Value Of Agricultural Output Research Articles

Forecasting Grain Production in Hubei Province Based on Markov Modeling

Abstract. Grain production plays a crucial role in economic and social development. Accurate prediction of grain production can help agricultural decision-makers allocate resources rationally and do a good job at the next stage of the arrangements for the deployment of the work.This article used the production data, which was from 2023 Hubei Provincial Statistical Yearbook,to simulate and predict the grain production for several years,with the method of Markov prediction. It can be seen from the results that the average fitting error of the model is 3.47%. Using the text dataset of grain production from 2020 to 2022, the results show that the model can effectively improve the prediction accuracy of agricultural grain procuction. Finally, the model is used to predict the agricultural output value structure of China from 2023 to 2027. Markov prediction can improve the predictability and initiative of the work and provide scientific basis for the future decision-making of agricultural managers, and has guiding significance for the work of grain storage and distribution.

Forecasting Grain Production in Hubei Province Based on Markov Modeling

Abstract. Grain production plays a crucial role in economic and social development. Accurate prediction of grain production can help agricultural decision-makers allocate resources rationally and do a good job at the next stage of the arrangements for the deployment of the work.This article used the production data, which was from 2023 Hubei Provincial Statistical Yearbook,to simulate and predict the grain production for several years,with the method of Markov prediction. It can be seen from the results that the average fitting error of the model is 3.47%. Using the text dataset of grain production from 2020 to 2022, the results show that the model can effectively improve the prediction accuracy of agricultural grain procuction. Finally, the model is used to predict the agricultural output value structure of China from 2023 to 2027. Markov prediction can improve the predictability and initiative of the work and provide scientific basis for the future decision-making of agricultural managers, and has guiding significance for the work of grain storage and distribution.

Effects of Agricultural Insurance on Water Pollution in China

Water pollution is the most serious environmental problems in China now, water pollution directly affects people's quality of life and the sustainable development of agriculture, and the biggest source of water pollution is agricultural non-point source pollution, so we need to pay more attention to the environmental impact of agricultural production and reduce agricultural non-point source pollution. This paper examines the environmental impact of agricultural insurance on water pollution. Using annual data from 30 provinces across China between 2011 and 2019, this paper employs a two-way fixed-effects model to examine the correlation between agricultural insurance development and agricultural pollutant emissions. Additionally, it takes agricultural carbon emissions and agricultural output value as dependent variables to comprehensively investigate the environmental and economic impacts of agricultural insurance. The research results indicate that the development of agricultural insurance has a significant effect on reducing agricultural water pollution and carbon emissions. The pollutant reduction effect is more significant in the major grain-producing areas. The positive environmental effect of agricultural insurance is based on the fact that the development of agricultural insurance is conducive to reducing the use of pesticides and chemical fertilisers and does not come at the expense of increased agricultural output.

Response Mechanism and Evolution Trend of Carbon Effect in the Farmland Ecosystem of the Middle and Lower Reaches of the Yangtze River

The farmland system in the global terrestrial ecosystem has dual attributes as both a carbon source and a carbon sink, playing a crucial role in controlling carbon emissions and mitigating global warming. Using carbon source and sink accounting of farmland ecosystems, we applied methods such as standard deviation ellipse, Tapio decoupling theory, and Markov chain to analyze the spatiotemporal changes, response mechanisms, and evolutionary trends of regional carbon effects. The results indicated that from 2011 to 2021, the farmland ecosystem in the middle and lower reaches of the Yangtze River consistently acted as a carbon sink. However, the net carbon sink showed slight fluctuations and significant spatial differences. The migration range of the net carbon sink center in the farmland ecosystem of the middle and lower reaches of the Yangtze River was relatively small, ranging from 115.52 to 115.77° E and 30.14 to 30.27° N. The decomposition of the Tapio decoupling index between the net carbon sink of the farmland ecosystem and agricultural output value showed the order of effects on their coupling relationship as follows: agricultural mechanization level > agricultural mechanization efficiency > agricultural output value > planting scale. The probability of maintaining the original state of net carbon sink in various cities in the middle and lower reaches of the Yangtze River (over 77%) was much higher than the probability of transfer, making it difficult to achieve a leapfrog growth in net carbon sink. The net carbon sink at the city scale exhibits the Matthew effect and spatial spillover effect. The above research results clarify the spatiotemporal changes in carbon effects in agricultural production at multiple levels, including city, province, and region. They also provide a theoretical basis for formulating differentiated regional emission reduction and sink enhancement strategies in the middle and lower reaches of the Yangtze River, promoting the rapid development of low-carbon agriculture in China.

Forecasting the Total Output Value of Agriculture, Forestry, Animal Husbandry, and Fishery in Various Provinces of China via NPP-VIIRS Nighttime Light Data

Forecasting the Total Output Value of Agriculture, Forestry, Animal Husbandry, and Fishery in Various Provinces of China via NPP-VIIRS Nighttime Light Data

Estimation of phosphorus input on county-based scale is more appropriate to formulate phosphorus management policies

The excessive phosphorus input generated by human activities has broken the nutritional balance of ecosystem. This study focused on the Three Gorges Reservoir Region, where human activities are concentrated. It involved the innovative selection of county subunits to provide a clearer analysis of different components contributing to net anthropogenic phosphorus input (NAPI) and factors impacting it on a smaller scale, opening up a new horizon for more accurately formulating phosphorus management policies. The results showed that NAPI of the reservoir region maintained a high level (2641.84 kg·km−2·a−1), while showing significant spatial variation due to high input (>4200 kg·km−2·a−1) at an urban agglomeration in the reservoir region. Phosphorus fertiliser made the largest (63 %–64 %) contribution to NAPI in the reservoir region, but different compositions of the component determining NAPI were shown among the counties. The sensitive coefficient (2.36) of phosphorus fertiliser in the reservoir region was the largest, the sensitive coefficients and proportional contributions in counties also varied among the counties. The findings of this study showed that reducing the input of phosphorus fertiliser and improving the utilization rate of phosphorus are direct methods for reducing NAPI in the Three Gorges Reservoir Region. Furthermore, improving the methods of treating human domestic waste and sewage can alleviate the high input pressure of phosphorus. The spatial differentiation of NAPI in the analyzed counties was mainly affected by the increase in phosphorus fertiliser and gross output value of agriculture, along with increasing urbanization, population densification, and greater economic activity in Chongqing compared with the other counties. Moreover, the components, sensitivities, contributions and impact factors in the counties were heterogeneous due to socio-economic, agricultural, and geographical characteristics, so it might be more appropriate to formulate phosphorus management policies on a smaller county-based scale.

Article Review: Relationship between Toxoplasmosis and other Diseases

Water provision is sensitive to climate change, and agricultural production and food supply are sensitive to water availability. Water scarcity affects food security and agricultural economic development through changes in agricultural production and changes in the composition of produced goods. Recent droughts also led to a decrease in the volume of water allocated to agriculture, which led to a decrease in total agricultural production and exports, and this has subsequent impacts on food security and economic development. The research aimed to measure the impact of water scarcity on agricultural economic development for the period 1990-2022. The research included three behavioral equations with three endogenous variables: the cultivated area, the value of agricultural output, and the value of gross domestic product, and four exogenous variables: the amount of available water, agricultural labor, and the value of agricultural investments and the income of other sectors, the studied model is called the sequential model, which was estimated using the Recursive method, using the ordinary least squares (OLS) method. The results indicated that increasing the amount of available water will lead to an increase in the cultivated areas by 141,129.2 dunums, and that increasing one thousand dunums of the cultivated area will increase agricultural output by 0.00821, and that agricultural labor is inversely proportional to agricultural output. It became clear that if the income of the rest of the sectors increased by one unit, the domestic product would increase by 0.1873. Water scarcity will reduce cultivated areas, which in turn will decrease agricultural output, causing the value of agricultural output to decrease and its contribution to the gross domestic product to decrease. In turn, it will have serious repercussions on agricultural economic development. Therefore, the research recommends the necessity of integrated water management and improving the efficiency of its use, as well as the application of modern technologies in agriculture, such as sprinkler irrigation, hydroponics, and redrawing crop compositions to ensure maximizing the net return per unit of water.

An Econometric Study of the Factors Affecting the Value of Agricultural Output in Iraq for the Period 2000-2022

An Econometric Study of the Factors Affecting the Value of Agricultural Output in Iraq for the Period 2000-2022

Impacts of climate change and agricultural diversification on agricultural production value of Thai farm households

This paper examines how rising temperatures impact the agricultural production value of Thai farmers, compares potential adaptation strategies like agricultural diversification, and analyzes future projections based on IPCC AR6 scenarios. We analyze nationally representative socioeconomic survey data from farm households alongside ERA5 weather data, utilizing econometric regression analysis. Our analysis reveals that higher temperatures lead to a reduction in agricultural output value, with the situation expected to worsen as global warming progresses. Furthermore, we find that households with diversified production practices, such as a variety of agricultural activities or multicropping, exhibit a greater capacity to adapt to rising temperatures. These findings substantiate the importance of the country’s policies promoting integrated farming and diversified crop-mix strategies.

Exploring the Chinese public's affective attitudes towards digital transformation in agriculture: A social media-based analysis.

This study utilizes natural language processing techniques and panel vector autoregression methodology, to delve into the perceived attitudes of social media users towards the digital transformation of agriculture, and to assess its impact on total agricultural output and agricultural science and technology inputs. Data related to agricultural digital transformation were collected from Sina Weibo using web crawlers. The SnowNLP model was employed to infer users' attitudes, encompassing both positive and negative aspects. Furthermore, the study delves into the specific themes capturing users' positive attitudes and explores regional variations in focus. The findings reveal a sustained increase in users' interest in agricultural digital transformation since 2013. Positive attitudes primarily center around green development, agricultural intelligence, and global cooperation and innovation. Moreover, the study establishes a significant positive impact of users' positive attitudes on both total agricultural output value and agricultural science and technology investment, highlighting the constructive influence of user support on the agricultural industry's development.

Measurement and evaluation of agricultural technological innovation efficiency in the Yellow River Basin of China under water resource constraints

Improving the efficiency of agricultural technology innovation is an inevitable requirement for ecological protection and sustainable agricultural development in the Yellow River Basin. Under the background of prominent water resources constraints in the Yellow River Basin, the actual level and regional differences of agricultural technology innovation efficiency in the basin are analyzed, which will provide theoretical basis and data reference for the development plan of agricultural modernization in the Yellow River Basin. The construction of evaluation index system and the choice of method are the main factors that affect the measurement results. Therefore, this paper first selects input indicators such as water-saving technology level and output indicators such as total agricultural output value to construct an innovative evaluation index system of agricultural technology innovation efficiency in the Yellow River Basin under the consideration of water resources constraints. Secondly, the three-stage DEA model was used to eliminate the interference of external environmental variables, and the overall and regional agricultural technology innovation efficiency of the Yellow River Basin during 2011–2020 was measured with the data of prefecture-level cities under the constraint of water resources. Finally, from the perspective of the whole and the region, the spatio-temporal dynamic evolution law is analyzed and evaluated. The results show that: on the whole, the agricultural technology innovation efficiency in the Yellow River Basin is good and rising in a wave trend, the adjusted pure technology efficiency increases, while the scale efficiency decreases. From the regional perspective, although there is regional heterogeneity, the overall development trend is good, and the lower Yellow River has the highest efficiency, followed by the upper reaches and the middle reaches. From the perspective of the change law, the spatio-temporal evolution distribution shows a multi-polarization trend, and the different regions in the upper, middle and lower reaches show great differences. Therefore, promoting the innovation of water-saving technology and the integration of agricultural science and technology, promoting the integration of production, study and research, and strengthening the regional linkage mechanism are helpful to improve the competitiveness of agricultural science and technology and achieve sustainable agricultural development in the Yellow River Basin.

Research on the impact of climate change on the income gap between urban and rural areas-empirical analysis based on provincial panel data in China.

Narrowing the income gap between urban and rural areas is the key to achieving common prosperity in China. On the basis of analyzing the mechanism of climate change's impact on urban-rural income gap, this article empirically analyzes the impact of climate change on urban-rural income gap using provincial-level panel data of 30 provinces in China from 2011 to 2020. Research indicates that climate change significantly impacts the urban-rural income gap at the 1% significance level, implying that climate change exacerbates the urban-rural income gap. This widening effect varies significantly across different regions, particularly in the western regions and areas with lower fiscal support for agriculture. Further analysis reveals that there is a mediating role between the total agricultural output value and resource mismatch in the impact of climate change on urban-rural income inequality; the digital rural construction plays a regulatory role in the impact of climate change on the urban-rural income gap. On this basis, policy recommendations are proposed to promote the development of climate-resilient agriculture, improve the meteorological forecast and early warning system, increase financial support, and optimize the allocation of agricultural resources.

Dynamic Energy Use Efficiency, Carbon Input, and Agricultural Benefits of Multiple Cropping in Southern China—A Case Study from Guangdong Province

Background: With the purpose of exploring the development of new quality productive forces in Guangdong, the present study hypothesized that reducing energy and carbon inputs was beneficial for increasing Guangdong’s multi-cropping agricultural energy output and economic returns. Methods: The energy use efficiency of crop production and the corresponding carbon input and agricultural benefit trends from 2011 to 2021 were examined by linear regression analysis for Guangdong Province, China. The corresponding development trends were also predicted using a grey model. Results: The results indicated that the total energy output increased by 12.50%, wherein the energy productivity levels of peanuts, vegetables, mulberry, and fruits increased greatly (51.27–106.17%), while the total energy input and the total carbon input decreased by 12.17% and 6.37%, respectively. Moreover, the energy input per carbon input decreased by 6.19%, while the energy output per carbon input increased by 20.15%. Both energy-related indicators and economic-related indicators all had substantially increased (28.08–44.97% and 83.86–120.91%, respectively). Grey model predictions show that the agricultural output value increased steadily under the current agricultural policy of reducing fossil energy input. Conclusions: The current low-carbon and high-output agricultural model is beneficial for increasing Guangdong’s multi-cropping agricultural economic returns and mitigating greenhouse effects.

Damping accumulated discrete MGM(1, m) power model and its application to forecasting agricultural output value share and employment share

PurposeThe damping accumulated discrete MGM(1, m) power model is proposed for the problem of forecasting the share of agricultural output value and the share of employment in China.Design/methodology/approachIn this study, the damping accumulated discrete MGM(1, m) power model was developed based on the idea of discrete modelling by introducing a damping accumulated generating operator and power index. The new model can better identify the non-linear characteristics existing between different factors in the multivariate system and can accurately describe and forecast the trend of changes between data series and each of them.FindingsThe validity and rationality of the new model are verified through numerical experiment. It is forecasted that in 2023, the share of agricultural output value in China will be 7.14% and the share of agricultural employment will be 21.98%, with an overall decreasing trend.Practical implicationsThe simultaneous decline in the share of agricultural output value and the share of employment is a common feature of countries that have achieved agricultural modernisation. Accurate forecasts of the share of agricultural output value and the share of employment can provide an important scientific basis for formulating appropriate agricultural development targets and policies in China.Originality/valueThe new model proposed in this study fully considers the importance of new information and has higher stability. The differential evolutionary algorithm was used to optimise the model parameters.

Empirical study on factors influencing farmers' income in Zhaoqing City

A significant portion of farmers' income comes from the primary industry. Based on time series data from 1985 to 2020, this study empirically examines the relationship between farmers' real income in Zhaoqing City and the actual output value of agriculture, forestry, animal husbandry, fishery, and service industry using methods such as unit root test, cointegration analysis, elimination of multicollinearity, and elimination of serial correlation. The results show that: · Animal husbandry and fishery have no significant impact on farmers' real income in Zhaoqing City; · Agriculture, forestry, and the agricultural, forestry, animal husbandry, and fishery service industry have a significant impact on farmers' real income in Zhaoqing City. Specifically, for every 100 million yuan increase in the output value of agriculture, farmers' per capita disposable income increases by an average of 0.0717%; for every 100 million yuan increase in the output value of forestry, farmers' per capita disposable income increases by an average of 0.1056%; for every 100 million yuan increase in the output value of the agricultural, forestry, animal husbandry, and fishery service industry, farmers' per capita disposable income increases by an average of 0.0858%; · The impact has a significant positive effect with a lag of 3 years. Based on the research findings, some policy recommendations are provided.

An Empirical Study on the Relationship between Farmers' Income Increase and Primary Industry in Zhanjiang City

This article briefly introduces the 25 themes of the "No. 1 Document" of the CPC Central Committee. Based on the data of farmers' income, agriculture, forestry, animal husbandry and fishery, and agriculture, animal husbandry and fishery service in Zhanjiang City, Guangdong Province from 1978 to 2021, this paper conducted an empirical study on the relationship between the primary industry and farmers' income in Zhanjiang City. In the empirical analysis, first of all, the stationarity test of the data was carried out, the EG co-integration modeling was carried out, the stepwise regression method was used to eliminate multicollinearity, and the generalized difference method was used to eliminate sequence correlation, and the optimized model was obtained. The results show that the total output value of agriculture and fishery has no significant effect on the increase of farmers' income in Zhanjiang City. Forestry, animal husbandry, agriculture, forestry, animal husbandry and fishery services have a significant impact on farmers' income. The total output value of forestry, animal husbandry and agriculture and the service industry of forestry, animal husbandry and fishery increased by 1%, and the income of farmers increased by 0.429%, 0.240% and 0.619%, respectively. The impact of agriculture and fishery on per capita disposable income in Zhanjiang rural areas is lagging, with a maximum lag of 9 years. Accordingly, the corresponding policy suggestions are put forward.

A synergistic study on farmers’ income enhancement and urban-rural financial development under the perspective of common wealth by an intelligent decision support system for land improvement

Abstract This paper proposes the general framework and technical process of the intelligent decision support system for land improvement based on a multi-objective artificial immunity algorithm. Based on the analysis of the current situation of land use structure and spatial layout in County S, three land resource quantity structure optimization schemes are selected, and the improvement of agricultural land use efficiency and agricultural output value in the three schemes are evaluated and analyzed. The mechanisms that affect income distribution in urban-rural financial development and land finance are summarized. The results show that after land improvement, the area of cultivated land and grassland in County S decreased by 1,444 ha, and the area of garden land and forest land increased to the greatest extent in the economically prioritized scenario. The size of towns increased to 541 ha, and the size of villages decreased to different degrees and all three land improvement programs had the combined effect of increasing the gross agricultural product and boosting farmers’ incomes. The development of urban and rural finance is aided by land improvement, but the degree of inequality in income distribution is widened.

Research and Forecast of Agricultural Output Value Based on SPSS Software

Research and Forecast of Agricultural Output Value Based on SPSS Software

The Impact of Digital Inclusive Finance on Agricultural Carbon Emission Reduction Analysis Based on Panel Data of 54 Prefecture-Level City

Based on the national ranking of the total agricultural output value, this paper selects Shandong, Henan, and Sichuan, which are in the top three, as the representatives of large agricultural provinces, and utilizing panel data from 54 prefecture-level cities throughout the three provinces for the years 2011 to 2020, this study thoroughly applies the fixed effect model, mediating effect model, and moderating effect model to examine the influence of digital inclusive finance on agricultural carbon emission reduction. The findings demonstrate that inclusive digital finance reduces agricultural carbon emissions favorably; the three sub-dimensions of the breadth of coverage, the depth of use, and the degree of digitization all have significant promoting effects on agricultural carbon emissions reduction, of which the breath of coverage has the most obvious effect; compared to the primary regions that produce grains, In non-primary grain-producing zones, the promotion effect of digital inclusive finance on agricultural carbon emission reduction is particularly significant. From the perspective of the mediating effect, agricultural decreases in carbon emissions can benefit from increased regional innovation thanks to digital inclusive funding; from the perspective of the moderating effect, the amount of urbanization is taken advantage of by digital inclusive finance to control the effects of crop reductions in carbon emissions.

Temporal and Spatial Changes of Agriculture Green Development in Beijing’s Ecological Conservation Developing Areas from 2006 to 2016

As an irreplaceable ecological barrier, an ecological conservation developing area (ECDA) is vital for the integrated construction of urban and rural areas and the optimization and adjustment of industrial structures. However, few empirical studies have been conducted on the spatiotemporal variations of agricultural green development (AGD) in the ECDAs of large cities. Based on the green agricultural traits of Beijing and the accessible data, we evaluated the AGD and analyzed its spatial and temporal heterogeneity in Beijing’s ECDAs by constructing a framework with 13 indicators. The results stated that energy consumption is a vital factor in green agriculture production and that the agricultural output value per unit of arable land area is the key to green agricultural revenue. From 2006 to 2016, the AGD index of the ECDA had an increasing trend, until 2012 when it followed a decreasing tendency. The AGD index of the northern region was higher than in the southern ECDA. The obstacle degree model was used to verify the AGD limiting factors, where poor infrastructure, slow agritourism, low labor productivity, and low resource use efficiency varied by districts in the ECDA. Given these findings, our study is conducive to AGD evaluation at the district (county) level for the ECDAs of large cities and provides important policy implications.