Designing a community-supported agriculture model for increasing food security

The institutionalization of participation is a topic that has been discussed in different ways over the last few decades. There are many diverse aspects of the agricultural sector and rural communities that can be identified and used to bring about a major change in agriculture. Community supported agriculture (CSA) is one of the participatory and sustainable approaches that can be used in this regard. CSA is a relatively new socioeconomic model for producing food materials, increasing food security, improving the quality of food materials and conserving agricultural land, plants and animals. This research aimed to design a CSA model that was operationalized in Markazi province, Iran, with the aim of increasing food security. It was a survey study applied through a questionnaire. The statistical population (N=110) consisted of all active farmers in Ghazel Dareh village who were selected through the census method. The necessary information was collected through a questionnaire (84 of which were completed and returned) and analyzed using SPSS v. 25 and LISREL. The results showed that economic, socio-institutional, policy-making, educational and infrastructural factors significantly influenced the development of CSA. Infrastructural and socio-institutional factors with impact factors of 0.88 and 0.54 had the largest and smallest effect on CSA, respectively. Finally, since all impact factors were positive, we can say that improving each of these factors could improve the development of CSA in the study area.

Modelling climate variabilities and global rice production: A panel regression and time series analysis

Climate change threatens agriculture and it remains a present global challenge to food security and Sustainable Development Goals. The potential impact on the supply of crops such as rice is seen as a major food security issue that requires intervention on several fronts. The literature on rice production, climate variations and climate change show several studies outlining various impacts on rice supply as a result of variations in temperature and rainfall. This study intends to further explore the impacts on rice production caused by temperature changes and rainfall variation by analyzing and modelling the production of rice by the top rice-producing countries globally. A time series of the national rice production and yield along with national average annual temperature and rainfall were sourced for 15 major rice-producing countries. The trends of the time series were then compared between the rice productivity variables and temperature and rainfall. A panel regression model was also developed to further assess the relationship between rice production and temperature and rainfall. The time series showed that rice production and yield are increasing for the majority of the countries analyzed. The panel regression model however showed that continued increase in temperature can result in decreased production of rice and that rainfall volume directly impacts rice output and therefore shows rice production is highly susceptible to flooding and drought events caused by climate variabilities.

Does financial development mitigate the effects of climate variability on rice cultivation? Empirical evidence from agrarian economy

This study is the first attempt to examine the effects of changing climate and financial development on rice cultivation in the context of agrarian economy like Thailand from 1969 to 2016. The current study also uses other important variables, such as cultivated area, organic fertilizers usage, and rural labor to determine the long-term connection amid variables. In this study, we applied several econometric techniques, for instance the autoregressive distributive lag-error correction model (ARDL-ECM), vector error correction model (VECM), impulse response functions (IMFs), and variance decomposition (VARD) method to estimate the most reliable and robust outcomes. The empirical results showed that in the long- and short-run, there is a reduction in rice cultivation as temperature increase. The carbon dioxide (CO₂) positively affects rice cultivation in the long-run, while this association is negative in the short-run. The findings further revealed that in the long- and short-run, domestic credit provided by the financial sector significantly positive improved rice cultivation, while domestic credit to private sector by banks negatively affects rice cultivation. The important input factors, including cultivated area, organic fertilizers usage, and rural labor significantly positive contributed toward rice cultivation in the long- and short-run. The calculated long-run causal connection of all the studied variables with rice cultivation is validated. The estimated short-run causal relationship is unidirectional among temperature, CO₂ emissions, financial development, rural labor, and rice cultivation. In addition, our outcomes are robust and also verified by IMFs and VARD method. The study offers some important policy suggestions to increase rice production with the help of sound and well-developed financial systems and climate controls.

Predicting Rice Production in Central Thailand Using the WOFOST Model with ENSO Impact

The World Food Studies Simulation Model (WOFOST) model is a daily crop growth and yield forecast model with interactions with the environment, including soil, agricultural management, and especially climate conditions. An El Niño–Southern Oscillation (ENSO) phenomenon directly affected climate change and indirectly affected the rice yield in Thailand. This study aims to simulate rice production in central Thailand using the WOFOST model and to find the relationship between rice yield and ENSO. The meteorological data and information on rice yields of Suphan Buri 1 variety from 2011 to 2018 in central Thailand were used to study the rice yields. The study of rice yield found that the WOFOST model was able to simulate rice yield with a Root Mean Square Error (RMSE) value of 752 kg ha−1, with approximately 16% discrepancy. The WOFOST model was able to simulate the growth of Suphan Buri 1 rice, with an average discrepancy of 16.205%, and Suphan Buri province had the least discrepancy at 6.99%. Most rice yield simulations in the central region were overestimated (except Suphan Buri) because the model did not cover crop damage factors such as rice disease or insect damage. The WOFOST model had good relative accuracy and could respond to estimates of rice yields. When an El Niño phenomenon occurs at Niño 3.4, it results in lower-than-normal yields of Suphan Buri 1 rice in the next 8 months. On the other hand, when a La Niña phenomenon occurs at Niño 3.4, Suphan Buri 1 rice yields are higher than normal in the next 8 months. An analysis of the rice yield data confirms the significant impact of ENSO on rice yields in Thailand. This study shows that climate change leads to impacts on rice production, especially during ENSO years.

Addressing the long- and short-run effects of climate change on major food crops production in Turkey

This study assessed the long-run (LR) and short-run (SR) impacts of climatic and non-climatic factors, i.e., CO2 emissions (CO2e), average level of temperature (ALT), average level of precipitation (ALP), area harvested of wheat and rice crops (AHW and (AHR), domestic credit (DCR), and agricultural labor (ALB) on wheat and rice production (WP and RP) in Turkey by using annual time series data ranging from 1980 to 2016 and by employing several econometric techniques. The autoregressive distributed lag-bounds (ARDL) approach and the Johansen and Juselius cointegration (JJC) test confirmed a valid long-term connection among underlying variables. The estimation results from the ARDL model reveal that climatic factors such as CO2 emissions and temperature adversely affected wheat production in the long run as well as in the short run, whereas precipitation positively improved wheat production in both periods. Further results indicate that non-climatic factors like area harvested of wheat and domestic credit positively and significantly enhanced wheat production in the long run and short run. Similarly, CO2 emissions also adversely affected rice production in both periods, while temperature and precipitation positively contributed towards rice production in both cases. In addition, area harvested of rice positively and significantly boosted rice production in the long run as well as in the short run, while domestic credit negatively influenced rice production in the long run but in the short run positively improved rice production. Additionally, the outcomes of the VECM Granger Causality for both rice and wheat production confirm that both climatic and non-climatic variables have a strong influence on the production of both crops. This study found that climate change has a deleterious influence on both wheat and rice production; therefore, the study suggests that temperature-resistant varieties of both crops should be developed and introduced by agricultural research institutions. In addition to this, up-to-date information is more needed related to climate change, and in the farming communities, it should be provided by agricultural extension workers.

Extreme climate projections under representative concentration pathways in the Lower Songkhram River Basin, Thailand

This paper aims to assess changes in the extreme climate indices of the Lower Songkhram River Basin of Thailand under Representative Concentration Pathways (RCPs) scenarios. A linear scaling method was used to correct climate data bias in three Regional Climate Models (RCMs) under RCP 4.5 and RCP 8.5 scenarios. Thereafter, extreme climate indices related to temperature and rainfall were analysed for the wet and dry seasons in upstream and downstream areas of the basin. A total of 14 climate indices were analysed for three time periods: the 2030s (2020–2044), 2055s (2045–2069), and 2080s (2070–2094) and compared with the baseline climate from 1980‒2004. The results show that considerable variability is expected in the extreme climate of the basin in future. The average annual and monthly maximum and minimum temperature is projected to increase, with a lesser increase in the near future and higher in the far future. Heat events (TXx, TXn) are projected to increase while the cold events (TNx, TNn) are projected to decrease in both dry and wet seasons upstream and downstream of the basin. The future average annual rainfall in the basin is projected to decrease under RCP 4.5 and RCP 8.5 scenarios for all three periods. However, the variability in average monthly rainfall is expected to increase in the dry season (Jan–May) and decrease in the wet (Aug–Dec). The most intense rainfall in one day (RX1Day) and five consecutive days (RX5Day) in the wet season is observed to increase in future, with a higher increase in the near future and a lower increase in the far future. The very heavy rainfall days (R20) (the number of days receiving more than 20 mm/day in the basin) are observed to decrease in both wet and dry seasons under RCP 4.5 and RCP 8.5 scenarios in both locations. The results of this study will be helpful for the planning and management of natural resources as well as disaster risk reduction in the Lower Songkhram River Basin.

Examining the effects of climate change on rice production: case study of Pakistan

The current empirical study explores the linkage between carbon dioxide (CO₂) emissions, average temperature, cultivated area, consumption of fertilizer, and rice production in Pakistan. For this research, the annual time series data from 1968 to 2014 were used to enhance the validity of the empirical outcomes. The cointegration analysis with the auto-regressive distributed lag (ARDL) bounds testing approach is applied to explore the effects of climate change on rice production. Additionally, the estimated long-run outcomes are verified by employing fully modified ordinary least squared (FMOLS) and canonical cointegrating regression (CCR) approaches. The empirical outcomes revealed that the selected important study variables are cointegrated demonstrating the existence of long-run linkages among them. The main fruitful outcomes of this study are that rice production in Pakistan is positively affected by the carbon dioxide (CO₂) emissions in both long-run and short-run.

Evaluation of climate change impacts and adaptation strategies on rainfed rice production in Songkhram River Basin, Thailand

This study investigates rice yield and evaluates potential adaptation measures on field management practices for rainfed rice production under climate change scenarios in the Songkhram River Basin, Thailand. The top-down and bottom-up approaches are combined to evaluate the future climate conditions in the Songkhram River Basin and identify adaptation strategies respectively. An ensemble of four Regional Climate Models (RCMs) bias-corrected using the Quantile Mapping technique was used to project the future climate under two climate change scenarios (RCP4.5 and RCP8.5). The DSSAT crop simulation model was used to simulate rice yield and evaluate the impacts of climate change on rice yield, as well as the feasibility of four adaptation options, which were solicited from four hundred farmers through questionnaire surveys in the basin. The strategies include (i) change in planting date, (ii) change in fertiliser application date, (iii) change in fertiliser application dose, and (iv) supplying irrigation water. Based on the model results, future maximum and minimum temperatures are expected to increase by 2.8 and 3.2 °C respectively under RCP8.5 scenario for 2080s. Although annual rainfall may be unchanged, rainfall patterns will shift earlier in future. Evaluation of adaptation strategies suggest that supplying irrigation water under RCP4.5 and RCP8.5 scenarios respectively are the best strategies to increase rice yield under climate change scenarios. Change in fertiliser application date and change in planting date can increase the future rice yield by 12 and 8%, respectively under RCP4.5 scenario for 2080s. Adjusting the fertiliser application dose may however reduce future rice yield. Although supplying irrigation water can aid the production of rainfed rice, other concerns such as the source of water are involved. The feasibility of adaptation actions would depend largely on available resources and mindset of farmers. Further work is warranted in exploring a combination of adaptation strategies and management plans to combat the adverse impacts of climate change.

Adaptation Strategies under Climate Change for Sustainable Agricultural Productivity in Cambodia

Since the Cambodian economy is largely dependent on agricultural production, it is important to understand the effects of climate change on rice production, the primary staple crop of Cambodia. This study assessed the economic impacts of climate change in Cambodia to provide an appropriate set of policy suggestions that could lead to sustainable agricultural productivity and economic growth. The results from the GLAM-Rice crop model and various climate models indicate that Cambodia will be severely affected by climate change, which will lead to lower rice production and economic growth. The changes in rice yield under the RCP 8.5 and RCP 4.5 baseline scenarios reduced the GDP by 8.16% and 10.57%, respectively. By employing an investment model based on a real options framework, the economic effects and feasibility of adaptation strategies such as irrigation and adjustment of planting dates are identified. The analysis indicates that irrigation is a feasible option and the most efficacious strategy to reduce the negative impacts of climate change for the agricultural sector. The index of economic feasibility for irrigation, defined by the ratio of the current realized agriculture value-added to the identified threshold, is 0.6343 and 0.8803 under the RCP 8.5 and RCP 4.5 baseline scenarios, respectively. The results suggest that the priority choice for adaptation measure be in order of irrigation, 20-day later adjustment, and 20-day earlier adjustment.