Performance of smallholder soybean farmers in Ghana; evidence from Upper West Region of Ghana

Asodina, Francis Akabo; Adams, Faizal; Nimoh, Fred; Asante, Bright Owusu; Mensah, Amos

doi:10.1016/j.jafr.2021.100120

“…The significant trends of cowpea, with an average of 0.71 ton/ha and soya bean with a mean of 0.78 ton/ha recorded in Bongo, remained low compared to a potential yield over 2 ton/ha for cowpea [77] or an estimated production of 2.5 ton/ha for soya bean [78]. Intercropping legumes with sorghum, millet, or maize raise soil fertility by fixing atmospheric nitrogen which conserves nutrients for higher productivity of cereals [79]. While sorghum, millet, and cowpea are well-known as climate-resilient crops in the Sudano-Sahelian savannah, tubers, such as sweet potato, attain high prominence in the Guinean zone because of their short-term growth cycle [80].…”

Section: Effects On Agricultural Yieldmentioning

confidence: 99%

Agricultural Yield Responses to Climate Variabilities in West Africa: A Food Supply and Demand Analysis

Schultze,

Kankam,

Sanfo

et al. 2024

Land

4

0

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Agricultural productivity is expected to decrease under changing climate conditions that correspond to the stability of West African food systems. Although numerous studies have evaluated impacts of climate variability on crop yields, many uncertainties are still associated with climate extremes as well as the rapid population growth and corresponding dietary lifestyle. Here, we present a food supply and demand analysis based on the relationship between climate change, crop production, and population growth in three sites from southwestern Burkina Faso to southwestern Ghana. Climate and agricultural time series were analyzed by using boxplots mixed with a Mann–Kendall trend test and Sen’s slope. Food balance sheets were calculated by estimating the demand using a population growth model linked to food supply with local consumption patterns. We found almost insignificant rainfall and temperature trends for both sites in the Sudano-Guinean savannah. Conversely, the climate regime of southwestern Ghana revealed a strong significant increasing temperature over time. Crop yield trends demonstrated that maize and sorghum were significantly enhanced in both study areas of the Sudano-Guinean savannah. Southwestern Ghana depicted a different crop pattern where cassava and plantain showed a strong upward yield trend. The grouped food balance sheets across the regions illustrated a surplus for the Sudano-Guinean savannah while southwestern Ghana exhibited a deficit. Despite the growing yield of various crops, food demand is outpacing regional production.

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“…The significant trends of cowpea with an average of 0.71 ton/ ha and soya bean with a mean of 0.78 ton/ ha recorded in Bongo remained low compared to a potential yield over 2 ton/ ha for cowpea [77] or an estimated production of 2.5 ton/ ha for soya bean [78]. Intercropping legumes with guinea corn, millet or maize will raise soil fertility by fixing atmospheric nitrogen that conserves nutrients for higher productivity of cereals [79]. While guinea corn, millet and cowpea are well-known as climate-resilient crops in the Sudano-Sahelian savannah, tubers such as sweet potato attain high prominence in the Guinean zone because of its short-term growth cycle [80].…”

Section: Effects On Agricultural Yieldmentioning

confidence: 99%

Agricultural Yield Responses to Climate Variabilities in West Africa: A Food Supply and Demand Analysis

Schultze,

Kankam,

Sanfo

et al. 2023

Preprint

0

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Agricultural productivity is expected to decrease under changing climate conditions that correspond to the stability of West African food systems. Although numerous studies evaluated food production gaps or impacts of climate variability on crop yields, many uncertainties are associated with climate extremes, but also rapid population growth and the corresponding dietary lifestyle determine farming activities. Here, we present a food supply and demand analysis based on the relationship between climate change, crop production, as well as population growth in three experimental sites from southwestern Burkina Faso to southwestern Ghana. The method consists of a tiered approach that encompassed a statistical analysis of historical climate as well as agricultural time series using boxplots and a trend test by Mann-Kendall. Food balance sheets were calculated by estimating the demand using a population growth model linked to food supply with local consumption patterns. Results of the boxplot analysis revealed for the majority of climate time series light to strong right-skewed distributions with either a few heavy rainfall or hot temperature events. We found almost insignificant rainfall and temperature trends for both sites in the Sudano-Guinean savannah. The rainfall regime of southwestern Ghana indicated an insignificant upward or downward trend while the temperature significantly increased over time. Crop yield boxplots demonstrated mainly right-skewed distributions for cereals, legumes and tubers as well as cash crops such as cotton. Backed by the Mann-Kendall test, maize and sorghum significantly enhanced in both study areas of the Sudano-Guinean savannah. Southwestern Ghana depicted a different crop pattern where cassava and plantain showed a strong upward trend at a confidence level of 1%. The grouped food balances sheets across the regions illustrated a surplus for the Sudano-Guinean savannah ranging from 221.2 megatons (Mt) to 4,846.77 Mt while southwestern Ghana exhibited a deficit between -193.33 Mt and -16,188.82 Mt. Despite a growing yield of various crops, food demand outpaces the regional production. Hence, it is recommended to focus on a larger array of commodities, imports and marketing of farm products.

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“…For soybean varieties, some scholars use the super-logarithmic stochastic frontier model to measure the efficiency. Otitoju and Arene [22] measured the technical efficiency of soybean production in Benue State, Nigeria as 0.73, and Asodina et al [23] measured 0.58 in Upper West Region, Ghana. For wheat varieties, Tuna and Oren [24] used DEA to measure the technical efficiency of wheat production in south-eastern Anatolia, Turkey to be 0.78.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019

Wang

¹

,

Hu

²

2021

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Globally, corn is characterised by high production and high export concentrations, yet the world is experiencing an unprecedented, huge change in this regard. Ensuring the global supply of corn, and thereby the energy and food security of nations has become particularly important. To understand the importance of corn production as an influencing mechanism of global food supplies, the present study researched the corn production of typical farms in major corn-producing and importing countries around the world. I selected the corn input and output data of 18 typical farms in 12 countries from 2012 to 2019, used the data envelopment analysis (DEA) model to calculate the technical efficiency of corn production, and built a tobit model to explore the impact of farming methods, input elements, supporting services, and other factors on efficiency. The study established that the average comprehensive technical efficiency of corn production on a typical farm was 0.863, and the average loss was 13.7%. In addition, it concluded that intensive tillage and conservation tillage have high technical efficiency. It also demonstrated that the proportion of mechanical labour and technical efficiency is in a ‘U’-shaped relationship, among others.

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Performance of smallholder soybean farmers in Ghana; evidence from Upper West Region of Ghana

Cited by 14 publications

References 9 publications

Agricultural Yield Responses to Climate Variabilities in West Africa: A Food Supply and Demand Analysis

Agricultural Yield Responses to Climate Variabilities in West Africa: A Food Supply and Demand Analysis

Agricultural Yield Responses to Climate Variabilities in West Africa: A Food Supply and Demand Analysis

Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019

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