Search results

During the planting process, agricultural products produce large amounts of greenhouse gas (GHG) emissions. This has placed tremendous pressure on sustainable global development. Many countries and regions in the world have adopted intensive subsistence cultivation methods when planting maize; however, limited studies exist on these methods. The main purpose of this research is to show the impact of climate change on maize yields and carbon footprint (CF) in South Korea over 10 years, find the proper operating method and promote the advanced combination of inputs for the sustainable development of maize farmers.

This study used survey data from the South Korea Rural Development Administration of 2010, 2014 and 2019 to estimate the CF of maize planting under intensive subsistence cultivation. Life-cycle assessment was used to determine the CF. Farmers were grouped according to significant differences in yield and GHG emissions. Linear regression was used to measure the dependence of the main contributors on the CF production and carbon efficiency.

In South Korean maize planting, N in chemical fertiliser was the most significant contributor to the CF and organic fertiliser was the most significant input. The use of chemical and organic fertilisers significantly affects the production of the CF and carbon efficiency. Households in the high-yield and low-GHG emission groups are more sustainable because they generate the least GHG when producing and earning through maize cultivation. Globally, maize production in South Korea has a relatively low CF and maize production produces fewer GHG.

This study provides information for policymakers to determine key operational options for reducing GHG emissions using intensive subsistence cultivation of maize production in South Korea and other countries.

The purpose of this paper is to examine the impacts of farmland renting-in on planted grain acreage.

A survey data of five counties were analyzed with the two-stage ordinary least squares model.

Households renting-in land trended to plant more maize, and the more land was rented by a household the more maize was planted, while wheat acreage showed non-response to farmland renting-in.

Overall, the analysis suggests that policy makers should be prepared for different changing trends of grain crop acreage across the nation as farmland transfer continues. Future research should pay attention to the effect of farmland transfer on agricultural productivity and rural household income growth.

As the Chinese Government is promoting larger-scale and more mechanized farms as a way of protecting grain security, it is important to understand whether farmland renting-in will reduce planted grain acreage. This study provides empirical evidence showing the answer to that question may differ across different regions and depend on the particular grain crop in question.

Constructing a low-carbon agriculture (LCA) park is considered an effective means to reduce greenhouse gas (GHG) emissions in developing countries. This study aims to explore the effectiveness of integrated low-carbon agricultural technologies based on evidence from a pilot LCA experiment in Shanghai, China, from 2008 to 2011.

Integrated low-carbon technologies in an agricultural park were adopted to reduce GHG emissions. Reduced emissions and net economic benefits were calculated by comparing emissions before and after the implementation of the experiment.

Results show that the low-carbon agricultural park experiment markedly reduced GHG emissions. This outcome can be attributed to the integrated technologies adopted in the experiment, including the reuse and recycle of resources, control of environmental pollution and GHG emissions and improvement of economic efficiency and social benefit. All the technologies adopted are already available and mature, thus indicating the great potential of LCA to reduce GHG emissions despite the lack of advanced technologies. However, supporting policies may be necessary to motivate private interests in LCA because of the considerable starting investments.

Previous macro-level and policy studies on LCA are based on knowledge from experimental studies, which typically specify environmental conditions to explore solely the effects of one low-carbon technology. Practically, integrating several low-carbon technologies in one experiment may be more effective, particularly for extensive agriculture, in developing countries. The effectiveness of integrated technologies is insufficiently discussed in the literature. Therefore, this study explores how effective integrated feasible LCA technologies can be in terms of both emission reduction and economic benefits based on the data obtained from an experiment in Shanghai, China.

The purpose of this paper is to contribute to the aforementioned literature on the linkage between economic activity and human preference by estimating the cross-sectional determinants of farmers’ participation in participation in crop insurance programs (CIPs) and identifying the impediments preventing the remaining farmers from participating.

Using the unique data sets of risk preference experiments and maize producer surveys pertaining to the maize production areas of China, this paper explores the determinants of farmers’ CIPs and scrutinizes the role of risk aversion in farmers’ CIP purchase decisions under the expected utility maximization framework. And a “non-zero threshold probit model” is used for the analysis.

The results show that risk aversion plays an important role in CIP purchase decision-making, not only in the form of its direct effect but also with regard to the interaction term and expected loss. Furthermore, if the insured amount is high enough, then risk aversion will no longer affect insurance purchase. Additionally, purchase experience, CIP environment (village purchase ratio), and contract items (insured amounts) are significant determinates in these decisions. There is no significant evidence to suggest that serious adverse selection exists in the sampling areas.

One theoretical model is established which considered not only general variables like farmers’ production and household information, but also conditions and terms in the insurance policies. The unique experimental method is used to measure farmers’ risk aversion. Both the role of risk aversion and its’ interaction terms with others in CIP participation are scrutinized to identify complicated influences under the context of real society.

World agriculture faces enormous challenges in the coming decades. To feed the world adequately in 2050, agricultural production in developing economies will need to nearly double. Incremental production will mainly come from increases in yields or cropping intensities. This chapter focuses on the potential of genetically modified (GM) crops to contribute to agricultural productivity growth and poverty reduction in developing economies. On the basis of a comprehensive literature review of the most recent literature, we aim to shed light on (a) whether GM crops benefit farmers in developing economies and (b) whether GM crops that are currently in the research pipeline address future challenges for agriculture. The first part of the chapter reviews farm-level impacts of GM crops in developing economies. The second part discusses the GM crop research pipeline. GM crop markets are expected to grow in the future but not to change dramatically. We conclude that GM crops benefited farmers, including resource-poor farmers, in developing economies, but benefits are location- and individual-specific. Addressing such complexities will be required to unlock technology potentials.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

The case portrays an actual organization, real people and an authentic marketing situation. Both primary and secondary data were used to develop the case. Interviews with the company’s founders were a major source of primary data. Email exchanges with the company’s leadership were used to verify and elucidate details within the case and instructor’s manual. Other primary data included direct observations of how maize was milled, sold in the marketplaces and cooked into various staple foods. Secondary data about the company were obtained from the company’s website, social media (Facebook, Twitter, Instagram) and articles in the press. Information on the company’s operating environment was derived from published government reports. The authors also drew on secondary data about the statistics, practices and issues involved in maize production and the agro-processing industry in Ghana.

This case features Sahel Grains Ltd, an agro-processing company based in Ghana, West Africa, striving to grow its maiden product, Faast Mmori. This ready-to-cook corn dough provides a more hygienic and convenient way of preparing local meals, compared to the traditional method, which involves taking maize grain to the local mill facilities and paying to have it milled before cooking. Alternatively, consumers purchase corn dough from the markets to make traditional meals. Since the company launched the product in Kumasi in 2018, sales have grown with the augmented street sales promotion and expanded distribution in premium supermarkets such as Shoprite and Citydia. However, starting in November 2020, the sales seemed to plateau with dwindling new customers, and the monthly dough sales in Kumasi dropped for the first time in December 2020. Although the sales regained positive growth, they then started to lose momentum.

In this scenario, Kofi, the CEO and co-founder, is considering marketing strategies to catalyze growth. Students assume the role of Kofi and are asked to recommend growth strategies to move the company forward. In doing so, they must scan the market environment and analyze the product’s market positioning. More importantly, they are challenged to develop strategies for managing growth.

This case is intended for undergraduate students in an introductory course in marketing, management, entrepreneurship and business in general. It introduces students to key marketing concepts, such as market environment scanning, positioning, product life cycle and market growth strategy.

This study aims to explore the grain chain in Kosovo. This study also aims to analyse the role of actors involved in the supply, production, processing, marketing and distribution of the grain value chain.

The study uses qualitative methods. A total of 60 semi-structured interviews are conducted with actors involved in the entire grain value chain.

Findings reveal that the country depends on grain imports and lacks an organised grain market, which is often distorted by the present political situation. Stakeholders are partly integrated in the grain value chain, and they are not very efficient in production. The existence of an informal market influences the decision-making of actors involved in the grain chain. The grain value chain displays mixed governance types, and the relationships among actors are based on the trust mechanism.

The research draws the importance of agriculture’s public policies to sustain domestic grain production. Public–private partnerships should be created to restore the grain market. Trading policies should be revised because they play a crucial role in enhancing fair competition between domestic and foreign traders.

A correlation has been shown in the literature between credit constraints and the adoption of agricultural technologies, technical efficiencies and measures for adapting to climate change. The relationship between credit constraints, risk management strategy adoption and income, however, is not well understood. Consequently, the purpose of this study was to investigate how credit constraints affect the income and risk management practices adopted by Northern Nigerian maize farmers.

Cross-sectional data were collected from 300 maize farmers in Northern Nigeria using a multi-stage sampling technique. Descriptive statistics, seemingly unrelated regression and double hurdle regression models were the analysis methods.

The results showed that friends and relatives, banks, “Adashe”, cooperatives and farmer groups were the main sources of credit in the study area. The findings also revealed that the sources of risk in the study area included production risk, economic risk, financial risk, institutional risk, technological risk and human risk. In addition, the risk management strategies used to mitigate observed risks were fertilizer application, insecticides, planting of disease-resistant varieties, use of herbicides, practising mixed cropping, modern planning, use of management tools as well as making bunds and channels. Furthermore, we found that interest rate, farm size, level of education, gender and marital status were significant determinants of statuses of credit constraints while the age of the farmer, gender, household size, primary occupation, access to extension services and income from maize production affected the choice and intensity of adoption of risk management strategies among the farmers.

The study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers’ income.

The study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers’ income. It therefore recommends that financial service providers should be engaged to design financial products that are tailored to the needs of smallholder farmers in the study area.

This paper incorporates the role of constraints in influencing farmers’ decisions to uptake credits and subsequently their adoption behaviours on risk management strategies. The researcher approached the topic with a state-of-the-art method which allows for obtaining more reliable results and hence more specific contributions to research and practice.