Identification of Adaptive Capacity Assessments to Improve Collective Adaptation of Farmers to Climate Change

Collective adaptation is a relevant discussion in association with the limited adaptive capacity of farmers to deal with climate change. This study aims to improve the collective adaptation of farmers through the identification of adaptive capacity assessments. A collective adaptation mechanism in the form of planning for rice planting time has succeeded in reducing the vulnerability of farmers. This study was conducted at a rice production center with a collective adaptation mechanism in Indramayu District, West Java Province, Indonesia. The data were collected using a quantitative method through a questionnaire distributed to 296 farmer respondents and a qualitative method through structured interviews. The observations provided an overview for authors to build structured interviews. The results of the study show that the adaptive capacity of farmers is supported by social capital and collective adaptation mechanisms of farmers consisting of trust in the formal leaders, quality of collective decisions, and planning capacity. The results of this study contribute to the implementation of public policies in order to support the successful implementation of adaptation strategies to deal with climate change in accordance with the needs of farmers.

Farmers’ Capacity and Rice Productivity in Climate Change Adaptation in Central Lampung Regency, Indonesia

Climate change is an extreme natural change condition due to global warming that cannot be avoided, and will have a broad impact on various aspects of life, including the agricultural sector. The impact of climate change that occurs in the agricultural sector, namely flood and drought that cause plants to crop failure , is becoming greater, causing significant reduction in agricultural production, especially rice, requiring that farmers have the ability to adapt to climate change. The purposes of this study are to analyze the relationship between the performance level of agricultural extension workers and the capacity level of farmers in regard to climate change adaptation, and to analyze the relationship between the level of farmer capacity in climate change adaptation and rice productivity. The research was conducted in Central Lampung Regency in 2019 using a total of 100 rice farmers. The data analysis method used is Spearman rank correlation analysis. The results show that the performance level of agricultural instructors is significantly related to the level of knowledge capacity, attitude, and skills of farmers in climate change adaptation. Knowledge capacity, attitude, and skills of farmers in climate change adaptation are significantly related to rice productivity.

Integration of Agro-Ecological and Groundwater Resources for the Assessment of Crop Suitability Potential Modeling: The Case of Limpopo Province, South Africa

A comprehensive subtropical fruit potential model (IUM) was established through novel integration of groundwater resources with multi-criterion predictive parameters. Equal-weights overlay was applied to reclassified and ranked rasters to institute IUM. Avocado and litchi had the least spatial extent that concealed the micro-climatic zones of high rainfall (>1000 mmpa) in Vhembe, Mopane, and Waterberg districts; meanwhile, mango and citrus were the crops with the most extensive province-wide distribution. Subsequent potential was apportioned in these sequences by constituency: Waterberg (1719019 ha), Mopane (977741 ha), Vhembe (764044 ha), Capricorn (579506 ha), and Sekhukhune (379968 ha). The IUM resulted in the demarcation of 8.7 million ha to produce the selected crops, which reflected an increase of 7.7 million from the rainfed suitability model. The integrated model would result in the creation of 10.87 million direct employments. The IUM expanded the agrarian sector with positive spinoffs for agribusiness development.

Screening of Five Lamiaceae Essential Oils as Repellents for Sweet Potato Weevil, Cylas Formicarius (F.) (Coleoptera: Brentidae)

In this research, the repellent activity of five Lamiaceae essential oils, Agastache rugosa, Elsholtzia blanda, Elsholtzia ciliata, Elsholtzia penduliflora, and Plectranthus ovatus, was evaluated against sweet potato weevil, Cylas formicarius using a two-choice test between the essential oil-treated filter paper and the control. E. blanda and A. rugosa essential oils have some sweet potato weevil attractant properties at low dose (<47.16 nl/cm2),while N,N-diethyl-3-methylbenzamide (DEET), P. ovatus, E. penduliflora, and E.ciliata essential oils have repellent properties at doses ranging from 15.72 nl/cm2 to 196.49 nl/cm2. The effect of type of essential oil and their dose were interactively associated with repellent efficacy. There was a increase in repellent efficacy as the dose increased for all essential oils. The repellent activities of P. ovatus essential oil and E. penduliflora were higher than the others, and the repellent effects of E. ciliata essential oil and DEET were more dose-dependent than others, indicating that at low dose, P. ovatus and E. penduliflora essential oils have stronger repellent efficacy, but at higher dose DEET and E. ciliata have greater effects. Our findings clearly demonstrate that P. ovatus, E. penduliflora, and E. ciliata essential oils are candidate materials for future investigation as repellent compounds against sweet potato weevil control.

Maize Output Supply Response to Climatic and other Input Variables in Ethiopia

Climate change is among the major challenges to sustainable agricultural production in Ethiopia. Production of cereal crops, especially maize, is very responsive to changes in rainfall and temperature, as climatic parameters influencing productivity. This paper analyzes how climatic and other variables affect the supply of maize in Ethiopia. The data were obtained from secondary sources and cover the period 1981–2018. Data were analyzed using the Autoregressive Distributed Lag (ARDL) approach. The Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and Hannan-Quinn Information Criterion (HQ) were used to select the optimum number of lags. In order to detect whether unit root is present in the series, Augmented Dickey-Fuller (ADF) and Philips-Perron (PP) tests were carried out. The presence of long-run equilibrium was found between maize output and temperature, rainfall, and other included variables. The results show that, in both the long and shortrun, all included climatic variables had a negative relationship with maize output supply, although temperature showed statistical insignificance (P>0.10). The result showed that maize crops are highly sensitive to extremes of rainfall – both shortage in the initial growing period and excessin the vegetative and fruiting stages. It was concluded that farmers face climate-related risk due to variations, particularly in rainfall. Therefore, farmers should adapt by using short-duration and climate-tolerant varieties of maize, along with engagement with eco-friendly production systems.

Nexus Between FDI, Agriculture, and Rural Development: Evidence from Asian Countries

The aim of this study is explore the effect of foreign direct investment on agriculture and rural development. For this, panel data of 46 countries from Asia were accumulated for the time frame 1991–2018. The models OLS, POLS, 2SLS, and GMM are employed in this study. The study reveals that there is a favorable association between foreign direct investment and agricultural land as percentage of total land using the models OLS, POLS, 2SLS. In stark contrast, value added for agriculture, forestry, and fishing has an unfavorable association with foreign direct investment in all models employed in the study. Furthermore, female employment in agriculture has a negative association with foreign direct investment in OLS, 2SLS and GMM models, whereas male employment in agriculture has a negative association with foreign direct investment in the POLS model only. Land under cereal production has a favorable association with foreign direct investment in all models except POLS, and permanent cropland has a favorable association with foreign direct investment in all models except GMM. In addition, rural population has a positive relationship with foreign direct investment in OLS, POLS and 2SLS and a negative relationship with foreign direct investment in GMM.

Farmers’ Use of Social Media and its Implications for Agricultural Extension: Evidence from Thailand

Social media are viewed as having potential for agricultural extension. This study therefore surveyed social media use by farmers in a developing country, and their role as a source of agricultural information. To this end, 365 farmers in Chiang Mai, Thailand, were sampled and interviewed using a questionnaire. The findings revealed that the majority of respondents (81.92%) did not adopt social media and, these remained marginal as a source of agricultural information for farmers. Those using social media (18.08%) employed certain applications, i.e., LINE, Facebook and YouTube, mainly for communication, new updates and entertainment. Younger farmers and farmers with a higher formal education related to social media use significantly. To fully harness the potentials of social media for agricultural extension, more farmers need to be encouraged to use them, while relevant agencies also are required to provide support for this effort, such as staff training in social media use, and enabling a social media policy.

A Pragmatic Study for Enhancing Agricultural Efficiency through Labor Freedom

The study aims to explore labor freedom in the agricultural sector for enhancing the efficiency of farming through policy change towards assigning property rights, rental contracts, and better wage-employment options to rural workers. Labor freedom emphasizes land reform and development policy for improving the economic status and capabilities of rural workers. The paper assessed the labor freedom index, weighted through agricultural property rights, labor wage contracts, and rural development policy. Data envelopment analysis is used to assess farm-level efficiency under the framework of Tobit regression for different size-based farm categories. Farm-level information was collected through a primary survey of 336 rural households of an advanced agricultural state in India. The study found a positive association between farm size and intensity of labor freedom, although the extent of freedom differs among farms. Size-specific variation was also observed for allocative efficiency such that marginal and medium-sized farms are more efficient than smaller ones. Tobit regression indicated labor freedom to be positively and significantly related to the efficiency of marginal, small and overall farms with enhancing efficiency of 25, 17 and nearly 20%, respectively; however, estimates of labor freedom insignificantly increased the efficiency of mediums farms, by 4.8%. This result suggests that labor freedom positive and significantly affects the efficiency of farms in general, and marginal and small farms in particular. Of course, the elasticity estimate of enhancing efficiency through labor freedom for medium farmers is found at a lower level.

The Effects of Improved Cassava Variety Adoption on Farmers’ Technical Efficiency in Indonesia

The adoption of technological innovations, such as an improved variety, has been widely promoted worldwide to improve agricultural productivity. This study aimed to examine factors affecting farmers’ decision to adopt a new improved cassava varieties (NICV), and to estimate the effects of NICV adoption on farmers’ technical efficiency. This research used cross-sectional data from 300 cassava farmers in East Java, Indonesia. Furthermore, the data were analyzed by probit regression to examine factors affecting farmers’ decision to adopt NICV. Propensity score matching (PSM) procedures and stochastic frontier analysis were applied to evaluate the impact of NICV adoption on farmers’ technical efficiency. The results indicated that adoption was highly influenced by cooperative membership, access to credit, internet access, certified land, and off-farm work. The stochastic frontier analysis, by controlling the matched sample using PSM procedures, demonstrated that NICV adoption positively and significantly impacted farmers’ technical efficiency. Those who adopted NICV showed a higher technical efficiency level than those who did not. This finding implies that improved varieties could be further promoted to increase productivity. The research suggests that there is a need to improve NICV adoption to increase the levels of technical efficiency and productivity.

Effects of Climate-Smart Agriculture Adoption on Performance of Rice Farmers in Northeast Vietnam

Agricultural production is increasingly vulnerable to risks and uncertainties associated with climate changes. Climate-smart agriculture (CSA) has been proposed to address challenges in agricultural production such as food security, water shortage, drought, and soil erosion, etc. The benefits of CSA adoption for farmers have been debated. Many previous studies have indicated that impacts seem to be affected by selection bias. However, controlling such selection bias has not been considered in studies on the CSA adoption. Thus, in this study, we analyzed the impacts of CSA adoption on major economic indicators for rice farmers. The Propensity Score Matching (PSM) method was employed to address such selection bias for a case study on rice farmers in Thai Nguyen province, Vietnam. Comparing main economic indicators, we found significant differences in rice yields and used seed inputs between CSA and non-CSA adopters. Ignoring selection bias control resulted in overestimation of economic returns. The results also indicate limited contribution of CSA adoption to a reduction in pesticide and herbicide usage, and an increase in use of organic fertilizers. Some implications for further research are also discussed.