Yield and Profitability of Crop Production in Mountain Less Favoured Areas

Klima, K.; Kliszcz, Angelika; Puła, Joanna; Lepiarczyk, A.

doi:10.3390/agronomy10050700

Cited by 17 publications

(20 citation statements)

References 17 publications

(17 reference statements)

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“…This relationship is common in mountain areas. Mountain areas are considered as less favoured due to difficulties caused by short growing seasons, steep slopes at lower altitudes, or by a combination of the two (Council of the European Union, 2013, cited in Klima et al, 2020). Land holdings in high altitudes of mountain areas are limiting the scale of economic activities performed by farmers to increase farm income.…”

Section: Descriptive Statistics and Income Percentile Sharesmentioning

confidence: 99%

“…However, the changes in the montane steppe belt were seen to greatly affect the scale of animal husbandry and the income of herdsmen (ibid). To address the challenges of agricultural production in mountain areas, farmers who are relatively better-off, tend to move along an altitude gradient-to the lowlands (Klima et al, 2020).…”

Section: Descriptive Statistics and Income Percentile Sharesmentioning

confidence: 99%

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Income Inequality in Mountain Areas: The Case of Agroforestry Farming Systems in Uluguru Mountains, Tanzania

Kadigi¹

2021

OJF

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Land degradation due to use of unsustainable agricultural practices has affected many communities in rural mountain areas rendering them to be more vulnerable to income poverty and inequality. In this case, agroforestry systems promise to offer great solutions as they can be developed in unfavourable conditions where other production systems would either rapidly degrade the land or otherwise would not be possible. However, little is known whether agroforestry can address issues of income inequality in mountain areas. Hence, we conducted a study to investigate the nature and determinants of income inequality in Uluguru Mountains, Tanzania. Specifically, we used the cross-sectional research design and we calculated the income percentile shares, Gini coefficients and the coefficient of variation (CV), to pinpoint the nature of income inequality in the study area. The determinants of income inequality were analysed using the step by step multiple linear model. The results of analysis suggested prevalence of income inequality. Crop production was the main source of income in the agroforestry systems of the study area. Earnings from crops and timber were decreasing income-inequality amongst smallholder farmers. Our disaggregated analysis showed that offfarm income was also decreasing income-inequality for farmers with farmlands located close to homestead, for female-headed households, for farmers who did not access extension services, and those who were members of community-based financial institutions. Estimated incomes increased with household assets, size of farmland, and age of household head. However, the same decreased with household size. We found gender disparity to be one of the key issues that need attention in formulating future policies to reduce inequality. We recommend promotion of livelihood diversification as well as the designing and implementation of tailor-made training and farm financing How to cite this paper: Kadigi, R.M.J.

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Section: Descriptive Statistics and Income Percentile Sharesmentioning

confidence: 99%

Section: Descriptive Statistics and Income Percentile Sharesmentioning

confidence: 99%

Income Inequality in Mountain Areas: The Case of Agroforestry Farming Systems in Uluguru Mountains, Tanzania

Kadigi¹

2021

OJF

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“…According to Klima et al [46], soil quality is among the factors affecting agricultural production and is one of the determining factors for the classification of the Areas with Natural Constraints (ANC), formerly referred to as less-favored areas (LFA). For this reason, many authors analyze the economic differences in companies within and outside ANC.…”

Section: Methodsmentioning

confidence: 99%

Organic Food Needs More Land and Direct Energy to Be Produced Compared to Food from Conventional Farming: Empirical Evidence from the Czech Republic

et al. 2021

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This study investigated direct energy consumption and land performance under two different methods of farming—organic and conventional. The aim of our study was to examine the performance of farmers in the Czech Republic and identify the differences between organic and conventional farming regarding food safety and direct energy consumption. Based on the data from the Farm Accountancy Data Network of the EU, we measured the performance of both organic and conventional farmers in terms of product per unit of land and direct energy consumption per unit of product regarding the natural condition of the farm localization. Our findings show that organic farms produce lower output with less direct energy per unit of land; however, they need more direct energy for one unit of production. We found that a product from organic agriculture consumes 1.7-fold greater direct energy than a conventional product. The worse the natural conditions for farming, the broader the difference between organic and conventional regimes regarding their performance and energy consumption. Our conclusions may help shape agricultural policy in the Czech Republic, where organic farming is receiving systematic political support, leading to an increase in the proportion of organically farmed arable land.

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“…Using two-year data of yield, price and costs, they use regression analysis and fuzzy simulation principles for predicting profits. Klima et al (2020) access the impact of subsidies on the yield and profitability of a number of crop types cultivated in a mountainous region of Poland.…”

Section: Methodsmentioning

confidence: 99%

Profit Forecasting in Crop Production: The Case of Gazipaşa

Ersoy¹,

Gümüş²

2021

International Journal of Agriculture Environment and Food Sciences

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Agriculture sector in Turkey is among the largest, employing one out of every five working people. In this study agricultural crop income of Turkey's Gazipaşa district is analyzed. Located on the coast of the Mediterranean, the district's main economy is based on agriculture with 81 different crops currently cultivated in 43 regions. For each crop type, total planted land size, yield, wholesale price and operating costs are determined using the data from Turkish Statistical Institute and the district's Directorate of Agriculture. Crop types are ranked based on their economic returns and top 30 that corresponds to 96.45% of the total agricultural income are determined. Profit forecasts are made for those 30 crop types for each of the next 15 years. Future wholesale prices are forecasted using linear trend projection. The annual agricultural loan interest rate of 7.5% is used to estimate the increase in operating costs. Results show that the annual total profit increases slowly in the next 11 years and then decreases. Moreover, profitability increases only for 18 out of the 30 crop types. Internal rate of return is also found to be 15%. Findings suggest that the current crop diversity is not economically sustainable and a better agricultural production plan is required.

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Yield and Profitability of Crop Production in Mountain Less Favoured Areas

Cited by 17 publications

References 17 publications

Income Inequality in Mountain Areas: The Case of Agroforestry Farming Systems in Uluguru Mountains, Tanzania

Income Inequality in Mountain Areas: The Case of Agroforestry Farming Systems in Uluguru Mountains, Tanzania

Organic Food Needs More Land and Direct Energy to Be Produced Compared to Food from Conventional Farming: Empirical Evidence from the Czech Republic

Profit Forecasting in Crop Production: The Case of Gazipaşa

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