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In this paper, Delphi method was used to evaluate the low-carbon technologies and measures for high agricultural carbon productivity in Taihu Lake Basin. We established the selecting process and standards and obtained the final list of low-carbon technologies and management measures of high agricultural carbon productivity in Taihu Lake Basin: (1) the initial list of low-carbon technologies and measures of planting industry included 19 items, of which 10 items were included in the final list. The 10 technologies and measures included in the final list were reducing fertilizers, mixed use of organic fertilizer and chemical fertilizer, soil testing and formulated fertilization, application of controlled release fertilizer, deep application of fertilizers, cultivation of new variety, extension of conservation tillage, extension of midseason/alternate drainage, paddy-upland rotation (rice-rape/rice-wheat), and reducing pesticides. (2) The initial list of low-carbon technologies and measures of animal husbandry included 11 items, of which 4 items were included in the final list. The 4 technologies and measures included in the final list were reasonable ratio of concentrate to roughage in ration, treatment straw feed by silage/ammoniation/shredding, application of nutritive cube/dietary additives, and promotion of high productivity livestock breeds. (3) Low-carbon agricultural technologies and management measures need to be adapted to local conditions according to different geographical, climatic, and socio-economic development characteristics, and it is necessary to form a regionally differentiated system of low-carbon agricultural technologies and management measures. The final list of low-carbon technologies and management measures of high agricultural carbon productivity can provide decision-making reference for the formulation of agricultural carbon emission reduction technology system and low-carbon agricultural development planning of provinces and cities in Taihu Lake Basin. At the same time, the final list can be considered a priority for the promotion of agricultural low-carbon technologies and measures in China and even in the world. [ABSTRACT FROM AUTHOR]

Climate change poses an urgent threat, necessitating the implementation of measures to actively reduce carbon emissions. The development of effective carbon emission reduction policies requires accurate estimation of the costs involved. In situations where actual prices of commodities are not available in the market, shadow pricing provides a useful method to calculate relative prices between commodities with and without price information. However, most studies focus on the industry, with few contributions on agricultural sector. This paper estimates the shadow price of carbon emissions in the agricultural sector from a provincial perspective, incorporating the impact of livestock into the calculation of carbon emissions and shadow pricing. Our findings indicate that ignoring livestock may overestimate CSP values. On the whole, the level of carbon shadow price is rising, indicating good green development in China's agricultural sector. The two types of convergence results show that there is sigma convergence and beta convergence in the western and central regions, demonstrating a significant improvement in environmental performance. [ABSTRACT FROM AUTHOR]

The high-quality development of agriculture requires not only sustainable growth of agricultural productivity but also green agricultural production. Internet technology has played an essential role in agricultural production and marketing in China over the past decades. This paper estimates provincial agricultural green growth in China from 1997 to 2019 and decomposes it into technological progress (TP) and efficiency changes (EC) based on the Luenberger productivity indicator method. Then an econometric model is employed to analyze the impact of the Internet on the growth of agricultural green productivity and each sub-component, and moderating role of farmer education in such effect. The empirical results indicated that annual average growth rate of agricultural green productivity in China is 1.33% from 1997 to 2019, and technological progress dominates its growth. The development of Internet technology has a significant positive impact on agricultural green productivity and its decomposition. Farmer education has strengthened the effect of Internet technology on agricultural green productivity and its decomposition TP and EC. [ABSTRACT FROM AUTHOR]

Multi-criteria decision-making (MCDM) is an important means for evaluating resources and environment, and sensitivity analysis can enhance understand the robustness of evaluation results. Spatial visualization has been used in sensitivity analysis of MCDM, but the sensitivity results are still generally summarized by presenting traditional statistical measurements that omit the spatial information. To address this issue, this paper proposed a novel spatially measurement approach of sensitivity analysis by introducing the spatial barycenter model (SBM), which overcame the limitations of existing statistical methods and provided the spatial directivity of uncertainty for the MCDM results. According to our proposed method and its application in farmland quality evaluation (FQE) in an arid area of China, the mean of the absolute average change rate (MACR) and the SBM were applied to test the sensitivity of farmland quality to different evaluation factors from both numerical and spatial perspectives. From the numerical perspective, the soil organic matter and irrigation capacity were the most sensitive factors determined by the MACR. From the spatial perspective, the ≥10 °C accumulated temperature (AT) and precipitation were the most sensitive factors measured by the SBM. Based on the SBM, the spatial configuration of farmland quality index was most sensitive to increase of AT in a northwesterly direction. Calculating the SBM is computationally inexpensive and provides a straightforward indication of spatial direction for the changes of FQE results with changes of parameters. This means it can provide improved understandings and new insights into the comprehensive measurement of sensitivity analysis and agricultural production layout. [ABSTRACT FROM AUTHOR]

The mechanism of the non-agricultural transfer of rural labor to agricultural production efficiency and their interrelationships is a problem worthy of further discussion at this stage in China. The mediating effect model is constructed, the least square method is used for regression, and the instrumental variable method is used to solve the possible endogeneity problem. Through the investigation of farmers in Loess Plateau region, this paper analyzes the effects of factor substitution and planting structure adjustment after agricultural labors work outside and its impact on agricultural land output from the theoretical and empirical aspects, as well as the impact of off-farm employment on agricultural land output under different constraints. Results showed that the negative influence of labor non-agricultural transfer on farmland land output rate is − 7.264, and farmers' participation in returning farmland to forests can alleviate the negative impact of non-agricultural transfer on the agricultural land output. Labor substitution factor investment plays a part in the mediating effect, and part of the mediating effect is − 0.879. The adjustment of agricultural planting structure plays the whole mediating effect, that is to say, the larger the scale of labor non-agricultural transfer in Loess Plateau area, the more unfavorable for farmers to invest in labor substitution agricultural factors of production, and the more they are inclined to grow food crops. When the constraint conditions of factor substitution difficulty and planting structure adjustment space are considered, the higher the factor substitution difficulty is, the smaller the planting structure adjustment space; the negative effect of the non-agricultural transfer of labor on the agricultural land output rate is more obvious. It provides effective reference value to judge the development stage and trend of regional agriculture and puts forward relevant policy suggestions to guarantee the development of regional agriculture and farmers' life. [ABSTRACT FROM AUTHOR]

The crop water relationship quantification is conducive to decision-making for regional food safety and resource conservation. However, irrigation water and crop water footprint (CWF) was observed separately in previous studies, which leads to incomplete evaluation of water resource occupation in agricultural system. The crop water resource use (WRU), combining WF and irrigation water accounting, in 31 provinces of China from 1999 to 2018 was estimated in current paper. The driving forces of WRU were analyzed using the logarithmic mean divisia index (LMDI) model, based on its spatial and temporal patterns demonstration. The results showed that national WRU increased from 1051.6 Gm3 in 1999 to 1676.4 Gm3 in 2018, with an average annual growth rate of 2.48%. The provinces with high WRU were mainly distributed in North China and Northeast China. Hebei, Shandong, and Henan jointly contributed 28.9% of the national WRU. In addition, economic level was the largest contributor to promote the growth of WRU, and water use intensity was the most important contributor to inhibit the growth of WRU. Economic level, resource endowment, and population size had a promoting effect on WRU in Northeast, Northwest, North China, and Southeast provinces, while water use intensity, irrigation technique, and urbanization degree showed inhibitory effect in Northeast, Northwest, and Southwest provinces. It is meaningful to combine water footprint and irrigation water use for agricultural water management and conservation. The arid North China Plain should adopt water-saving irrigation and rainwater recycling technologies to control WRU, and the Northeast granary should reduce WRU by strengthening water pollution prevention and improving water resources scheduling to ensure food security and sustainable use of water resources. [ABSTRACT FROM AUTHOR]

The climate change on the impact of grain production potential has significant regional differences. Researchers have studied the grain production potential of various crop combinations or focused on single crop types in a typical area; however, the regional differences of the climate change on the impact of grain production potential were neglected. This paper used the Global Agro-Ecological Zone (GAEZ 3.0) model to focus on the analysis what is the climate change on the impact of grain production potential in different geographic units (Northern Shaanxi Plateau, Guanzhong Basin, Qinba Mountain) in Shaanxi Province of China. The case showed that the precipitation (Pre) what made changes of grain production potential was the most important factor in different geographic units. The increase of Pre had a positive impact on the grain production potential in Northern Shaanxi Plateau and Guanzhong Basin. However, in Qinba Mountain, due to excessive Pre in the Qinba Mountains, the decrease of Pre had a certain positive impact on the grain production potential. The precipitation was less in the Northern Shaanxi Plateau; therefore, its major factors leading to changes of crop production were precipitation and rainfall days. The increase of the mean maximum temperature (Tmx) and the mean minimum temperature (Tmn) had a positive impact of the grain production potential in the Northern Shaanxi Plateau and Guanzhong Basin. The higher temperature had a negative impact on the grain production potential. In Qinba Mountain, the increase of the temperature has a certain negative impact on the grain production potential. It has more influence of Tmx in the Guanzhong Basin and Qinba Mountain rather than that in the Northern Shaanxi Plateau. Generally speaking, the major climatic factors leading grain production potential were Pre and Tmx in Guanzhong Basin and Qinba Mountain. [ABSTRACT FROM AUTHOR]

Sustainable agricultural technologies are of great significance in fully utilizing agricultural resources and promoting agricultural production. However, the adoption rates of these technologies are often characterized as low in rural areas in China. To figure out the potential salient determinants of rice farmers' willingness to adopt sustainable agricultural technologies, this paper, by employing the multivariate probit model and ordered probit model, particularly and firstly explores the roles of observational learning and experience-based learning through communication from parents within the household on rice farmers' willingness to adopt these technologies. Results show that there are strong complementarities and substitutabilities between sustainable agricultural technologies that rice farmers are willing to adopt, and that observational learning and experience-based learning through communication within the household do have pronounced effects on rice farmers' willingness to adopt some sustainable agricultural technologies and on their intensive use intentions. Therefore, while formulating policies to improve the adoption rates and adoption intensity of these technologies, relevant government agencies should take the complementarities and substitutabilities between sustainable agricultural technologies as well as observational learning and experience-based learning through communication from parents into consideration. [ABSTRACT FROM AUTHOR]

Climate, topography, and landscape patterns affect river water quality through processes that influence non-point source pollution. However, little is known about the response of the water quality of rivers on China's Tibetan Plateau to these environmental factors. Based on the water quality parameters data of the Xoirong River on the Tibetan Plateau in western China, the redundancy analysis and variation partitioning analysis were adopted to determine the main influencing factors affecting river water quality and their spatial scale effects. The major water pollutants were further analyzed using the partial least square-structural equation modeling (PLS-SEM). Another mountainous river with a similar latitude, the same stream order, and low anthropogenic disturbance in central China, the Jinshui River, was also selected for comparative discussion. The results indicated that the overall river water quality on the Tibetan Plateau was superior to that of the Jinshui River. At the catchment scale, the cumulative explanatory powers of the influencing factors of both rivers were greatest. Landscape composition and configuration were the determinant factors for the overall water quality of the two rivers, while the river on the Tibetan Plateau was also significantly affected by climatic and topographical factors. Regarding the main water quality issue, i.e., total nitrogen, agricultural production activities might be the main cause of the river on the Tibetan Plateau. This study unveiled that the river water quality on the Tibetan Plateau is sensitive to climate and topography through comparative studies. [ABSTRACT FROM AUTHOR]

Cultivated land fragmentation (CLF) has severely affected China's agricultural production efficiency, large-scale operations, agricultural modernization, and food security. Exploring the spatiotemporal evolution patterns and driving forces of CLF is crucial for agricultural modernization. However, the driving forces of CLF in different agricultural regions in China still need to be clarified. In this study, CLF was measured in 2000, 2010, and 2020 based on remote sensing data with landscape pattern metrics, and the driving forces of spatial differentiation were detected based on a geographical detector model. The overall cultivated land area has slightly declined during the study period while the CLF has intensified. CLF showed significant spatial autocorrelation, with CLF increased-cultivated land decreased (2000 to 2010) and CLF decreased-cultivated land decreased (2010 to 2020). The contribution rate of land use intensity on CLF was the highest among all agricultural regions, excluding the Qinghai Tibet Plateau. In contrast, the contribution rates of other factors significantly varied across agricultural regions. These findings provide scientific support in formulating policies to conserve cultivated land for sustainable use of agricultural resources and CLF management in China. [ABSTRACT FROM AUTHOR]

This study uses Chinese rural household data to examine the relationship between environmental regulation and farmers' income. The study found that environmental regulation has the most apparent promotion effect on farmers' agricultural production income. However, the effects on self-employment and non-farm employment are insignificant. In addition, the increase in agricultural green total factor productivity is a channel for environmental regulation to promote agricultural production income. The stronger the farmers' awareness of environmental protection, the more significant the effect of environmental regulation on agricultural production income increase. In China, the effect of environmental regulations on farmers' income from agricultural production is most significant in the central region, followed by the eastern region. In the western region, environmental regulations do not affect agricultural production income. Finally, we discuss the different impacts of industrial and agricultural environmental regulations on farmers' income. Results show that agricultural environmental regulation affects agricultural production income. By contrast, industrial environmental regulations affect farmers' self-employment and non-farm income. [ABSTRACT FROM AUTHOR]

Agricultural production outsourcing services (APOS) are an important means to promote green and low-carbon development of agriculture in China. Topography is the key factor limiting the development of APOS. There is little research on the influence relationship between APOS and farmers' chemical fertilizer use from the perspective of topography. Based on the theory of economies of scale, this study empirically evaluated the effect of APOS on chemical fertilizer use and their differences from the perspective of nutrient elements under different topographic conditions by using micro survey data for farmers in China and econometric methods. The results show that APOS can reduce farmers' chemical fertilizer use, and this effect is more obvious for farmers with large farmland sizes and high education levels. Farmland topography directly affects the fertilizer reduction effect of APOS in China. Compared with plain areas, hilly and mountainous areas weaken this effect. To enhance the fertilizer reduction effect of APOS, China should fully consider farmland topography when promoting APOS development. In plain areas, farmland scale management should be further encourage to better utilize APOS as a means of reducing chemical fertilizer use. In hilly and mountainous areas, high-standard farmland construction and small agricultural machinery use can alleviate the constraints of topographical on the scale expansion of APOS. It is necessary to fully consider the differences in farmers' resource endowments and their awareness of purchasing agricultural services in promoting APOS development, especially in regard to the farmers with small farmland sizes and low education levels. [ABSTRACT FROM AUTHOR]

Urbanization and land transfer have triggered a profound reform of the Chinese agricultural sector since reform and opening, leading to a continuous rise in agricultural carbon emissions. However, the impact of urbanization and land transfer on agricultural carbon emissions is not widely understood. Therefore, based on the panel data covering 30 provinces (cities) in China from 2005 to 2019, we adopted a panel autoregressive distributed lag model and a vector autoregressive model to empirically explore the causal relationship between land transfer, urbanization, and agricultural carbon emissions. The main conclusions are as follows: (1) Land transfer can significantly reduce carbon emissions from agricultural production in the long run, while urbanization has a positive effect on agricultural carbon emissions. (2) In the short run, land transfer has a significant positive impact on agricultural carbon emissions, and urbanization also has a positive impact on the carbon emissions of agricultural production, but in insignificant ways. (3) There is two-way causality between land transfer and agricultural carbon emission, and between urbanization and land transfer is the same, but urbanization is the one-way Granger cause of agricultural carbon emissions. Finally, some suggestions are provided for low-carbon agriculture development: the government should encourage the transfer of land management rights and guide high-quality resources to gather in green agriculture. [ABSTRACT FROM AUTHOR]

Increasing food output while reducing agricultural carbon emissions (ACE) is a major challenge to achieving green agriculture in China. Previously unexplored research regarding the relationship between agricultural production outsourcing services (APOS) and ACE is investigated using household microsurvey data in China and econometric methods, and the influencing mechanism is also tested empirically. The results reveal that APOS increases the total ACE and reduces ACE per unit area. The mechanism test shows that APOS are beneficial to the expansion of rice planting areas and farmers' adoption of agricultural green production techniques. The increasing effect of rice planting area on ACE was greater than the decreasing effect of green production techniques. In the future, China should accelerate the selection and breeding of rice varieties with low carbon emissions to reduce the increase of ACE caused by large-scale land management in the process of APOS development. Policy support and subsidies should be strengthened for APOS organizations to purchase green production techniques, so as to further drive farmers to adopt green production techniques and reduce ACE. It is also necessary for China to encourage small-scale farmers to outsource their agricultural production activities to APOS organizations. The role of collective action consciousness of agricultural production in increasing the supply capacity of APOS organizations should be enhanced. [ABSTRACT FROM AUTHOR]

With the improvement of industrialization, numerous rural laborers migrate to urban areas in search of off‐farm jobs. Farmers change agricultural production decisions to adapt to the change of labor force, which will inevitably affect the crop planting structure. However, few studies have explored the sustainability of crop planting structure. Based on the calculation of the multiple cropping index (MCI), grain crops planting rate (GCR), economic crops planting rate (ECR), and ecological sustainability index (ESI) of crop planting structure, this study analyzes the impact of labor transfer rate (LTR) and labor cost (LC) on the sustainability of crop planting structure using a geographically and temporally weighted regression (GTWR) model. The results show that the scale of rural labor transfer and labor cost in China remains on the rise, but the growth rate has slowed down. The total carbon absorption of crops in China shows a U-shape trend, and the rice and maize have the largest carbon absorption. The impact of LTR on MCI is mainly positive, especially in the North China Plain in the early stage and some provinces in the Southwest China in the later stage. The impact of LTR on ECR and ESI is negative in most provinces. And the negative influence of LC on MCI is increasing, showing the spatial distribution characteristics of large influence in the southeast and small influence in the northwest. The impact of LC on ESI shows a negative effect in most provinces in the early stage, and the negative effect is more concentrated in some provinces in the southwest in the later stage. [ABSTRACT FROM AUTHOR]

The past few decades of extreme drought and flooding caused by changing climate conditions have significantly affected agricultural production globally. This study focuses on two vital crops in China—maize and rice—and provides a comprehensive analysis of how these crops are affected by climate change-induced factors over the periods 1978Q1–2015Q4. Four key findings were obtained. First, using a nonparametric approach to estimate actual and observed trends of climatic variables, the results show a significant positive trend in average temperature from February to October. On the other hand, seasonal temperature increases during spring, summer, and autumn. Second, the results show no significant change in the monthly, seasonal, and annual rainfall patterns when examined over the study period. Third, using an autoregressive distributed lag (ARDL) model, we find that while temperature and rainfall do not significantly support rice production in the long and short run, they play a substantial role in maize production in China. Finally, we find no significant difference in the results for rice when the quantile regression (QR) technique that controls for distributional asymmetry effects is employed. However, the impact of temperature on maize decreases at higher quantiles. Given the outcomes of our study, we argue that an advanced irrigation system is crucial and must be encouraged to minimize the effects of climate change on crop production. [ABSTRACT FROM AUTHOR]

Biological disasters in farmland have become a serious threat to global sustainability. Quantitative studies on spatiotemporal change in regional intensity of biological disasters in farmland (RIBDF) are crucial for promoting sustainable intensification of farmland use and global food security. Many studies have revealed the impacts of natural environment on biological disasters in farmland. However, research on the impacts of farmers' activities on biological disasters remains very limited from the perspective of induced substitution in agricultural production. Based on the principle of induced substitution in agricultural production, a theoretical framework for the impacts of farmland use intensity (FUI), the occurrence intensity of biological disasters (OIBD), the natural loss intensity resulting from biological disasters (NLIBD), and the actual loss intensity controlled by human activities (ALIBD) on change in RIBDF was presented, and we therefore established an assessment model integrating these four key indices in this study. Taking Guangdong Province in China as the study area, this study analyzed the spatiotemporal changes in RIBDF from 1996 to 2017 and found that RIBDF increased overall with three change stages of slow growth, rapid growth, and decline at the provincial and regional levels. Moreover, the gravity center of RIBDF appeared to shift towards the coastal region in southwestern Guangdong at a speed of 18.20 km per year. The results reveal that the spatiotemporal change in RIBDF is determined by the key influencing factors including the substitution of chemical fertilizers for farmland and crop substitution. These findings suggest that it is necessary to expand the scale of farmland management and to encourage farmers to implement diversified cropping as well as chemical fertilizers reduction. The foremost contribution of this study is its exploration of an understanding of the linkage between farmland use activities characterized as induced substitution in agricultural production and biological disasters. Moreover, policy implications for sustainable intensification of farmland use were discussed based on these findings. [ABSTRACT FROM AUTHOR]

The overuse of chemical fertilizers and pesticides (CFPs) has negatively impacted the environment and human health. It is an urgent issue that should be addressed. In this study, we investigate whether agricultural cooperatives can serve as an institutional arrangement that helps reduce the consumption of CFPs, using the data of 2012 family farms from the Ministry of Agriculture and Rural Affairs of China. Various approaches, including instrumental variable-based two-stage residual inclusion approach (2SRI), endogenous switching probit (ESP) model, and endogenous switching regression (ESR) model, are utilized to help address the endogeneity issues of the cooperative membership variable. The results show that agricultural cooperative membership significantly increases the probability of reducing fertilizers and pesticides of the family farms and improves net return per yuan CFPs. The further analysis shows that agricultural cooperative production services reduced the usage of fertilizers and pesticides, while cooperatives marketing services only significantly lowered the use of pesticides. Our findings highlight the importance of promoting the development of agricultural cooperatives to support green agricultural production in China. [ABSTRACT FROM AUTHOR]

With the development of industrial and agricultural production, the cadmium (Cd) pollution in farmland soil is increasing which threatens the quality and safety of agricultural products in China. The purpose of this research is to explore the potential of chelated iron amendments for reducing the bioavailability of Cd to maize plants. The experiment of maize cultivation was carried out in pots. Maize was cultivated in brown soil collected from a northeast region in China and then artificially contaminated with Cd with an average concentration of 10 mg/kg. The potential of ethylenediamine tetra acetic acid ferric-sodium (EDTANa2Fe) and ethylenediamine-N, N'-bis(2-hydroxyphenylacetic acid) ferric-sodium (EDDHAFe) as amendments for Cd immobilization in soils were tested. Effects of different concentrations (0.013, 0.026, 0.053, and 0.08 g/kg) of EDTANa2Fe and EDDHAFe (calculated by iron) on the growth of maize and the Cd and Fe uptake in maize were evaluated. Principle component analysis (PCA) was performed to further analyze the overall effects of iron amendments on Cd accumulation in plants. The results showed that EDTANa2Fe and EDDHAFe at dose of 53 mg/kg reduced available Cd in soil to the value of 5.19 and 4.59 mg/kg, respectively. EDTANa2Fe of 80 mg/kg and EDDHAFe of 26, 53, and 80 mg/kg increased Fe concentration in grains by 34.86%, 36.88%, 41.46%, and 44.05%, respectively, while reduced the Cd content in grains by 39.82%, 42.67%, 48.41%, and 35.08%, respectively. Fe concentration in grains showed a significant negative correlation with the concentration of Cd (P < 0.05). EDTANa2Fe of 53 mg/kg treatment increased the maize yield by 30.45% which was higher than in all other treatments. EDDHAFe treatments of 26 and 53 mg/kg increased the total root length by 39.72% and 48.68%, respectively, and increased the total root surface area by 19.95% and 22.98%, respectively. In general, the application of EDTANa2Fe and EDDHAFe at dose of 53 mg/kg can effectively immobilize Cd in soil and reduce Cd accumulation in maize and improve Fe uptake in grains. [ABSTRACT FROM AUTHOR]

Crop straw retention is a strongly recommended practice for sustainable agricultural production in China. However, a comprehensive analysis of straw retention effects on crop yield, N2O and CH4 emissions, net greenhouse gas (NGHG), and net greenhouse gas intensity (NGHGI) and their response to various external influence factors, including location/climatic conditions, soil properties, and field management practices, in a national scale were easily ignored. Based on the collected published literatures, we found that straw retention improved crop yield and N2O and CH4 emissions by 4.7% (−4.6 to 25.8%), 18.3% (−26.6 to 57.6%), and 21.0% (−49.0 to 214.5%) in contrast with no-straw retention. For different external conditions, crop yield was increased by 15.9% in temperate zone and 10.7% in upland soils with straw retention. N2O emissions which correspond to the above conditions were enhanced by 42.2% and 18.8%, while CH4 emissions were restrained by 49.0% in temperate zone. Negligible changes in crop yield and N2O emissions were observed for subtropical zone or paddy soils, but with increase in CH4 emissions. Additionally, straw retention enhanced NGHG and NGHGI by 20.7% and 15.4% on average regardless of various external conditions, respectively. However, NGHG was reduced under conditions of straw retention in temperature or mulching to field. Straw retention under appropriate site-specially conditions simultaneously safeguard food security and slightly increase environmental effects. [ABSTRACT FROM AUTHOR]

Agricultural green production (AGP) and efficiency improvement of smallholders' management are the objective requirements for the development of China's modernized agriculture and the understanding of the rural vitalization strategy. Based on field survey data of 582 rice farmers in Shaanxi Province, this study used the Logit model to analyze the determinants of smallholders' adoption of agricultural green production technology (AGPT) and used the propensity score matching (PSM) method to measure the effect of AGPT on the technical efficiency (TE) of rice production and the heterogeneity of this influence among smallholders. Results showed that the AGPT adoption rate and the mean of rice production TE were 15.1% and 0.312, both had a lot of room for improvement. Furthermore, it was found that household's characteristics, family characteristics, agricultural management characteristics, social characteristics, and cognitive characteristics significantly affect smallholders' AGPT adoption, and the AGPT adoption significantly increased the TE of rice production by 18.8 to 24.5%. Besides, farmers with older age, less education, more specialized planting, more fragmented land, and more off-farm employment adopting AGPT could significantly improve the TE; the increase proportion was 29.8%, 29.5%, 21.3%, 27.2%, and 16.8%. The study also showed that the AGPT could not significantly increase the rice output value of smallholders. In addition, considering the endogeneity problem caused by sample selection bias, the study re-estimated using the endogenous transformation regression (ESR) model which showed that the promotion of AGPT to TE was still robust. The study puts forward policy recommendations on how to further promote the adoption of AGPT and improve the TE by farmers. [ABSTRACT FROM AUTHOR]

The concept of climate neutral has been introduced in the agricultural production system to re-examine the connotation of agricultural carbon footprint (CF). According to the integrated accounting framework of the agricultural CF we built, then selected a case from China, and carried out the climate economic effect quantitative analysis of the agricultural production system. The results indicated that CO2 emissions accounted the largest percentage of total carbon emissions by 52.05%, which was driven strongly by the application of agricultural fertilizers and consumption of diesel oil and CH4 emissions (ME) from cattle fed intestinal fermentation, and the driving force behind carbon sequestration was derived from the woody cash crops of carbon sequestration by vegetation and the input of residual carbon from straw returning to field and root stubble in the soil carbon pool. The carbon sink finally realized in the agricultural production system and the agricultural CF index reflected the surplus of 1.801 Mt C in the study area. In addition, we used the indicators of carbon density, carbon intensity, and carbon efficiency to judge the trade-offs of cost-benefit between the agroecosystem and economic system, so as to put forward some potential mitigation strategies for the study area. The mitigative effect of agricultural production system on climate neutral need to be further estimated in a more rigorous manner while controlling for more uncertainties in the future. [ABSTRACT FROM AUTHOR]

Agricultural greenhouse gas (GHG) emissions account for 14% of the total greenhouse gas (GHG) emissions from human activities, and the carbon footprint (CF) of agricultural production, which can help to propose positive measures to mitigate greenhouse gas (GHG) emissions, is a general method for assessing the impact of agricultural practices on the external environment. This article calculated the carbon footprint (CF) of rice production and compared the differences between the double-and single-cropping rice regions, which is rarely mentioned in previous literature. Some interesting information was shown. For example, the internal structure of rice production carbon footprint (CF) is prominent. (a) In terms of time evolution, CF of agricultural materials showed an increasing trend year by year, while CF of rice planting remained basically stable. (b) In terms of regional differences, whether single-cropping rice regions or double-cropping rice regions, CF of agricultural materials did not show the previous increasing trend after 2011, especially after 2015. This may be greatly affected by the policy such as the abolishing of the China agricultural tax in 2006. These studies can help us to reveal how agricultural policies and different rice cropping patterns affect each region. [ABSTRACT FROM AUTHOR]

Straw returning usually gives rise to greenhouse gas (GHG) emissions from the soil, and thus negatively affects carbon footprint (CF) of crop production. Numerous studies reported the effects of straw returning on the CF from single crop production. However, little is known about the integrated effects of different levels of straw returning on the CF and net ecosystem economic benefits (NEEB) from rice-wheat rotation. Here, we investigated the effects of different amounts of straw returning on soil CH4 and N2O emissions, GHG emissions from agricultural inputs (AIGHG), CF, and NEEB from a 2-year cycle of rice-wheat rotation. The CF was determined based on the total GHG emissions associated with crop production inputs and services. Overall, straw returning significantly increased annual CH4 emissions by 5.4–72.2% and reduced annual N2O emissions by 3.3–31.4% compared with straw removal. Straw returning remarkably increased rice grain yields by 8.1–9.9% and wheat grain yields by 10.2–21.1% compared with straw removal. The average annual AIGHG from rice-wheat rotation ranged from 3579 to 4987 kg CO2-eq ha–1. Diesel consumption played a dominant role in the AIGHG. The annual CF ranged from 0.96 to 1.31 kg CO2-eq kg–1 and increased with increasing straw returning amounts. The NEEB, which ranged from 14161 to 17413 CNY ha–1, was significantly affected by the levels of straw returning. The treatment with returning of 1/3 of preceding crop straw to the field (2.19–2.47 kg ha−1 year−1 of rice straw in the wheat season and 1.38–1.68 kg ha−1 year−1 of wheat straw in the rice season) resulted in relatively higher grain yield, the lowest CF, and the highest NEEB among all treatments, and thus can reduce CF, and increase grain yields and NEEB, and thus can be recommended as a sustainable approach to mitigate GHG emissions and increase economic benefits from rice-wheat rotation. [ABSTRACT FROM AUTHOR]

This study aims to explore the dynamic association among crop production, livestock production, power consumption in agriculture, forest area, and carbon dioxide (CO2) emissions. Based on the annual data of China, spanning the period 1990 to 2016, the study applied the auto-regressive distributed lag (ARDL) bounds testing approach. In addition, the fully modified ordinary least squares (FMOLS) canonical cointegration regression (CCR) and the Granger causality tests are employed to check the robustness of the ARDL estimations. The ARDL-bounds testing approach indicated that all variables share a long-run connection. The long- and short-run ARDL estimations confirmed that crop production, as well as livestock production, has a significant positive effect on CO2 emissions in both cases. However, power consumption in agriculture and forest area has a negative effect on it, indicating that both variables reduce CO2 emissions in the long and short run. These results stood robust under various regression estimators and confirmed the findings of the ARDL method. Additionally, the results of the causality approach specified that a unidirectional causality is running from crop production, power consumption in agriculture, and forest area to CO2 emissions. The causality between livestock production and CO2 emissions is bidirectional. Therefore, the directions of this connection also validate the outcomes under various techniques used for robustness. These findings suggest that the government must reconsider its policies related to agricultural and livestock production and adopt environment-friendly practices in the agriculture sector that may reduce the carbon footprints in the long run. [ABSTRACT FROM AUTHOR]

Carbon dioxide emission and greenhouse gas emissions are considered core issue in the world that influence agricultural production and also cause climate change. The present study seeks to investigate the linkage of methane emissions, nitrous oxide emissions, carbon dioxide emission, and greenhouse gas emissions with agricultural gross domestic product in China. The long-term association was checked by using an autoregressive distributed lag (ARDL) bounds testing approach, fully modified least squares method, and canonical cointegrating regression analysis. The results from long-run analysis exposed that carbon dioxide emission and greenhouse gas emissions have positive coefficients that demonstrate the long-run linkage with the agricultural gross domestic product having p values of 0.5709 and 0.3751, respectively. Similarly, results also revealed that agricultural methane emissions and agricultural nitrous oxide emissions have a negative association with the agricultural gross domestic product having p values of 0.1737 and 0.0559. China is a huge emitter of CO2 emission and greenhouse gas emissions. Possible conservative policies are required to form the Chinese government to tackle this challenge to decrease CO2 emission in order to increase agricultural production. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Enzyme activity and microbial population in soils have important roles in keeping soil fertility. ZJ0273 is a novel pyrimidynyloxybenzoic-based herbicide, which was recently developed in China. The effect of ZJ0273 on soil enzyme activity and microbial population in two different soils was investigated in this study for the first time. The protease activity was significantly inhibited by ZJ0273 and this inhibiting effect gradually weakened after 60-day incubation. The results also showed that ZJ0273 had different stimulating effects on the activities of dehydrogenase, urease, and catalase. Dehydrogenase was consistently stimulated by all the applied concentrations of ZJ0273. The stimulating effect on urease weakened after 60-day incubation. Catalase activity was subject to variations during the period of the experiments. The results of microbial population showed that the number of bacteria and actinomycetes increased in ZJ0273-treated soil compared with the control after 20 days of incubation, while fungal number decreased after only 10 days of incubation in soils. DT50 (half-life value) and k (degradation rate constant) of ZJ0273 in S1 (marine-fluvigenic yellow loamy soil) and S2 (Huangshi soil) were found 69.31 and 49.50 days and 0.010 and 0.014 day, respectively. [ABSTRACT FROM AUTHOR]