Search

Addressing the excessive input and inefficient use of agrochemicals are crucial for global food security, environmental protection, and human health. This paper offers a new idea from the perspective of outsourcing agricultural production. The impact of outsourcing on the frequency and intensity of agrochemical inputs were theoretically analyzed and empirically tested using a field survey of 1211 farmers in Heilongjiang, Henan, and Hunan, the major food-producing areas in China. A Logit regression framework was used to analyze the effect, a conditional mixture process (CMP) method was used to address potential endogeneity concerns, and a mediation effect model was used to dissect the mechanism. The results show that the effect of outsourcing on both input frequency and input intensity of agrochemicals was positive at the 1% significance level. The positive effect conclusion still holds even after addressing the potential endogeneity concerns, and in the sub-sample estimates for maize, wheat, and rice. We conclude that outsourcing can improve the utilization efficiency of agrochemicals by increasing the frequency of agrochemical inputs, but fail to solve the excessive agrochemical inputs and even leads to a further increase in the intensity of agrochemical inputs. Moreover, the mechanism for an increase in agrochemical input intensity due to outsourcing was explored, and it is more likely to be caused by inhibiting farmers' investment in soil improvement measures. [ABSTRACT FROM AUTHOR]

The conflict between agricultural production and environmental protection, especially vegetable production, is one of the world's most prominent concerns. The acceptance degree and possible response of new agricultural operation subjects, represented by Farmers Professional Cooperatives (FPCs), to green production policies are a core issue that must be considered when designing environmental policies in the future. Based on field survey data of 192 FPCs of vegetables in Shanghai, China, this paper uses a choice experiment method to test the willingness of cooperatives to adopt green production behaviors under different policy settings and to identify the differences under different operation scales. The results show that both mandatory policies and incentive policies have an impact on the willingness of cooperatives to adopt green production behaviors, but significant differences exist among FPCs of different operation scales. Specifically, the willingness of large-scale FPCs to adopt green production behavior is affected by key technology training and income subsidies, whereas the willingness of small-scale FPCs is only affected by income subsidies; the willingness of medium-scale FPCs is simultaneously affected by key technology training, income subsidies, and penalties. Therefore, when formulating relevant policies in the future, policy-makers should consider local conditions, including the endowment heterogeneity of the production and operation subjects, so as to enhance the level of green production. [ABSTRACT FROM AUTHOR]

Ensuring household food security and fighting hunger are global concerns. This research highlights factors affecting food security and solutions by utilizing a nexus of statistical and fuzzy mathematical models. A cross-sectional study was conducted in district Torghar, Northern Khyber Pakhtunkhwa, Pakistan, among 379 households through a structured interview schedule. Further, the data were coded into SPSS for analysis, i.e., descriptive, and inferential statistics. In a binary logistic regression model, the study explored that agricultural productivity lag, population growth, and climate change all had a negative impact on household food security (P = 0.000). In addition, these results were further cross-checked through spherical fuzzy mathematics. The fuzzy results revealed that population growth is the most powerful factor deteriorating the existing equilibrium of household food security in Torghar. The study concluded that climate change, population explosion, and agricultural production were the major factors behind the hunger in the study area. Thus, designing a synergy based on taking all these aforementioned realities into consideration is the need of the hour. If extended, a comprehensive model of addressing these anomalies with a solely objective-based approach may work as a panacea for all ills. Lastly, this study contributes to the food security literature by introducing a new approach that is more robust and flexible than existing methods. [ABSTRACT FROM AUTHOR]

Food availability is one of the dimensions of food security, and it is necessary to analyze the crop production scenario to estimate the availability of food in a region. Cropping sequence and cropping intensity indicate the seasonal crop production, thereby indicating the seasonal availability of food. Seasonal variation of per capita or per household availability of the cropped land determines the food security status of a given region. In Indian Sundarbans region, people's livelihood is seriously threatened by the food insecurity. The present study aimed to determine the seasonality of cropped land as well as the cropping intensities of Gosaba CD block of Indian Sundarbans during 2017–2018, 2018–2019 and 2019–2020 cropping years using Multi-dated Sentinel-2 data. Rule-based classification was applied for cropping sequence and cropping intensity mapping. Winter season cropped land was the lowest (< 16% of the village area). The area under crop–fallow–crop sequence (200% cropping intensity) decreased, while the area under crop–fallow–fallow (100% cropping intensity) sequence increased. Area under 300% cropping intensity gradually decreased. The average cropping intensity changed from 150% in 2017–2018 to 124% and 136% in 2018–2019 and 2019–2020, respectively. Large variation of the seasonal cropped land per household was estimated, and it became the worst during winter when it became less than 0.5 bighas (0.07 ha). Crop cultivation during dry season depended on the rainfall pattern and surface water availability. The present study successfully addressed the cropping scenario and food insecurity of the study area, and hopefully, it will help the planners and policy makers to take necessary actions for cropping intensification and ensuring food security in the Indian Sundarbans region. [ABSTRACT FROM AUTHOR]

Keeping the relationship between economic development, humankind and the environment in balance has been one of the main challenges of economic policies and science in recent years. Such concerns are recurrent when it comes to climate change and the dependence of the economic process on finite resources. In this way, the present study aims to assess Greenhouse Gases (GHG) emissions from the agricultural and livestock production and the Rural Development Index (RDI), seeking to identify the spatial relationship of these two variables among Brazilian states in 2010. The methodology used to meet the objective was the Exploratory Analysis of Spatial Data (EASD), which incorporates spatial factors. The main results obtained show that both RDI and emissions are positively influenced by space. Different patterns of association were observed among Brazilian states: states characterized by low emissions and high RDI; high emissions and high RDI; and low emissions and low RDI. Most parts of the states with high emissions are relevant livestock producers. It indicates, thus, that investments in more sustainable practices for livestock production allied with the promotion of welfare shall be encouraged. Although being a time cut, this study brings evidence that high levels of rural development, in its broad sense, do not always mean high emissions rates, the latter depending more on the type of agricultural and livestock activity practiced. [ABSTRACT FROM AUTHOR]

Climate change is among the most pressing challenges for human advancement in the twenty-first century. Climate change is having a significant impact on the agricultural sector. The main objective of this study is to evaluate the food security status and sustainability of crop production under different climate change scenarios in the arid and semi-arid zones of Iran. To this end, the Statistical Down-Scaling Model (SDSM) and the outputs of the General Circulation Model (GCM) are employed to project future climate parameters under three climate scenarios. The study then employs the Just and Pope approach by using a panel dataset to evaluate the impact of climate change on crop production. Also, the multi-criteria decision-making (MCDM) technique is used to assess the sustainability of crop production from an economic, social, and environmental perspective in the context of climate change and baseline conditions. The results of the study show that precipitation has a significant favourable effect on crop yield in both zones. Maximum temperature is positively and significantly related to crop yield in the semi-arid area, while the relationship is negative in the arid region. Future projections reveal that under different climate scenarios, the production of irrigated wheat, dryland wheat, irrigated barley, dryland barley, and potato crops will change by a maximum of approximately 7.57%, 35.70%, 62.86%, 15.90%, and 26.88% in the semi-arid zone and − 24.07%, 29.73%, − 31.33%, − 4.80%, and 25.80% in the arid zone, respectively. The findings imply that climate change will decrease the food security index for all crops in the arid zone, while improving the situation for crops in the semi-arid region. The results also indicate that future climate change can have a significant adverse effect on economic water productivity, economic benefits, and the sustainability of strategic crop production in the arid zone compared to the semi-arid zone. Given that a large part of Iran is covered by an arid climate, designing coherent adaptation actions and mitigation policies need to be prioritized to tackle the negative impact of climate change on food production systems. [ABSTRACT FROM AUTHOR]