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Overuse of chemical fertilizers and pesticides is a major policy concern for many countries. Chinese government has adopted many technologies and management practices to reduce their use. However, little is known about the effects of social-economic method such as short supply chain (SSC) participation. SSC is an important organizational innovation in fresh food supply chains aiming at directly connecting farmers and consumers. Closer relationships between farmers and consumers may result in production behavioral changes. Thus the purpose of this paper is to investigate the impacts of SSC participation on agrochemicals application.

Based on the household level data collected from Jiangsu province in China, this paper employs an instrumental variable (IV) method to address the self-selection bias when we evaluate the effects of SSC participation on use of chemical fertilizer and pesticides. In addition, this paper also distinguishes between growth inputs and facilitating inputs in the production function when we calculate the marginal production values of chemical fertilizer and pesticides.

The empirical results show that SSC participation significantly reduces chemical fertilizer use by 351 kg and pesticides costs by 1659 Yuan (RMB) per hectare, accounting for 43.4% of the average chemical fertilizer use and 49.4% of the average pesticide costs, respectively for Chinese vegetable farms. However, SSC participation still cannot improve the use efficiency of agrochemicals.

This paper uses both application quantities and allocation efficiencies of chemical fertilizer and pesticides to comprehensively evaluate the effects of SSC participations. The results will reveal the core role of SSC played in promoting sustainable development of Chinese agricultural sector dominated by small-scale farmers.

The purpose of this paper is to understand the critical factors associated with growing fertilizer usage culminating in contamination of soil/water in agriculturally intensive regions of Uttar Pradesh, India. The agriculture sector is seen as one of the major contributors in ensuring food security, however adoption of sustainable agriculture to protect water resources from contamination due to fertilizers and pesticides is becoming pressing to achieve long term environmental security.

A two staged study aimed at monitoring the soil quality status followed by stakeholder survey has been attempted. Attitude-behavior framework based on the theory of reasoned action has been tried to explain the fertilizer use behavior in the study. The results are analyzed through Analysis of variance.

Soil monitoring data showed nitrate and total nitrogen loadings beyond the permissible limit in the identified regions. A questionnaire aimed at determining farmer’s attitude toward fertilizer usage showed a significant influence of factors like net farm income, overall farm yield, extension services, farmer characteristics on one hand and risks associated with changing farming practices, costs of substitutes available, market-based instruments like subsidies and loans on the other. Divergent responses were observed with respect to farmer’s perceived risks from adopting to organic substitutes, linkages of fertilizer application with environmental degradation and the level of adoption of sustainable agricultural practices.

The study can be scaled up to study the inter-regional differences by benchmarking regional responses. It would be interesting to extend the work to find solutions from the farmers as alternative fertility management strategies. The items used in questionnaire are self-made; hence there is still a possibility of enhancing the robustness of scale by applying advanced statistical techniques.

Results of the study indicate excessive nitrogen loadings in farm soils which is an indicator of potential future nitrate contaminated zones or vulnerable zones emerging in agricultural intensive regions. Findings reinforce the role of education, knowledge transfer and awareness for long-term agricultural sustainability. The paper highlights the urgency for reorientation of the support system by the government and policymakers.

The paper attempts to understand the linkage between the agricultural productivity and the environmental implications followed by the reasons culminating in the agri-environmental imbalance. On-site monitoring study followed by assessment of reasons culminating in this scenario has not been attempted earlier and this paper contributes to understanding at dual level. This paper emphasizes on the insights of stakeholder which is instrumental in ensuring agricultural sustainability or otherwise. It takes the position that the farmer’s farm management behavior is strongly influenced by factors like food security and income, keeping environmental quality at second place. It also identifies the barriers for organic farming and other alternative systems as well as explores the economic, social, and philosophical aspects of sustainable agriculture.

The modernization of the agro-based industry has encouraged the application of inorganic fertilizers to increase productivity. However, such fertilizer emissions may pose harmful environmental effects in the long run. This study aims to empirically explore the matter by applying the environmental Kuznets curve (EKC) hypothesis in the Indian agro-based industry.

The study builds two models considering nitrous oxide emission levels from inorganic (synthetic) and organic (manure) fertilizers to evaluate the safer option for the environment. The validity of an industry-specific EKC (IEKC) is tested for the models considering time series data from 1975 to 2019. Here, the autoregressive distributed lag model is applied for the 45 years long time series analysis to test the hypothesis with respect to inorganic and organic fertilizers emissions.

The existence of the IEKC is rejected by the inorganic fertilizer emissions model. Its U-shaped curve implies that applying such fertilizers will gradually cause degrading environmental effects. On the other hand, the organic fertilizer emissions model supports the existence of an inverted U-shaped IEKC. It proves that organic fertilizers are a better choice for safeguarding the environment in the long run.

Applying the EKC hypothesis on an industrial level can signify whether an industry worsens the environment in the long run. However, very few studies have explored such an application of the hypothesis in the past. Moreover, the literature could not find any previous study exploring the environmental effects of inorganic and organic fertilizers by analyzing the EKC hypothesis. The hypothesis can offer such insights with simplified empirical assessment.

Constraints associated with public agricultural extension services imply that farmers increasingly rely on input providers for agricultural innovations and knowledge. Yet such providers are typically commercial profit-making agents and may have an incentive to suggest relatively costly inputs and/or high rates. The purpose of this paper is to look into the case of Bangladesh and the role of fertilizer traders in terms of farmers’ decisions on which fertilizer to apply and at what rate. Using primary data, the authors examine farmers’ chemical fertilizer use and the associated rice production efficiency, based on different information sources (fertilizer traders, government extension agents or own/peer experience).

Using primary data, the present study estimates an ordered probit model and production functions separately based on whether or not a farmer relied on information from fertilizer traders or own experience and government extension agents, and examines the efficiency score of each type of farmer.

The findings demonstrate that the resource-poor farmers rely more on traders’ suggestions for fertilizer application than public extension – but the actual fertilizer information source has no significant effect on the production efficiency of the rice farmers. This study, therefore, does not find exploitative behavior of fertilizer traders. Thus, this study concludes that small rural traders in Bangladesh are working as agricultural extension agents and provide necessary fertilizer application information to resource-poor farmers.

This is a case study based on Bangladesh – an emerging economy in South Asia. The findings of the study may not be generalized for other countries.

To the authors’ knowledge, this is the first study that confirms the role of agricultural input sellers as the extension agent in developing countries.

The authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.

Primary data were sourced from 435 cocoa farmers. Cragg hurdle and two-step Tobit model with continuous endogenous regressors/covariates were applied for the drivers of cocoa farmers' participation in fertilizer subsidy programme and productivity. Propensity score matching (PSM), inverse-probability weights (IPW) and augmented inverse-probability weights (AIPW) were applied for productivity impact assessment of fertilizer subsidy.

All the farmers were aware of fertilizer subsidy for cocoa production in Ghana. Farmers became aware of fertilizer subsidy through extension officers, media and other farmers. Half of cocoa farmers benefitted from fertilizer subsidy. Averagely, cocoa farmers purchased 292 kg of subsidized fertilizer. Many socio-economic, farm-level characteristics and institutional factors determine cocoa farmers' participation in fertilizer subsidy programme, quantity of subsidized fertilizer obtained and productivity. Beneficiaries of fertilizer subsidy recorded higher cocoa productivity than non-beneficiaries. Hence, fertilizer subsidy for cocoa production in Ghana leads to a gain in productivity.

There should be more investments in fertilizer subsidy so that all cocoa farmers benefit and obtain the required quantities.

The authors provide new evidence on cocoa productivity gain or loss emanating from fertilizer subsidy by combining different impact assessment techniques for deeper analysis: PSM, IPW and AIPW.

There is an urgent need to develop climate-smart agrosystems capable of mitigating climate change and adapting to its effects. Conventional agricultural practices prevail in Mauritius, whereby synthetic chemical fertilizers, pesticides and insecticides are used. It should be noted that Mauritius remains a net-food importing developing country of staple food such as cereals and products, roots and tubers, pulses, oil crops, vegetables, fruits and meat (FAO, 2011). In Mauritius, the agricultural sector faces extreme weather conditions like drought or heavy rainfall. Moreover, to increase the crop yields, farmers tend to use 2.5 times the prescribed amount of fertilizers in their fields. These excess fertilizers are washed away during heavy rainfall and contaminate lakes and river waters. By using smart irrigation and fertilization system, a better management of soil water reserves for improved agricultural production can be implemented. Soil Nitrogen, Phosphorus and Potassium (NPK) content, humidity, pH, conductivity and moisture data can be monitored through the cloud platform. The data will be processed at the level of the cloud and an appropriate mix of NPK and irrigation will be used to optimise the growth of the crops. Machine learning algorithms will be used for the control of the land drainage, fertilization and irrigation systems and real time data will be available through a mobile application for the whole system. This will contribute towards the Sustainable Development Goals (SDGs): 2 (Zero Hunger), 11 (Sustainable cities and communities), 12 (Responsible consumption and production) and 15 (Life on Land). With this project, the yield of crops will be boosted, thus reducing the hunger rate (SDG 2). On top of that, this will encourage farmers to collect the waters and reduce fertilizer consumption thereafter sustaining the quality of the soil on which they are cultivating the crops, thereby increasing their yields (SDG 15).

From the perspective of land mortgages, the purpose of this paper is to understand how farmers can be motivated to utilize environment-friendly formula fertilizers, thereby reducing the use of chemical fertilizers.

Two hypotheses are empirically tested using questionnaire responses from 714 farmers across three provinces in China to establish the relationship and to determine the role land rent plays.

This study finds that farmers who obtain land mortgages will be more willing to apply formula fertilizers in order to obtain higher value of their “own” land. This is because obtaining land mortgages can be considered as the process of titling land management rights. Farmers who have been transferred the land by verbal agreement no longer need to worry about losing it at any time. Hence, they are willing to apply formula fertilizers on their transferred land. Similarly, farmers who have been transferred the land by written contract to obtain more land mortgages will also be willing because the formula fertilizers can not only improve the quality of their transferred land, but also increase its value as collateral. This mechanism is clearer in the area where the average land rent is relatively lower.

No study has yet linked the reform of land mortgages to environmentally friendly behavior. While other studies have focused on the way access to credit changes farmer investments and spending, this particular relationship has not yet been formalized, giving this study theoretical and empirical significance.

The paper aims to clarify the relationship between the output value of unit sown area (OVUSA) and its major influential factors by taking Jiangsu Province, People's Republic of China as an instance, followed by some suggestions for adjusting the agricultural inputs.

The paper is characterized by an exploratory research by constructing a grey incidence model (GIM) based on the grey system theory (GST) initiated by Chinese professor Julong Deng. The original data processed in the model are quoted from Jiangsu Statistics web site and the Statistical Yearbook of Jiangsu Province.

The analysis indicates several noteworthy points in the following areas. To start with, the proportion of irrigated area to sown area has turned out to be a stabilizing factor influencing OVUSA; next, the contributions of nitrogen and phosphorus fertilizers' output to the growth of the OVUSA were reduced, while the marginal outputs of nitrogen and phosphorus fertilizers seemed to be lower; then the outputs of potash and compound fertilizers have made significant contributions to the growth of the OVUSA, although their application rates were drastically increased; besides, the total power of agricultural machinery was a major factor boosting the growth of the OVUSA; furthermore, the decrease of labor force was obviously remarkably related to the reduction of OVUSA; finally, the areas affected by natural disasters have had a foremost impact on OVUSA reduction.

Suggestions are also proposed to the related policy-makers as follows: to reasonably control the application rates of nitrogen and phosphorus fertilizers, to encourage fertilizer manufacturing enterprises to develop potassium mineral resources with the purpose of guaranteeing the potash fertilizer's supply, to scientifically design the composition of compound fertilizers in order to satisfy the needs of cultivated lands in different areas, to improve the quality and structure of agricultural labor forces with the aim of meeting emerging trends in the agricultural industry, to make every effort to further modernize the current agricultural industry, and to enhance the disaster-prevention capability of the agricultural industry by gradually converting it into a controllable one.

The purpose of this paper is to describe the provision of existing learning object repositories with enhanced forms of describing digital resources on organic agriculture and agroecology.

The approach followed was to investigate non‐invasive techniques for semantic annotation of learning objects, for which use was made of two tools. The first tool was a software application for the automated classification of learning resources stored in public learning object repositories. The second tool was an ontology in OWL derived from the knowledge in the Agrovoc thesaurus.

Current digital repositories for educational resources and open access archives provide scholars with a number of features, such as the ability to search for materials according to given criteria, or to retrieve the full content of those materials from the repository. Many provide advanced features as well, such as browsing, assessing and collaboratively peer reviewing learning resources, but at the cost of using the specific tools and interfaces provided by each repository.

This research is part of the EU‐funded project Organic.Edunet, aimed at facilitating access, usage and exploitation of digital educational content related to organic agriculture and agroecology (OA&AE). Consequently, knowledge representation, thesauri and the educational resources reported herein are deliberately focused on the OA&AE domain, even though the concepts and techniques utilized may be easily applied in other contexts.

The paper describes two new approaches aimed at enhancing availability of learning resources: the potential use of ontologies for the description of learning resources, and the full use of the classification category in the IEEE LOM metadata standard.

This paper investigates the relationship between plot size and fertilizer use efficiency (FE) in Chinese large-scale farming and searches for the underlying mechanisms that explain this relationship.

Based on a household- and plot-level data set of large-scale production units (LSPUs) from Jiangsu and Jiangxi Provinces, the technical and fertilizer use efficiency of large-scale rice production is estimated by applying a translog stochastic frontier production function. The authors impose a monotonicity condition on the translog frontier using a three-step procedure to get theoretically consistent efficiency estimates. A beta regression model is then used to explore the association between plot size and LSPUs' efficiency in fertilizer application.

The average FE for the sampled plots is around 30%, which shows a large potential for LSPUs to reduce fertilizer use. A U-shaped relationship is observed between plot size and FE. The authors relate this non-linear pattern to the substitution of labour with capital-intensive technology and the efficiency differences in terms of farming performance between family and hired workers.

First, according to the authors’ knowledge, this paper is a first attempt to study the size–efficiency relationship focussing on fertilization practices of large-scale farming. The second contribution lies in the large-scale ranges of the plot-level data set. Third, efforts are made to reveal the mechanisms determining the plot size–FE relationship. Fourth, the authors provide guiding evidence for policymaking, as they show that the size of individual plots deserves equal attention in land consolidation decisions. Methodologically, this paper improves existing estimates of single-factor technical efficiency issued from a restricted production frontier model.