariate Time Series. Science Journal of Applied Mathematics and Statistics. Vol. 3, No. 3, 2015, pp. 124-135. doi: 10.11648/j.sjams.20150303.15
  • Coelli, T. J. (1996). A guide to FRONTIER VERSION 4.1c. A computer program for stochastic frontier production and cost function estimation, Mimeo, Department of Econometrics, University of New England, Armidale, Australia.
  • Danso-Abbeam, G., Bosiako, J. A., Ehiakpor, D. S., and Mabe, F. N. (2017). Adoption of improved maize variety among farm households in the Northern Region of Ghana. Cogent Economics and Finance, 5(1), 1416896. Degefa, K., Biru, G., and Abebe, G. (2020). Economic efficiency of smallholder farmers in tomato production in BakoTibe District, Oromia Region, Ethiopia. Journal of Agricultural Science and Food. ISSN: 2593-9173 Diagne, A., Alia, D., Amovin-Assagba, E., Wopereis, M. C., Saito, K., and Nakelse, T. (2013). Farmer perceptions of the biophysical constraints to rice production in sub-Saharan Africa, and potential impact of research. Realizing Africa's Rice Promise, 46-68.
  • Diao, X., Hazell, P., and Thurlow, J. (2010). The Role of Agriculture in African Development, World Development, Elsevier, Vol 38, (10), Pp 1375-1383.
  • Evenson, R. E., and D. Gollin, D. (2003). Crop Variety Improvement and Its Effect on Productivity: The Impact of International Agricultural Research. Science, Vol 300, (5620) pp. 758-762
  • Food and Agriculture Corporate Statistical Database Special Report, FAOSTAT (2017). Food and Agriculture Organization of the United Nations Statistical Division, Rome, Italy. 8 pp
  • FAOSTAT, (2020). Food and Agriculture Organization of the United Nations. Production Dataset. http://faostat3.fao
  • Gebregziabher, K. M. (2014). Agricultural extension service and input application intensity: Gebremariam, G., and Tesfaye, W. (2018). The heterogeneous effect of shocks on agricultural innovations adoption: Microeconometric evidence from rural Ethiopia. Food Policy, 74, 154–161.
  • Gollin, D., Parente, S., and Rogerson, R. (2002). The role of agriculture in development. American Economic Review, 92 (2): Pp. 160-164.
  • Hassan, M. H. (2020). Impact of climate change on life. Environmental change and sustainability.
  • Husna, N., and Desiyanti, R. (2016). The analysis of financial performance on net profit margin at the coal company. International Journal of Management and Applied Science, Vol 2, 4, Pp. 2394-7926
  • Ibitoye, S. J., Shaibu, U. M., and Omole, B. (2015). Analysis of resource use efficiency in tomato (Solanum Lycopersicum) production in Kogi state, Nigeria. Asian Journal of Agricultural Extension, Economics and Sociology, 220-229.
  • Jahangirpour, D., and Zibaei, M. (2022). Farmers’ Decision to Adoption of Modern Irrigation Systems Under Risk Condition: Application of Stochastic Efficiency with Respect to a Function Approach. Front. Water 4:931694.
  • Jeetendra, P. A., Jat, M. L., Sapkota, T. B., Khatri-Chhetri, A., Kassie, M., Rahut, D. B., and Maharjan, S. (2018) Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. International Journal of Climate Change Strategies and Management, 10, 3, 407-427.
  • Jenkwe E. D., and Chup C. D. (2016). Analysis of structural soil conservation measures in the Federal Capital Territory, Abuja. Abuja Journal of Geography and Development, 4, 1, 450-465.
  • Jimoh, A. I., Mbaya, A. L., Akande, D., Agaku, D. T., and Haruna, S. (2020). Impact of toposequence on soil properties and classification in Zaria, Kaduna State, northern Guinea Savanna, Nigeria. International Journal of Environmental Quality. Vol. 38: 48-58
  • Kaduna Agriculture Development Agency KADA, (2021). Crop Production Recommendations for Kaduna State. Kaduna Press Ltd. Nigeria, 39 pp.
  • Kaduna Agricultural Development Project. (2014). Agricultural production survey in Kaduna State, Nigeria. Kaminski, J., and Christiaensen, L. (2014). Post-harvest loss in sub-Saharan Africa- what do farmers say? Global Food Security, 3(3), 149-158.
  • Kassie, M., Jaleta, M., Shiferaw, B., Mmbando, F., and Mekuria, M. (2013). Adoption of interrelated sustainable agricultural practices in smallholder systems: Evidence from rural Tanzania. Technological Forecasting and Social Change, 80, 525–540.
  • Kebedom, A., and Ayalew, T. (2012). Analyzing adoption and intensity of use of coffee technology package in Yergacheffe District, Gedeo Zone, SNNP Regional State, Ethiopia. International Journal of Science and Research, vol. 3(10): 1945 – 1951.
  • Kiet, T. H., Thoa, N. T., and Nguyen, P. T. (2020). Applying Cobb-Douglas stochastic frontier profit function: A case study of Hoaloc-Mango in the Mekong Delta, Vietnam. Journal of Sustainable Development and Planning, XI: 493 – 502.
  • Kodde, D. A., and Palm, F. C. (1986). Wald criteria for jointly testing equality and inequality restrictions. Econometrica, 54: 1243-148
  • Koussoube, E., and Nauges, C. (2017). Returns to fertiliser use: Does it pay enough? Some new evidence from Sub-Saharan Africa. European Review of Agricultural Economics, 44(2), 183-210.
  • Levine, K., and Mason, N. (2014). Do input subsidies crowd in or crowd out other soil fertility management practices? Evidence from Zambia. Invited paper presented at the 5th International Conference of the African Association of Agricultural Economists, Addis Ababa, Ethiopia.
  • Mango, N., Siziba, S., and Makate, C. (2017). The impact of adoption of conservation agriculture on smallholder farmers’ food security in semi-arid zones of southern Africa. Agric and Food Security, 6, 32.
  • Marenya, P. P., and Barrett, C. B. (2009). Soil quality and fertilizer use rates among smallholder farmers in Western Kenya. Agricultural Economics, 40(5), 561-572.
  • Matemilola, S., and Elegbede, I. (2017) The Challenges of Food Security in Nigeria. Open Access Library Journal, 4: e4185. https://doi.org/10.4236/oalib.1104185
  • Matsumoto, T., and Yamano, T. (2011). Optimal fertilizer use on maize production in east Africa. In emerging development of agriculture in east Africa: pp. 117-132.
  • McDonald, R. I., Mansur, A. V., Ascensao, F., and Colbert, M. (2020). Research gaps in knowledge of the impact of urban growth biodiversity. Nature sustain. 3, 16-24
  • Melesse, B. (2018). A review of factors affecting adoption of agricultural new technologies in Ethiopia. Journal of Agricultural Science and Food Research, 9(3): 1–4.
  • Mukhtar, U., Mohamed, Z., Shamsuddin, M. N., Sharifuddin, J., and Iliyasu, A. (2018). Application of Data Envelopment Analysis for Technical Efficiency of Smallholder Pearl Millet Farmers in Kano State, Nigeria. Bulgarian Journal of Agricultural Science, 24(2), 213-222.
  • Mutayoba, V., and Ngaruko, D. (2018). Assessing tomato farming and marketing among smallholders in high potential agricultural areas of Tanzania. International Journal of Economics, Commerce and Management, VI, 8, 13.
  • Muyanga, M., and Jayne, T. S. (2014). Effects of rising rural population density on smallholder agriculture in Kenya. Food Policy, 48, 98-113.
  • Mwaura, G. G. (2021). Adoption intensity, perception and profitability of organic based soil fertility management technologies in Murang’a and Tharaka-Nithi Counties, Kenya. A thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Agricultural Economics in the School of Agriculture and Enterprise Development of Kenyatta University, Kenya: 1-106.
  • Najjuma, E. (2016). Techinical Efficiency of Tomato Production: A Comparative Study between Small Scale Green House and Open field tomato farmers in Kiambu. Journal of Agriculture Policy 1, 2(1):16-36. National Bureau of Statistics NBS, (2021). Annual Report. Federal Republic of Nigeria. NBS Publication National Population Commission, (2006). Provisional 2006 Nigeria Census Figures. 3 pp.
  • Nasiru, S. (2022). Policy evaluation of the anchor borrowers programme and smallholder farmers in the Federal Capital Territory, Abuja. Global journal of political science and administration. Vol 10, No. 3, pp 27-41.
  • Nguetti, J. H., Imungi, J. K., Okoth, M. W., Wang’ombe, J., Mbacham, W. F., and Mitema, S. E. (2018). Assessment of the knowledge and use of pesticides by the tomato farmers in Mwea Region, Kenya. African Journal of Agricultural Research, 13(8), 379-388.
  • Oladimeji, Y. U., and Abdulsalam, Z. (2014). An Economic Analysis of Dry Season Irrigated Farming in Asa River, Kwara State, Nigeria: Implications for Poverty Reduction. Journal of Sustainable Development in Africa, 16(7): 1-15.
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  • Yami, M., and Asten, P. V. (2017). Policy support for sustainable crop intensification in Eastern Africa. Journal of rural studies. Vol 55, pp 216-226.
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  • Zondo, B. S. (2020). Determinants of adoption and use intensity of organic fertilizer: A case of smallholder potato farmers in KwaZulu-Natal, South Africa. SA-TIED Working Paper No.135: 1-18
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Tarım Ekonomisi
Bölüm Araştırma Makalesi
Yazarlar

Shalom Bentley 0009-0005-8495-434X

Yusuf Usman Oladimeji 0000-0001-5987-3488

Aderonke Bashirat Mohammed 0000-0002-1118-9385

Aisha Hussaini

Fatima Yisa 0000-0003-0941-1896

Hannatu Usman

Yayımlanma Tarihi 30 Haziran 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 7 Sayı: 1

Kaynak Göster

APA Bentley, S., Oladimeji, Y. U., Mohammed, A. B., Hussaini, A., vd. (2024). Effects of input intensification and cost efficiency on the productivity of irrigated tomato farmers in Kaduna State, Nigeria. Academic Review of Humanities and Social Sciences, 7(1), 39-59. https://doi.org/10.54186/arhuss.1351542

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