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This study aims to propose a comprehensive conceptual framework for the characterization of agricultural heritage in desert-prone areas, with a focus on Siwa Oasis in Egypt.

The research utilizes a multidimensional approach, integrating perspectives from sustainability principles, stakeholders and the agricultural heritage frameworks of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and Food and Agricultural Organization (FAO). It involves thematic analysis of qualitative data collected through focus group discussions and interviews with a diverse range of participants, including community members, government officials, nongovernmental organizations (NGOs) and researchers.

The study identifies five key elements of agricultural heritage in Siwa Oasis: cultural, ecological, economic, social and scientific. Cultural elements include traditional farming practices, irrigation systems and architectural features, while ecological elements encompass crop biodiversity, wildlife habitats and traditional landraces. Economically, date palm cultivation, olive production and agritourism activities play crucial roles in livelihood security and local economies. Socially, community cohesion, gender roles and cultural practices shape the social fabric of the oasis, with festivals and rituals fostering a sense of belonging. From a scientific perspective, the integration of traditional knowledge with modern agricultural practices enhances sustainability and resilience.

The study focused solely on Siwa Oasis as a case study, limiting generalizability to other desert-prone areas. Further research could explore additional regions to enhance the understanding of agricultural heritage in diverse contexts. Additionally, the qualitative nature of the study may limit statistical analysis. Future studies could employ mixed-methods approaches for a more comprehensive understanding of agricultural heritage dynamics.

Understanding the multifaceted aspects of agricultural heritage in Siwa Oasis can inform sustainable development initiatives, tourism planning and cultural preservation efforts. Local policymakers and stakeholders can utilize these insights to develop policies that support traditional farming practices, ecotourism and community development. Furthermore, the promotion of agricultural heritage can enhance economic opportunities, food security and environmental sustainability in desert-prone regions.

Recognition of the social elements embedded within Siwa Oasis’s agricultural heritage highlights the importance of community cohesion, gender roles and cultural practices. By acknowledging and preserving these aspects, initiatives can be developed to empower local communities, promote gender equality and preserve cultural identity. Such efforts can enhance social cohesion, strengthen cultural bonds and promote inclusivity in the development agenda of desert-prone areas.

This study contributes a novel conceptual framework that bridges multifunctionality concepts, sustainability principles and stakeholder perspectives to characterize agricultural heritage in desert-prone areas. It offers insights into the complex interplay of cultural, ecological, economic, social and scientific dimensions of agricultural heritage systems.

Investments in gender training for agricultural researchers have not attained expected outcomes, bringing into question the efficacy of training approaches used. New approaches for transformative gender training need to draw on lessons learned from previous courses. This chapter analyses short gender training courses identified using a scoping methodology. Selected courses offered between 2005 and 2015 for scientists in Eastern Africa were critiqued against a theoretical framework for transformative gender training. Also shared is a training model (Gender Responsive Researchers Equipped for Agricultural Transformation course) that addresses gaps in previous courses. The chapter identifies critical lessons for facilitating transformative gender training for non-gender research practitioners which include the need for inter-disciplinary grounding in the disciplines of gender and agriculture, having a phased course delivery and the value of continuous technical support during and after training. Gender training models should also allow for the deepening of gender awareness and consciousness by providing safe spaces for personal reflections on the root causes of gender inequalities and for the questioning of the internalized norms and biases.

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.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

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.

Evaluating the economic effects of climate change is a pivotal step for planning adaptation in developing countries. For Bangladesh, global warming has put it among the most vulnerable countries in the world to climate change, with increasing temperatures and sea-level rise. Hence, the purpose of this paper is to examine how climate change impacts the economy in Bangladesh in the case of climate scenarios.

Using a dynamic computable general equilibrium (CGE) model and three climate change scenarios, this paper assesses the economy-wide implications of climate change on Bangladesh’s economy and agriculture. It is clear from the examination of the CGE model that the impacts of climate change on agricultural sectors were felt more sharply, reducing output by −3.25% and −3.70%, respectively, and increasing imports by 1.22% and 1.53% in 2030 and 2050, compared to the baseline.

The findings reveal that, relative to baseline, agricultural output will decline by a range of −3.1% to −3.6% under the high climate scenario (higher temperatures and lower yields). A decrease in agricultural output results in declines in agricultural labor and household income. Household income falls in all categories, although it drops the most in urban less educated households with a range of −3.1% to −3.4%. On the other hand, consumption of commodities will fall by −0.11% to −0.13%, according to the findings. Although climate change impacts had a relatively small effect on gross domestic product, reducing it by −0.059% and −0.098% in 2030 and 2050, respectively.

As agricultural output, household consumption and income decline, it will impact the majority of the population’s health in Bangladesh by increasing malnutrition, hidden hunger, poverty, changing food environment, changing physical and mental health status and a changing health-care environment. Therefore, population health and food security will be a top socioeconomic and political concern for Bangladesh Government.

The examination of the dynamic CGE model is its originality. In conclusion, the evidence generated here can provide important information to policymakers and guide government policies that contribute to national development and the achievement of food security targets. It is also necessary to put more emphasis on climate change issues and address potential risks in the following years.

The purpose of this study was to conduct a comprehensive analysis of the impact and its mechanism on the transfer of agricultural labor forces in the surrounding areas resulting from the establishment of a natural reserve, which holds great significance. The significance of this analysis is on the ecological protection of the natural reserve and the coordinated development of local social economy.

This study first performs an analysis on the impact and its mechanism on the establishment of the natural reserve on the transfer of agricultural labor forces from two aspects, which are push and pull factors. Then, based on county panel data in Jiangxi Province from 1995 to 2012, this study builds a generalized difference-in-difference model and performs an empirical study on the impact, heterogeneity and its mechanism on the establishment of the natural reserve on the transfer of agricultural labor forces.

The empirical analysis reveals that the establishment of natural reserves would significantly promote the transfer of agricultural labor forces to non-agricultural sectors. The robust test and placebo test with changed estimation methods verify the robust of the result. The result passes the parallel trend test and shows that the impact is most significant within one year after the implementation of the policy. From the mechanism analysis, the impact mainly comes from the “push” effect brought by the restricted development of agricultural production and primary industry on agricultural labor forces, and the “pull” effect brought by the development of local tertiary industry.

The conclusion of this study enriches the understanding of the internal mechanism between the establishment of natural reserves and the transfer of agricultural labor forces from the push and pull factors, and can provide reference for formulating policies to promote the coordinated development of natural reserve construction and regional social economy.

This paper investigates the impact of bank credit on agricultural productivity in the Central African Economic and Monetary Community (CEMAC) from 1990 to 2019. Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting.

Agricultural value added (AGRVA) to the gross domestic product (GDP) proxies agricultural productivity while domestic credit to the private sector by banks (DCPSB), broad money supply, land, inflation (INF), physical capital (PHKAP) and labour supply are explanatory variables. The autoregressive distributed lag technique is utilized.

The co-integration test results show a long-run co-integration among the variables. The findings disclose that DCPSB, land and PHKAP impact positively on the AGRVA. Broad money supply, INF and labour impact negatively on the AGRVA to the GDP.

The results suggest that the CEMAC governments should encourage effective ways to increase bank credit flow to private enterprises in the agricultural sector through efficient bank's intermediation.

The governments should create more agricultural banks and improve the operation of existing ones to ensure direct credit to agricultural activities. The Bank of Central African Economic and Monetary Community should apply aggressive policy which eliminates all the bottlenecks undermining credit flow to the private sector in mutualism with agricultural productivity.

The commercial banks should give more credit to private sector to mutually benefit the agricultural sector and the banking sector. The governments of the CEMAC economies should expand funding into the capital market which considerably boosts agricultural productivity.

Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting; some reveal positive impacts, some show negative impacts and others indicate U-shape behaviour. Hence, research is required to fill the lacuna.

The authors examined the impact of the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP) payments to United States agricultural producers on non-real estate agricultural loans.

The authors used quarterly, state-level commercial bank data from 2016–2020 to estimate dynamic panel models.

The authors found MFP and CFAP payments not associated with the percentage of non-real estate agricultural loans with payments over 90 days late. However, these payments associated with the percentage of non-real estate agricultural loans with payments between 30 and 89 days late. The available data utilized cannot consider when producers received the actual payment and what they specifically did with those funds.

The contribution of this study is for US policymakers and agricultural lenders. The findings could be helpful in designing and implementing future ad hoc payment programs and provide an understanding of potential shortcomings of the current safety net for agricultural producers in the Farm Bill. Additionally, findings can assist agricultural lenders in predicting the impact of ad hoc payments on their distressed loan portfolios.