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This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This paper aims to examine the effects of CO₂ emissions, energy consumption, cultivated area and the labour force on the production of cereal crops in Pakistan from the period 1971-2014.

The study used the Johansen cointegration test, the autoregressive distributed lag (ARDL) approach and Granger causality test to estimate the long-run cointegration and direction of the relationship between the dependent and independent variables.

The outcomes of the Johansen cointegration test confirmed the existence of a long-term cointegrating relationship between the production of cereal crops, CO₂ emissions, energy consumption, cultivated area and the labour force. The results of the long-run coefficients of CO₂ emissions, energy consumption, cultivated area and labour force have a positive impact on cereal crops production. The long-run relationships reveal that a 1 per cent increase in CO₂ emissions, energy consumption, cultivated area and labour force will increase cereal crops production by 0.20, 0.11, 0.56 and 0.74 per cent, respectively. Moreover, the findings show that there is a bidirectional causality running from CO₂ emissions and cultivated area to cereal crops production. Moreover, there is a unidirectional causality running from energy consumption to cereal crops production.

The present study also fills the literature gap for applying the ARDL procedure to examine this relevant issue for Pakistan.

Farmers' adaptation strategies in agricultural production are required to minimise the negative impact of climate change on a nation's food production in developing countries. Based on the panel data of the provincial level in China from 2000 to 2017, this study aims to analyse the changing climate over recent years and farmers' adaptation strategy in terms of cropping in agricultural production.

This study uses Simpson's diversity index (SDI) to measure the degree of crop diversity planted by farmers and evaluate the influence of climate change on farmers' cropping strategy using the fixed-effect model. Further, the authors estimate the impact of farmers' cropping strategy on their economic performances in two aspects including yields and technical efficiency of crops.

The empirical results show that the overall climate appears a warming trend. Different from farmers in some other countries, Chinese farmers tend to adopt a more specialised cropping strategy which can significantly improve the technical efficiency and yields of crops in agriculture. In addition, as a moderating role, the specialised cropping can help farmers to alleviate the negative impact of climate change on technical efficiency of their crops.

First, previous studies showed that the changing climate influenced farmers' adaptation strategies, while most studies focussed on multiple adaptation strategies from the farm-level perspective rather than cropping strategy from the nation-level perspective. Second, the present study investigates how the cropping strategy affects the economic performance (in terms of the technical efficiency and crop yields) of agricultural production. Third, the stochastic frontier analysis method is used to estimate the technical efficiency. Fourth, this study explores the moderating effect between farmers' cropping strategy and technical efficiency by introducing an interaction item of SDI and accumulated temperature.

This paper aims to describe the indigenous and innovative practices adopted by the small-scale farmers to cope with the impacts of climate change hazards on subsistence farming.

The data were collected through focus group discussions with 72 small-scale farmers from a rural community in Limpopo Province, South Africa. The discussions were analysed through verbatim transcripts and content analysis.

The study results show the farmers’ understanding of climate change variability and its hazards in the form of rainfall scarcity and excessively increased temperature, which are responsible for a declining production of indigenous crops. It has also been found that in the face of these hazards, the farmers experience low crop yields, which cannot provide the household food requirements. However, the small-scale farmers use a combination of local and innovative knowledge and skills to improve their crop production. They have adopted the indigenous adaptation mechanisms, which include rainfall prediction, preparation of the gardens, change of crops and the planting season to ensure better crop yields. The farmers also adopted innovative adaptation practices such as the use of fertilisers, growing of exotic crops and use of extension officers’ guidance and skills to minimise the risks and maximise the chances of resilient crop production.

This paper describes the farmers’ ability to use the indigenous and innovative adaptation practices. It is only focused on the farmers’ knowledge and skills other than the extension officers’ skills.

The adaptation practices reported in the study fall within the adaptation and mitigation systems stipulated in the South African National Climate Change Strategy to assist the small-scale farmers grow and maintain the crops to improve production and minimise the risks, thus ensuring food security under observable harsh climate hazards.

This study aims to examine the effect of climate variability on smallholders’ crop income and the determinants of indigenous adaptation strategies in three districts (Mieso, Goba-koricha and Doba) of West Hararghe Zone of Ethiopia. These three districts are located in high-moisture-stress areas because of crop season rainfall variability.

Primary data collected from 400 sample households were used for identifying factors that affect households’ crop income. The study used ordinary least square (OLS) regression to examine the effect of climate variability. Given this, binary logit model was used to assess smallholders’ adaptation behavior. Finally, the study used multinomial logistic regression to identify determinants of smallholders’ indigenous adaptation strategies.

The OLS regression result shows that variability in rainfall during the cropping season has a significant and negative effect, and cropland and livestock level have a positive effect on farmers’ crop income. The multinomial logistic regression result reveals that households adopt hybrid crops (maize and sorghum) and dry-sowing adaptation strategies if there is shortage during the cropping season. Variability in rainfall at the time of sowing and the growing are main factors in the area’s crop production. Cropland increment has positive and significant effect on employing each adaptation strategy. The probability of adopting techniques such as water harvesting, hybrid seeds and dry sowing significantly reduces if a household has a large livestock.

The three districts are remote and accessibility is difficult without due support from institutions. Thus, this study was conducted on the basis of the primary data collected by the researchers after securing grant from Swedish International Development Agency (SIDA).

The purpose of this paper is to explore the economic performance of Norwegian crop farms using a stochastic frontier analysis.

The analysis was based on a translog cost function and unbalanced farm-level panel data for 1991–2013 from 455 Norwegian farms specialized in crop production in eastern and central regions of Norway.

The results of the analysis show that the mean efficiency was about 78–81 percent. Farm management practices and socioeconomic factors were shown to significantly affect the economic performance of Norwegian crop farms.

Farmers are getting different types of support from the government and the study does not account for the different effects of different kinds of subsidy on cost efficiency. Different subsidies might have different effects on farm performance. To get more informative and useful results, it would be necessary to repeat the analysis with less aggregated data on subsidy payments.

One implication for farmers (and their advisers) is that many of them are less efficient than the estimated benchmark (best performing farms). Thus, those lagging behind the best performing farms need to look at the way they are operating and to seek out ways to save costs or increase crop production. Perhaps there are things for lagging farmers to learn from their more productive farming neighbors. For instance, those farmers not practicing crop rotation might be well advised to try that practice.

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize farmers appear to bring some benefits in terms of more efficient production that, in turn, increase the supply of some foods so possibly making food prices more affordable.

Unlike previous performance studies in the literature, the authors estimated farm-level economic performance accounting for the contribution of both an important farm management practice and selected socioeconomic factors. Good farm management practices, captured through crop rotation, land tenure, government support and off-farm activities were found to have made a positive and statistically significant contribution to reducing the cost of production on crop-producing farms in the Central and Eastern regions of Norway.

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO₂ emissions, farming areas and the labor force in China.

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

The Johansen test findings have shown that the fruit crop growth, energy use, CO₂ emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO₂ emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO₂ will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO₂ emissions to agricultural areas to fruit crops.

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.

Different livestock production systems contribute to globally Greenhouse gas emission (GHG) emission differently. The aim of this paper is to understand variation in emission in different production systems and it is also important for developing mitigation interventions that work for a specific production system.

In this study, the authors used the Global Livestock Environmental Assessment interactive model (GLEAM-i) to estimate the GHG emission and emission intensity and tested the effectiveness of mitigation strategies from 180 farms under three production systems in northern Ethiopia, namely, pastoral, mixed and urban production systems.

Production systems varied in terms of herd composition, livestock productivity, livestock reproductive parameters and manure management systems, which resulted in difference in total GHG emission. Methane (82.77%) was the largest contributor followed by carbon dioxide (13.40%) and nitrous oxide (3.83%). While both total carbon dioxide and methane were significantly higher (p < 0.05) in urban production system than the other systems emission intensities of cow’s milk and goat and sheep’s meat were lower in urban systems. Improvement in feed, manure management and herd parameters resulted in reduction of total GHG emission by 30, 29 and 21% in pastoral, mixed and urban production systems, respectively.

This study is a first time comparison of the GHG emission production by various production systems in northern Ethiopia. Moreover, it uses the GLEAM-i program for the first time in the ex ante settings for measuring and comparing emissions as well as for developing mitigation scenarios. By doing so, it provides information on the various livestock production system properties that contribute to the increase or decrease in GHG emission and helps in developing guidelines for low emission livestock production systems.

This study aims to examine determinants of farmers’ use of climate-smart agricultural practices, specifically improved crop varieties, intercropping, improved livestock breeds and rainwater harvesting in Wadla district, northeast Ethiopia.

A cross-sectional household survey was used. A structured interview schedule for respondent households and checklists for key informants and focus group discussants were used. This study used both descriptive statistics and a multivariate probit econometric model to analyze the collected data. The model was used to compute factors influencing the use of climate-smart agricultural practices in the study area.

The results revealed that households adopted selected practices. The likelihood of farmers’ decisions to use improved crop varieties, intercropping, improved livestock breeds and rainwater harvesting was 85%, 52%, 69% and 59%, respectively. The joint probability of using these climate-smart agricultural practices was 23.7%. The model results confirmed that sex, level of education, livestock holding, access to credit, farm distance, market distance and training were significant factors that affected the use of climate-smart agricultural practices in the study area.

The present study used the most selected locally practiced interventions for climate-smart agriculture.

This paper is designed to assess the sustainable value chain approaches for marketing channel development opportunities for agricultural products in coastal Bangladesh to combat climate change through an approach of community-based adaptation options.

The study was designed to select the potential value chain candidate and to analyze and establish a value chain map to benefit the crop farmers. In this connection, the resources of the whole context were evaluated. The approach uses few tools to generate three outputs, the last of which are the final list of value chains selected for in-depth assessment to design interventions as community-based adaptation practices of the study to combat climate change in the study areas.

The study demonstrated that the difference in the institutional circumstances of the end markets of the agriculture products is connected to the different categories of harmonization and control of the facilitating environment throughout the supply chains. National and local networks improve the value chain in terms of the value addition of the agriculture products, technology improvement, market access and profitability of the products. Strengthening the weak financial structure, focus more on formal financial systems and resolving sociocultural and climate change-induced hazard concerns are the major concerns on the development of value chains in the countries. Apparently, guarantee for good governance, checking illegal and unregulated market contexts, proper mitigation measures to climate change are some paramount important issues for the sustainable management of livelihood, yield, income and development.

All kinds of stakeholders of the agriculture product value chain should focus on competitiveness and productivity and look for and exploit multiple ways to add value once initial success has been attained with a single deal. Ensuring sustainability within the value chains is an important feature to cater to the challenges and changing demands of the age.

The study will help to established a sustainable value chain approach in response to climate change, which process will help to existent opportunities for firms to manage the issue of climate risk by codeveloping and employing adaptation options that may be more preferred or accepted by consumers across the entire chain for the sustainable management of livelihood, yield, income and development.