Sustainable Agriculture: A Review of Challenges Facing the South African Agricultural Sector

Middelberg, Susanna Levina

doi:10.1080/09709274.2013.11906590

Cited by 12 publications

(5 citation statements)

References 2 publications

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“…The drivers for the transition to a circular economy is the challenge faced by the global agricultural food production, as well as the estimated population increase of 9.6 billion (UN, 2017) by 2050 putting global agriculture under a large amount of pressure due to decreasing arable land, rising urbanization, and extreme climatic conditions due to global warming. Thus, producers are pressurized to increase crop yields using environmentally friendly agricultural practices, while perceiving natural resources and feeding a growing population [4]. However, in order to meet the expectations of the circular economy, innovative and modern technology that allows for the recovery of valuable materials should be established [5,6].…”

Section: Introductionmentioning

confidence: 99%

Relations between Circular Economic “Principles” and Organic Food Purchasing Behavior in Hungary

et al. 2020

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Because of the climate change and emerging need for an environmentally sustainable production system, circular economic characteristics have come to the front in many studies. There are many challenges in this shift toward a circular value chain. Still, it is unquestionable that the analysis of consumers’ behaviour is crucial, because without their engagement, circular systems cannot work correctly. This article aimed to explore the circular characteristics of consumers’ attitude towards food purchasing in Hungary. Factor and cluster analyses were applied for market segmentation. The question to be answered was the following: “Are there any segments in the Hungarian food market that can be aimed at by different marketing tools to promote circular systems?” The hypothesis was that well-defined segments can be separated, garnering more engagement in the circular value chain in Hungary. We could separate two clusters, in which the members’ opinions were in line with the circular economic characteristics. Summing up the features of the different clusters, we can state that the members in cluster 1 (“Information-dependent”) and cluster 3 (“Direct purchasers”) were in the most local dimension; their attitude was the most adequate for the circular economic values. The “Information-dependent” consumer in particular was remarkable from the aspect of this investigation. This study showed that highly educated young people, who are very conscious consumers and live on good incomes, may be the target group for circular innovation. These young consumers usually buy organic food, are confident internet and software users, live in cities, and follow a healthy lifestyle. Finding the right marketing tools to integrate these consumers into more sustainable circular systems effectively and to be committed to the concepts of circular consumption is an essential mission in the future. Collecting from different databases and continuously analysing consumer feedback can be a huge step towards in achieving sustainable consumption and avoiding food waste. The significance of this analysis was that we found a defined segment that represents propensity towards accepting circular economy values and can be the target group of policies integrating circular systems.

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Section: Introductionmentioning

confidence: 99%

Relations between Circular Economic “Principles” and Organic Food Purchasing Behavior in Hungary

et al. 2020

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“…Another significant environmental impact associated with dairy farming is GHG emissions (Food and Agriculture Organization of the United Nations (FAO), 2010;de De Léis et al, 2015). Greenhouse gas emissions are associated with global climate change, which is one of the most significant environmental challenges of this century (Rotz et al, 2010) and a key challenge facing the South African agricultural sector (Middelberg, 2013). The extent and sources of farm GHG emissions resulting from agricultural practices can be measured using a carbon footprint calculator (Food and Agriculture Organization of the United Nations (FAO), 2010; Rotz et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Opportunities to improve sustainability on commercial pasture-based dairy farms by assessing environmental impact

Galloway

Conradie

Prozesky

et al. 2018

Agricultural Systems

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For pasture-based dairy farming to become more sustainable, the negative environmental impacts associated with milk production must be minimized. These negative impacts include eutrophication, ammonia emissions and greenhouse gas (GHG) emissions. Two tools, a nutrient budget and a carbon footprint calculator, allow farmlevel assessments of these negative impacts. In this study, a nutrient budget was used to calculate the efficiency of nitrogen and phosphorous use, and a carbon footprint calculator was used to calculate GHG emissions. Farm system descriptors were used to identify the farm systems that had the lowest environmental impact. Soil carbon was measured as an indicator of soil health, and the link between soil health, nutrient use efficiency and GHG emissions was examined. Nitrogen and phosphorous were not efficiently utilized on the farms included in this study, with a large excess of nutrients imported onto the farms each year. The average use efficiency was 29% for nitrogen, and 36% for phosphorous. The GHG emissions per liter of milk production were higher on the farms included in this study than found in previous studies on dairy farms, with an average of 1.39 kg of carbon dioxide equivalents emitted per kilogram of energy-corrected milk. Farm systems which optimized milk production on the available land, while applying the least amount of fertilizer and feeding the least amount of purchased feeds per milk produced, had the lowest environmental impact. Farms with higher soil carbon levels had higher nitrogen use efficiencies and lower GHG emissions. This is the first South African research to examine environmental impact on pasture-based dairy farms in this manner. It is possible for pasture-based dairy farmers to reduce the environmental impact of milk production by adopting some of the principles identified in this study. conserved forage (roughage). The two farm types employ very different practices and mechanisms to reduce environmental impact and improve efficiency, but comparisons between them are few (Scholtz et al., 2013;O'Brien et al., 2014). The two types are also not always operated

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“…The factors that influence farmers' adaptation behavior are according to the farmers' internal factors such as characteristics, knowledge, perceptions, and external forces such as economy, policy, environmental, and technology (Neufeldt et al, 2013). In addition, influence on adaptation behavior of farmers such as household heads educational attainment, farming experience, land size, perception of climate change impacts, knowledge and skills, the stability of farm productivity, soil protection strategies, income, access to the information, access to the market, extension services, crop diversity, livestock production, institutional, policy and technical support are found to be the factors influencing the adaptation behavior of CSA technologies (Middelberg, 2013). In a Sri Lankan context, insufficient resources, limited marketing options have been highlighted as reasons for poor adaptation although these impacts have never been quantified (World Bank CIAT, 2015).…”

Section: Factors Influencing the Adaptation Behavior Of Csa Technologiesmentioning

confidence: 98%

Associated Farm and Farmer-Specific Factors for Climate-Smart Agriculture Adaptation in the Dry Zone: A Case from Vavuniya, Sri Lanka

Yogarajah

Weerasooriya

2020

Sri Lankan J Agric Econ

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Climate-Smart Agriculture (CSA) technologies have been introduced to mitigate adverse climate change impacts. However, the adaptation of CSA technologies by farmers is relatively low in the dry zone of Sri Lanka. This study focuses on how farmers' adaptation behavior for CSA technologies varies with household characteristics, economic status, and farm characteristics. Data on 94 farmers were collected using a pre-tested questionnaire. A score was developed for each farmer on the adaptation of CSA technologies under 4 broad categories namely: water and energy-smart, nutrient and soil-smart, carbon and weather-smart, and knowledge and yieldsmart. A generalized linear model (GLM) was employed to identify the factors that influence farmers' adaptation and the level of adaptation. According to GLM results, income increases the adaptation of water and energy-smart technologies, while land ownership and managing livestock compared to labour decrease the adaptation. Adaptation of nutrient and soil-smart technologies were positively influenced by experience, and training while negatively influenced by labor use and managing livestock compared to crops. Adaptation of carbon and weather-smart technologies were positively influenced by income, cost of transport, higher education levels, managing both crop and livestock compared to only crop, and training while negatively influenced by the gender of the household head and household size, source of income, and land ownership. Knowledge and yield-smart technologies were positively influenced by income, level of education, and training while negatively influenced by only managing livestock compared to crops. Overall, the results suggest the importance of providing training and facilitating knowledge dissemination in addition to understanding the subtle issues that act as barriers to the adaptation of CSA technologies in dry zone farming.

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Sustainable Agriculture: A Review of Challenges Facing the South African Agricultural Sector

Cited by 12 publications

References 2 publications

Relations between Circular Economic “Principles” and Organic Food Purchasing Behavior in Hungary

Relations between Circular Economic “Principles” and Organic Food Purchasing Behavior in Hungary

Opportunities to improve sustainability on commercial pasture-based dairy farms by assessing environmental impact

Associated Farm and Farmer-Specific Factors for Climate-Smart Agriculture Adaptation in the Dry Zone: A Case from Vavuniya, Sri Lanka

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