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The application of smart agriculture is increasingly becoming a critical force in transforming the traditional methods of agricultural production in China. This change, based on technological innovation, is essential to promoting a sustainable production system in family farms. This study is based on the resource orchestration theory to investigate how smart agriculture affects the diversity of green production technologies (GPTs) on family farms. Based on a sample of 563 family farms surveyed in 2022, this study utilizes propensity score matching (PSM) methods and instrumental variables to analyze the effect of smart-agriculture adoption on the diversity of GPTs on farms. The findings reveal that smart agriculture has significantly increased the diversity of GPTs on farms by 8.5%. Network consulting services, value-added products, and environmental monitoring services are potential impact mechanisms underlying the positive effects of smart agriculture on the diversity of GPTs on farms. Furthermore, the increased diversity of GPTs is more significant on purely plantation farms, farms without contract farming, and farms with high levels of mechanization.

Impression of this study is to investigate the correlation of land fragmentation and rice production efficiency into two different major rice cropping zones, which mostly at middle and upper part of the Sindh province, Pakistan. For this study, randomly data of 450 rice growers were collected from 5 major growing districts (Dadu, Naushahroferoze, Sukkur, Larkana and Shikarpur) of Sindh province Pakistan, 432 respondents were analyzed out of 450, remaining 18 samples found an error in data due to auto-generated results. As for the empirical results Cob Douglas and censored normal Tobit model were analyzed by using SPSS and E-views. As for as results of Cob Douglas production function opined that the production can be increased owing to the increase in family income, ploughing, planking and irrigation also confirm that the 1% reduction in land rent, temporary labor with fertilizer usage such as; urea, DAP and chemical spray would causes the production increase in middle part of the Sindh, followed by the upper Sindh rice production can be raised by the land rent increment, permanent labor ploughing, planking, seed rate and fertilizer; urea and NP, just need to reduce 1% appliance on irrigation. In addition, the results of the censored Tobit model suggests that there is possibility to increase rice production efficiency by increasing the general characteristics of rice growers such as; age, education, experience, farm size, health of farmers, market availability near to farms, extension service and school, producer efficiency. The rice production can also be increased by the decreasing land fragmentation and distance from homestead to farm in middle Sindh. When the production efficiency would be increased in upper Sindh as compare to the middle Sindh gradually by increasing age, experience, land rented in, shared out land, farm size and availability of the market near farm, same variables for land fragmentation and distance from homestead to farm has negative coefficient impression. The results policy suggested the assurance of land fragmentation and distance from homestead to farm has significant correlation with rice production. Therefore, government may revise land reform policies with its land consolidate; by this farmers may adopt modern agro-based technologies easily and resultantly to increase rice production and ultimately help to reducing poverty scale. Keywords: Rice, production, fragmentation, Policy and Sindh.

Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon.

This study aims to contribute to the literature and examine the causal relationship between Pakistan’s agricultural products export, industrialization, urbanization, transportation, energy consumption, and carbon emissions. For the last four decades, time-series data were used to employ short-run and long-run nexus between the selected variables by analyzing the autoregressive distributed lag model (ARDL). The Granger causality test was analyzed to estimate the causality directions. The unit root test results indicate that all the selected variables are stationary at the level and first difference. The bound test confirmed that all variables are cointegrated at a 1% significance level. Long-run estimates suggest that an increase in energy consumption will increase the export of agricultural products. An increase in urbanization, transportation, and carbon emission resulted in a decrease in agricultural products export in Pakistan. In the short run, an increase in industrialization, transportation, and energy consumption leads to an increase in agricultural products export. Increasing urbanization and carbon emission decrease the agricultural products export of Pakistan. Based on our findings, we recommend sustainable agricultural production, renewable energy consumption, low carbon emission technologies, and a green portfolio for sustainable agricultural products export.

The present research focuses onthe problems faced by sugarcane growers in adoption of production practices of sugarcane in district Naushahro Feroze. From taluka Moro and N. Feroze five villages were selected through multistage sampling techniques.Thus,makingasampleof75farmerswasrandomlyselected from the study area. Multistage plan was used to collect the data. It was observed that a high majority of the respondents had knowledge that land ploughing helps to increase the increase the yield stability rate of crops (60%). Regardingtimeofapplicationoffertilizers,majorityofrespondentshadpartial knowledge with 70 percent of the respondents having full knowledge regarding applicationofirrigationoncein10to15days. The results indicates that majority (40%) of the respondents adopt proper land preparation practices. The results indicated that the major constraints faced by percent of respondents were high cost of fertilizers and non-availability of credit facilities, non-availability of required quantity of fertilizers. In light of constraints faced the major suggestion expressed was providing credit at lowerinterest rate and at required time, cost of complex fertilizers should be reduced, conduct demonstrationsondifferentsustainablecultivationpracticesinsugarcanetoshowtheir efficacy, proper schedule of varietal harvesting must be followed by sugar factories, organizetrainingprogrammesonsustainablecultivationpracticesinsugarcane,provide pest and disease resistant varieties through sugar factories and research stations, conduct as many as group discussions, and exposure trip to sugarcane growers to convince the benefit of various sustainable cultivation practices, establish sugarcane growers club and conduct regular meetings with scientist and progressivefarmers

E-commerce furnishes farmers in rural China with a novel solution accomplishing entrepreneurship transformation, but serious credit constraints still coexist with it at present, which may restrict the release of e-commerce’s potential. Therefore, this study investigates whether formal credit promotes entrepreneurial farmers’ e-commerce utilization and explores its influencing mechanism. Based on the survey data collected from 831 entrepreneurial farmers in Shaanxi province, Ningxia province and Shandong province in rural China, the propensity score matching (PSM) method was applied to measure the impact of formal credit on e-commerce utilization. The results show that formal credit contributes to a 18.41% increase of e-commerce utilization in general and increases entrepreneurial farmers’ online purchases and sales by 11.15% and 14.69%, respectively. Some groups perform significantly in the heterogeneity analysis, the most noteworthy of which are entrepreneurial farmers who are younger, belong to new type of agricultural business entities and use mobile payments. Their e-commerce utilization, including online purchases and sales, are impacted most by formal credit. Furthermore, when the bootstrap method was used to examine the mediating effect, we found that formal credit has a positive and significant effect on the utilization of e-commerce through four channels, which are internet learning, asset allocation, labor allocation and income growth. Hence, the findings suggest that the government should augment the amount of formal credit to optimize entrepreneurial farmers’ internet learning, asset allocation, labor employment and income growth, thereby promoting e-commerce to achieve entrepreneurial transformation and sustainable development in rural areas.

The research on the protective effect of piped water on young children has been documented in developing countries. However, little is known about the effect of access to piped water (APW) on adolescent health. Based on China Education Panel Survey (CEPS) baseline data for 9,204 adolescents in rural China, we examine the causal effect of APW on adolescent health by employing a control function with ordered probit (CF‐oprobit) model. We find that the availability of piped water in rural households can significantly improve the adolescent health status and also that the effect of piped water on adolescent health is heterogeneous in different subgroups. The protective effect is more pronounced among minorities (rather than Han nationalities), the only‐child families, and left‐behind children during the preschool years. Consequently, piped water programs have irreplaceable significance in improving adolescent health in rural China. Furthermore, policy‐makers should pay more attention to households of ethnic minorities, left‐behind children, and other vulnerable groups in their implementation.

Currently, the world is facing challenges of environmental pollution and public health owing to increasing urbanization. Therefore, many researchers from developed and developing countries are considering environmental pollution and public health to be the most important topics for sustainable development alongside a healthy and green environment. Although in the literature many researchers have investigated a pictorial view of green environment by defining the urban green space and blue space effects on public health, the green environments and public health research trend remains unclear. Thus, this study aimed to contribute to the literature by visualizing the bibliometric for green environments and public health, and to identify the missing research pathway. Data for this study was collected from the Web of Science from 2003-2019 in order to facilitate a visualization and bibliometric analysis carried out by CiteSpace. The visualization results reveal the most influential studies, institutions, authors, countries, keywords, and category cloud in the green environments and public health research field. Furthermore, this study suggests that researchers need to pay attention to how the genome changes due to climate change, as well as environmental pollution and its effect on human health. Mental health and research related to green environment and social health is also missing. In addition, there is also a missing link regarding green environment, underground water and public health. Additionally, this study could help authors and publishers make decisions concerning research on green environments and public health and planning for future perspectives to contribute to both academic development and applied methodology.

Air quality is a social, economical, and health issue for fast-developing countries such as China. Due to the overuse of nonrenewable energy, industrialization, and the population put pressure on air quality, which seriously threatens public health and economic growth. This study focuses on air quality and also aims to investigate the short-and long-run correlation between foreign direct investment, energy consumption, domestic credit, and financial development. The Autoregressive distributed lag model and the Granger non-causality test were carried out over the period from 1985 to 2018. The main findings of this study show a positive and significant long-run impact of energy consumption on air quality. In addition, domestic credit and financial development similarly show a significant positive short-run association with air quality. Moreover, the unidirectional causality correlation running from foreign direct investment and domestic credit to air quality was concluded by the Granger non-causality test. Considering the empirical analysis, this study suggests that domestic financial institutions should offer credit to industries at a low-interest rate in order to help them to switch from non-renewable to renewable energy consumption towards the promotion of sustainable and healthy air quality.

China is the world's largest fossil fuel consumer and carbon emitter country. In September 2020, China pledged to reduce carbon emissions, and achieve carbon neutrality by 2060. Therefore, this study aimed to contribute to the literature and show the pictorial nexus of bioenergy and fossil fuel consumption, carbon emission, and agricultural bioeconomic growth, a new pathway towards carbon neutrality. For this study, time-series data from 1971 to 2019 were used to analyze the autoregressive distributed lag (ARDL) bound testing and novel dynamic autoregressive distributed lag (DYNARDL) simulation models. Initially, the unit root tests results showed that all variables were stationarity at the level and first difference. The presence of cointegration between selected variables was confirmed by the results from ARDL bound test. In addition, the results of long-run and short-run nexus show an increase in bioenergy consumption that caused an increase in agricultural bioeconomic growth both in the long and short-run nexus. A decrease in fossil fuel consumption was shown to result in increased agricultural bioeconomic growth with respect to both long- and short-term effects. Furthermore, the results of the novel dynamic ARDL simulation model demonstrated that a 10% positive shock from bioenergy consumption caused an increase in agricultural bioeconomic growth, while at the same time, a 10% negative shock in bioenergy consumption led to a decrease. A 10% negative shock from fossil fuels caused an increase in agricultural bioeconomic growth, whereas a 10% positive shock from fossil fuels led to a decrease. Therefore, this study suggests that China needs to switch from fossil fuel and other non-renewable energy consumption to sources of bioenergy and other renewable energy consumption to achieve carbon neutrality by 2060.

Pakistan is an agricultural country where cereal crops are used as a staple food, but with time trend cereal production is decreasing. Therefore, this study aims to investigate asymmetric causality between agricultural carbon emissions, energy consumption, fertilizer consumption, and cereal food production in Pakistan. The secondary time series data over the period from1976 to 2018 was used to estimate the nonlinear-autoregressive distributed lag model. The empirical results of the linear Granger causality test confirm that the causality is running from energy consumption and fertilizer to cereal food production. The nonlinear Granger causality test declares cereal food production Granger cause to agricultural carbon emissions and energy consumption. It also confirms the unidirectional causality running from fertilizer consumption to cereal food production. Furthermore, the results of the nonlinear-autoregressive distributed lag model disclose that the positive and negative change in agricultural carbon emission, energy consumption, and fertilizer causes to changes in cereal food production. The dynamic multiplier curve suggests that positive and negative shocks influence cereal food production. The stability of the model was confirmed by the nonlinear-autoregressive distributed lag cumulative sum and cumulative sum of square test. Therefore this study suggests that it is essential for Pakistani farmers to switch from chemical fertilizer, burning non-renewable energy to organic fertilizer, and renewable energy in order to reduce carbon emission and increase cereal food production with a healthy environment.

The spillover effect of environmental behavior has been of wide concern in recent years. The purpose of this paper is to explore the influence of household waste sorting on green consumption (behavioral spillover) and the possible psychological mechanisms involved in such spillover of environmental concern. Though it is important, insufficient attention has been paid to exploring the relationship, and the process of its formation, between waste sorting and green consumption. To narrow this gap, survey data collected in 2018 from 688 rural households from Shaanxi Province in western China were used. The propensity score matching method was employed to measure the effect of waste sorting on rural households&rsquo, green consumption. The mediating model was employed to investigate the path of influence in the relationship between waste sorting and green consumption. The results showed that waste sorting behavior positively spilled over into green consumption, with a net effect of 0.205. Environmental concern has a mediating effect on the relationship between waste sorting and green consumption behavior, with a mediating effect of 0.3177. In summary, household waste sorting behavior has a spillover effect on green consumption behavior as a result of the mediation effect of environmental concern. The results of this article fill in our knowledge on the spillover effects of waste sorting behavior in developing countries. Policy makers and regulators should vigorously advocate and implement waste sorting behavior, increase farmers&rsquo, concern for the environment, and promote their participation in green consumption behavior, so as to maximize the spillover effect.

Environmental Kuznets curve (EKC) is a statistical tool to examine the cointegration and causality nexus between economic growth and carbon emissions. The EKC is widely used in energy and environmental economics studies. Although a large number of researchers have analyzed the EKC by applying different statistical models, some review work has been summarized to draw a pictorial view of extending studies in this research field. However, still, the macroscopic overview needs to be considered. Therefore, this study aims to contribute to the literature for finding a new pathway for further research employing, and to facilitate this research, scientometric analysis is carried out by feature in CiteSpace. The dataset was screened and found 2384 records out of 59,225 Web of Science (WoS) references, and the records for the timespan 1999–2019 was used to visualize the knowledge map and outcome of the scientific enterprise. The visualization results reveal the most influencing studies, institutions, authors, countries, keywords, and category cloud, in the research field of EKC. This article reveals that the research on EKC in alignment with green and sustainable technology science requires more attention. Further, this article would help authors and publishers make their decisions for the research of EKC and planning for future perspectives to contribute to academic development and applied methodology.

This study examines the quantitative effects of market price in cotton producing areas of China. It also analyzes the qualitative effects of price regulation on cotton production. Secondary time series data were collected from National Bureau of Statistics in China, between 1990 and 2013. Calculation of the growth rate of cotton in production was done using linear trend model and multi-regression model to analyze the correlations between production, area and market price. The results of regression between the dependent variable (cotton production) and independent variables such as the previous year’s area, current year’s area and the previous year’s market price showed that the R-Square and adjusted R-Square values are 0.89 and 0.87, respectively, and the t-statistics of all independent variables rejected null hypothesis of no correlation at the 1% significant level. This infers that the market price and cultivating area of cotton crop has a highly significant relationship with the production. What’s more, the coefficients of current year’s area and previous year’s market price are higher than 0, denoting a positive impact on production. However, coefficient of previous year’s area is smaller than 0, implicating a negative influence on cotton production. In addition, the value of dry weight calculated is 1.94, which means no series auto-correlation exists. Despite this, it can be concluded from the regression results is that cultivating area and market price have time lag impacts on cotton production. Furthermore, price regulation has indirect positive impacts on cotton production. Key words: Cotton productivity, growth rate model, multi-regression.

Globally, all countries have producing different levels of carbon emissions and also facing both the problems of climate change and global warming due high carbon emissions in the atmosphere. Therefore, it is important to cutting carbon emissions in the atmosphere. This is only possible by switching to cleaner fuels, use of innovation technologies and development of carbon capture storages. These can substantially help the nations to reaching carbon neutrality. Given this background, this paper examines the effect of disaggregated energy consumption, technological innovations, capital on economic output and CO2 emissions in India for the period of 1990–2018. Based on empirical analysis, our long-run elasticities indicate that disaggregated energy consumption and technological innovations have a positive impact on economic growth, while renewable energy consumption and technological innovations have a positive impact on CO2 emissions. It implies that more use of energy consumption producing significant amount of CO2 emissions and by using renewable energy consumption and technological innovations (i.e. carbon capture storages) can significantly lowering CO2 emissions, which is clearly indicating that India has moving towards carbon neutrality. The causality analysis further indicates a unidirectional causal relationship running from disaggregated energy usage to economic growth and carbon emissions. These empirical findings suggest that the increased consumption of renewable power does not lead to rise carbon emissions, which, in turn, ensures sustainable economic growth.

The aim of this study is to investigate the green growth of cereal food production under the constraints of agricultural carbon emissions and area sown. A qualitative time-series data from 1985 to 2018 was used to analyze the Autoregressive distributed lag (ARDL), vector error correction model (VECM), and Novel dynamic ARDL models. The empirical results of the long-run and short-run nexus show that the increasing in area sown and food production index resulting to increase cereal food production. While agricultural carbon emission only confirms short-run significant negative effect and predicts that the decreasing agricultural carbon emissions will support to the increase of cereal food production. The novel dynamic ARDL model revealed that in long-run 10% positive change in agricultural carbon emission decreases cereal food production and a 10% decrease in agricultural carbon emission will steadily increase cereal food production. Besides, the VECM model results predict that bidirectional Granger causality runs from area sown and food production index to the cereal food production while unidirectional Granger causality exists from cereal food production to agricultural carbon emissions. Overall, conclusion the agricultural carbon emissions and area sown are accountable for reducing cereal food productivity. By switching from chemical fertilizers to organic fertilizers, farmers can enhance farm productivity in a healthy and sustainable environment.

The aim of this research is to address two emerging and relevant issues that have not been thoroughly investigated in the context of the Russian Federation. The first one is the increasing importance of natural gas and its competing role with Oil as a fossil fuel which should have a significant impact on the overall growth of the Russian Economy. The second issue is an asymmetric effect of natural resource utilization and rents earned on the economic growth which may result in the incorrect interpretation of either resource curse or resource blessings if not properly captured and identified. For this study time-series data from 1988 to 2019 was analyzed using nonlinear autoregressive distributed lag model (NARDL) model. The main findings of this research are surprisingly interesting and confirm the existence of a resource curse for Russia triggered by the positive shocks of natural gas rents. However, the shocks in oil rents which are broadly recognized as the main causes of resource course, tend to be a blessing, because both positive and negative have a positive effect on GDP growth. These findings have important policy consequences for the Russian economy, including how to limit natural gas supply in the face of high global demand and rising prices.

Increasing population and food demand has led to steadily declining resources as a result of over-exploitation and fossil fuel consumption that cause air contamination and reduce soil fertility. Therefore, this study aimed to investigate the correlation between air pollution, energy consumption, and the contribution of agriculture to national GDP. Secondary study data covering two decades were collected from different sources, and an autoregressive distributed lag (ARDL) bounds testing model was employed to determine long-run and short-run correlations. First, the unit root test was used to determine the stationarity of variables, and results showed that variables were integrated at level, ARDL co-integration equation estimation, which rejected the null hypothesis at less than 5% significance level. Further, based on the results of the ARDL bounds testing model, F-statistic values exceeded the upper bound value. This entire model was adjusted at a speed of −2.364 towards long-run equilibrium. In addition, CUSUM test and CUSUMSQ test results confirmed the goodness of fit of this model. In light of the resulting policy implications, the Chinese government may consider measures to improve the agricultural industry to meet the food demand for the fast-growing population while maintaining a healthy environment and safeguarding the available limited resources for future generations.

Waste sorting is the cardinal measurement to solve the problem of low efficiency of rural environmental governance and to alleviate environmental pollution by reduction, recycling, and harmlessness in rural areas. However, non-excludable and non-rival features of public goods easily cause a wide free-rider problem, which results in a low frequency of participation in the waste sorting of rural people. Based on the theory of the utility maximization of the rational economic man, this paper investigates survey data of 688 farm households in three cities and three counties of Shaanxi Province to explore the effect of the perceived value on the household waste classification behavior based on cost-benefit analysis. The results show that perceived benefit and perceived cost are important perceived value factors affecting farmers&rsquo, participation in waste sorting. Specifically, the spiritual benefit of the perceived benefit has a significantly positive impact on classification behavior, while the time cost, physical cost, and material cost of the perceived cost have a negative impact on waste classification behavior. Further study of the heterogeneity of income impact shows that time cost only has a significant impact on the high-income group of farmers&rsquo, classification behavior, while spiritual benefit and learning cost only affect the low-income group of farmers&rsquo, waste classification behavior. Material cost has different influence directions on high- and low-income groups. In view of the aforementioned findings, this study highlights corresponding policy implications from the perspective of perceived benefit and perceived cost.

A rich body of literature exists for explaining the role women play in ensuring their household’s food security; however, as far as their own food security is concerned, little attention has been given. Therefore, this research collects evidence on the relationship between women’s empowerment and their own food security (access) in the rural areas of Azad Jammu & Kashmir (AJK). Data were collected from the households of 600 rural women. The results provide insights that the domains of legal rights, information and communication technologies (ICTs), social support and familial rights, can be a significant pathway for enhancing the food security of women as more bargaining power of women over the utilization of resources could result in a good quality of food choices and more expense on food items due to these rights. Besides, understanding food insecurity also requires considering gender norms as in this study, the infrastructural facilities and sense of land entitlement provide unexpected non-significant results. Though women help in the mounting necessities of their families, they are unable to enhance the food requirements for themselves due to restricted mobility and less economic opportunities. This is mainly due to the poor infrastructure, and more importantly, the lack of access to resources, especially land, because of lack of knowledge and self-confidence. Notably, the fear of conflict and domestic violence may also impede women from fighting for their rights, which results in poor access to food. Hence, by understanding the household makeup from women’s perspectives and customs, the findings from this study can help and guide policymakers in developing more appropriate strategies to improve the food security of women.

The data for this empirical study were collected from three major cropping systems of Sindh province, and a total of 240 farmers were selected by simple random sampling technique. Cobb-Douglas production function was applied to analyze the data. Results show that in mixed cropping zone wheat yield increased with increasing ploughing, seed and plant protection. The dominant factors behind yield increase in the cotton-wheat cropping zone were ploughing, seed, fertilizer, and irrigation. Wheat yield in the Rice-wheat zone increased linearly with increasing ploughing, seed and fertilizer as well as plant protection measures. Further the results show that salinity and water logging are the driving threats leading to high water table in most regions of upper Sindh. Due to poor land management and improper irrigation strategies, the coefficient of irrigation shows negative value. Contrarily, lower Sindh needs canal irrigation water (i.e. Mixed and cotton-wheat zone), because most of the areas have unfit ground water for irrigation, thus increasing the soil erosion and salinity in lower Sindh. Furthermore, the cost of production estimated in cotton-wheat zone’s grower spends more USD$841/ha as compared to rice-wheat zone’s grower and Mixed cropping zone’s grower spend USD$827/ha and USD$780/ha. The growers of the whole Sindh spend USD$816/ha. In case of gross income cotton-wheat zone’s grower received higher than 1287, followed by the growers of mixed cropping zone and rice-wheat zone received USD$1248/ha and USD$1132/ha due to high cost of production. The overall Sindh growers received USD$1222/ha. In the case of net return grower of mixed cropping zones received higher USD$481/ha, compared to cotton-wheat zone’s and rice-wheat zone’s grower received USD$451/ha and USD$308/ha, respectively. The growers of the whole Sindh province received USD$413/ha net return from wheat crop. The production of wheat is lower as compared to cost. Therefore, net income of per acre and the production cost of per acre reduce with farm size, so increasing the use of inputs should assure the quantity and quality by the approach of growers. Keywords: Wheat farming, Economic analysis, Sustainable farming, Production function, Sindh Pakistan