Agricultural Change Research Articles

Prefiguring the counter-hegemony of open cooperativism: The case of Open Food Network

Drawing on Ernesto Laclau and Chantal Mouffe's discourse theory of hegemony, the paper introduces a chain of equivalence that articulates discourses such as “commons-based peer production”, “partner state” and “ethical market entities” around the counter-hegemony of open cooperativism vis-à-vis the current hegemony of neoliberalism. The paper sets out to empirically test its theoretical premises by reviewing the Open Food Network as an illustrative case-study of open cooperativism. The Open Food Network deploys the digital commons to launch short food supply chains and bring about systemic change in agriculture. Τhe paper suggests that for the Open Food Network to contribute to systemic change in agriculture and beyond it may create cross-sectoral synergies across the economy, civil society and politics to help articulate a chain of equivalence linking up ethical market entities, the commons and a partner state around the model of open cooperativism.

Assessment of Spatio-Temporal Land Use/Cover Change and Its Effect on Land Surface Temperature in Lahaul and Spiti, India

Land Use/Land Cover (LULC) changes have a significant impact on Land Surface Temperature (LST). The LST is an important parameter in various environmental and climatological studies, as it plays a crucial role in understanding the Earth’s surface–atmosphere interactions. The LULC changes can modify the surface energy balance and alter the radiation budget, leading to changes in LST. Urbanization, deforestation, and agricultural land use changes are some of the primary drivers of LULC change that have a significant impact on LST. Deforestation and agricultural land use changes result in a reduction in evapotranspiration, leading to an increase in LST. The main objective of the study is to analyze the spatio-temporal change in Land Use/Land Cover (LULC) and its effect on Land Surface Temperature (LST), as well as to establish a correlation of LST with the Normalized Difference Vegetation Index (NDVI) and Normalize Difference Snow Index (NDSI). Understanding the impact of LULC on LST is essential for developing effective land use policies that can mitigate the adverse effects of LULC change on the environment and human health.

Context – Goal – Method – Outcome: Alignment in Citizen Science Project Design and its Relation to Supporting the United Nations Sustainable Development Goals

Citizen science (CS) is a diverse practice, with projects emphasizing scientific and/or democratization goals. While the integration of both goals is advocated for sustainability transitions, this implies contextualized methodological choices. This contribution presents an instrument to explore methodological choices in relation to project goals and context, linking these patterns to the United Nations Sustainable Development Goals (SDGs). By way of a PRISMA scoping review, case studies implemented in the Global North (GN) or Global South (GS) were selected and categorized using the instrument to identify notable patterns. GN projects are generally published by GN authors and can predominantly be linked to productivity goals relating to SDGs on biodiversity (SDGs 14, 15). In contrast, GS projects are commonly associated with diverse co-author groups that focus on democratization and/or productivity, and prioritize SDGs on agriculture, health, sustainable communities, and climate change (SDGs 2, 3, 11, 13). The analyzed case studies could contribute directly to three SDG indicators and indirectly to 22. Methodological choices regarding project goals and themes translate into variations in participant selection and recruitment, contribution types, and project outcomes. Further, project design and outcomes can be linked to co-authorships, with larger teams typically associated with co-created projects which in turn focus on democratization or democratization and productivity goals, and produce a wide diversity of outcomes. Qualitative information extracted from the investigated papers was used to contextualize the relevance of combining productivity and democratization goals as well as the related challenges of harmonizing different interests and of resource limitations as well as other project constraints.

Development of Physics LMS Based on Science Literacy Related Energy Content in Agricultural Context (Farmer)

Farmer is a Physics learning media that functions as Learning Management System (LMS) to organize, manage, and deliver subject matter on the concept of energy and its changes related to work, changes in mechanical, chemical, electrical, heat and renewable energy on the basic techniques of plant production processes which refer to a science literacy-based learning flow with a web format for the vocational school of Agriculture. The purpose of this study was to analyze the concept of Energy and its changes in Agriculture that are used in the LMS Farmer. The Material of Energy and its changes in Agriculture in LMS farmers were developed using the ADDIE model 1) Analysis Phase; 2) Design Phase; 3) Developed Phase; 4) Implementation Phase; 5) Evaluation Phase. This research used the qualitative method. The non-test research instruments included material validations by four material experts consisting of two physics experts, one teacher and one Agricultural material expert. The data analysis techniques included descriptive statistics. The results showed that the material of Energy and its changes in Agriculture on LMS Farmer, based on the assessment by four experts lies in the “feasible” category. The conclusion of this study is that the material of Energy and its changes LMS Farmer in the feasible category so that they are feasible to be applied in physics learning for vocational schools majoring in Agriculture.

The Influence Mechanism of Farmer Behavior on the Spatial Pattern Evolution of Agricultural Production in the Yanhe River Basin

Featuring complex and fractured terrain, the Loess hilly and gully regions suffer poor grain production capacity. The behavior of farmers, the major users of agricultural production space, significantly influences the agricultural production space. Hence, it is essential to explore the evolution rules of the agricultural production space under the influence of farmer behavior and reveal the influencing mechanism of agricultural production space change, which will facilitate the promotion of ecological protection and high-quality development of the Yellow River Basin. Relying on six-stage remote sensing images of the Yanhe River Basin from 1995 to 2018, this study utilized a land use dynamic index, transfer matrix and landscape pattern index to analyze the spatial pattern evolution of agricultural production in the Yanhe River Basin. Furthermore, the geographic detector model was applied to quantitatively analyze the influencing factors of the spatial pattern evolution of agricultural production. The results demonstrated the following: (1) From 1995 to 2018, the overall area of cultivated land in the Yanhe River Basin decreased by 927.02 km2, with a change degree of 21.07%. The spatial structure of agricultural production changed, mainly transferring the cultivated land to woodland and grassland. (2) The spatial form of agricultural production has changed from fragmentation to regularity, and the complexity of the production space shows a trend of first increasing and then decreasing. (3) The evolution of the spatial pattern of agricultural production was affected by multiple factors of farmer behavior, where significant interactive enhancement effects existed. Specifically, labor input was the dominant factor affecting the overall scale of the production space, with an influence value of 0.202; fertilization input and cultivated land transfer were the key factors affecting the spatial distribution of production, with influence values of 0.264 and 0.242, respectively; income level and social interaction were the base factors affecting the spatial form of production, with influence values of 0.558 and 0.438, respectively. The research results provide scientific support for the improvement of agricultural production quality and the spatial evolution mechanism of agricultural production in the Yanhe River Basin.

Quantifying the impact of farmers' social networks on the effectiveness of climate change mitigation policies in agriculture

AbstractTo reduce agricultural greenhouse gas (GHG) emissions, farmers need to change current farming practices. However, farmers' climate change mitigation behaviour and particularly the role of social and individual characteristics remains poorly understood. Using an agent‐based modelling approach, we investigate how knowledge exchange within farmers' social networks affects the adoption of mitigation measures and the effectiveness of a payment per ton of GHG emissions abated. Our simulations are based on census, survey and interview data for 49 Swiss dairy and cattle farms to simulate the effect of social networks on overall GHG reduction and marginal abatement costs. We find that considering social networks increases overall reduction of GHG emissions by 45% at a given payment of 120 Swiss Francs (CHF) per ton of reduced GHG emissions. The per ton payment would have to increase by 380 CHF (i.e., 500 CHF/tCO2eq) to reach the same overall GHG reduction level without any social network effects. Moreover, marginal abatement costs for emissions are lower when farmers exchange relevant knowledge through social networks. The effectiveness of policy incentives aiming at agricultural climate change mitigation can hence be improved by simultaneously supporting knowledge exchange and opportunities of social learning in farming communities.

Study on the Relationship between Economic Growth of Animal Husbandry and Carbon Emission Based on Logarithmic Average Index Method and Decoupling Model: A Case Study of Heilongjiang Province

With the establishment of the action plan for the goal of “carbon peaking and carbon neutrality”, how to achieve high-quality agricultural development, help implement the construction of the green Longjiang River, reduce agricultural carbon emissions, and increase the level of agricultural carbon sink is a key problem that must be solved for Heilongjiang Province to achieve the goal of “double carbon”. This article uses the Life Cycle Assessment (LCA) method to estimate the carbon emissions of animal husbandry in Heilongjiang Province and 13 cities from 2000 to 2020. By constructing the Tapio decoupling model, Kaya identity, and the LMDI model, the relationship between animal husbandry economy and carbon emissions in Heilongjiang Province and the driving factors affecting animal husbandry carbon emissions are explored. The results indicate that: (1) From 2000 to 2020, the carbon emissions of animal husbandry in Heilongjiang Province showed an overall slightly upward trend. From the perspective of various emission links, the highest carbon emissions are from the gastrointestinal fermentation environment (42.49%), with beef cattle, cows, and live pigs being the main livestock and poultry in Heilongjiang Province with carbon emissions. (2) The Tapio decoupling model results indicated that from 2000 to 2020, the relationship between the economic development of animal husbandry in Heilongjiang Province and carbon emissions was mainly characterized by weak decoupling. (3) The main driving force behind the continuous increase in carbon emissions from animal husbandry in Heilongjiang Province is the changing factors of agricultural population returns and changes in the production structure of animal husbandry; The driving factors that suppress the increase in carbon emissions from animal husbandry in Heilongjiang Province are changes in animal husbandry production efficiency, population and urban development levels, and population mobility factors. Finally, based on the decoupling effect status and driving factors of decomposition between Heilongjiang Province and its various cities, it is recommended to implement countermeasures and suggestions for the transformation of animal husbandry in the province towards green and low carbon at the macro level. This can be achieved through the adoption of sustainable and eco-friendly practices such as the use of renewable energy sources and the reduction of greenhouse gas emissions. Additionally, promoting research and development in sustainable agriculture and animal husbandry can also contribute to the transformation towards a more environmentally friendly industry.

Socio-hydrological dynamics and water conflicts in the upper Huasco valley, Chile

In arid regions of north-central Chile, mining activities and agricultural land use changes lead to competing water demands, water insecurity, and related conflicts. Different local and external user groups rely on the scarce water resources. This case study investigates socio-hydrological transformations in the upper Huasco valley. It builds on a mixed method approach that combines remote sensing assessments (Corona, Landsat, Sentinel-2) with a set of social science methods including interviews and an analysis of Twitter tweets. Against the backdrop of the recent mega drought, results show that the upper Huasco valley faces adverse environmental impacts and conflicts over mining activities as well as an expansion of export-oriented agriculture. While water availability largely depends on the cryosphere, remote sensing analyses show a drastic glacier decrease in the vicinity of the mining project, where three glaciers completely disappeared since 2000. Furthermore, an expansion of the cultivated area from 2,000 ha in the 1990s to about 3,210 ha occurred in the 2000s. Agricultural expansion has come to a halt and only a slight increase of 100 ha can be detected over the last decade. Interview and social media data show local concerns and discourses on issues of water scarcity and quality related to these land use changes. The study stresses the necessity of integrative assessments for a better understanding of water scarcity and water-related conflicts. Equitable water governance in climate-sensitive areas requires contextualizing land use changes and the precarious drinking water situation from a socio-hydrological perspective.

MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets.

Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

Efficiency of Solar Power Generation System Application on Agricultural Automatic Drip Irrigation in Indonesia

Irrigation is one of the important components of farming producers in cultivation. Lack of irrigation water causes crop failure risk, while excess water also causes agricultural crop failure. It is necessary to regulate irrigation water to achieve technical and economic farming efficiency. This study aims to determine the efficiency of solar power generation in agricultural automatic drip irrigation. This study uses experimental research with the design of materials and research tools. Efficiency estimation uses a simple ratio by looking at the cost components of each treatment so that the value that appears becomes the final efficiency value. This study showed that automatic drip irrigation for solar power generation was more economically efficient than ordinary electricity. The use of automatic drip irrigation can save costs of Rp. 4,346,200. In addition, unlimited renewable energy support is a major advantage besides being environmentally friendly and an agricultural climate change adaptation strategy. The system’s performance on the automatic pump is running well, as seen from P1, P2, P3, P4, and P5; the pump turns on at a percentage of water ranging from 10-90% and turns off after reaching 100% water or water-saturated soil conditions. The main obstacle faced during the research was the climate problem because this research model used the solar system. This means that as long as sunlight shows its existence, the energy obtained is also perfect, but vice versa. In addition, it is still difficult for traditional farmers to carry out the operational control system, so further research is needed.

The Role and Use of Mathematical Programming in Agricultural, Natural Resource, and Climate Change Analysis

Climate change undeniably impacts agriculture and natural resources, enterprises and markets. For informed decision making, there is a need for information on climate change adaptation possibilities and mitigation alternatives. Mathematical programming has been used to address the economic aspects of such questions and allows analysis as climate change moves the environment into previously unobserved conditions. It allows us to model spatial and dynamic features of the issue and analyze heretofore unobserved adaptation and mitigation possibilities. This review provides an overview of and references for modeling techniques, conceptual issues, and major assumptions involved with using mathematical programming as a climate change economic analyzing engine, along with a brief comparison with other methods. We also review a number of studies applying mathematical programming to examine climate change impacts, adaptation, and mitigation issues in the agricultural and natural resources arena. Finally, we present a very brief discussion on research needs.

Digital Agriculture Policies and Strategies for Innovations in the Agri-Food Systems—Cases of Five West African Countries

The digital transformation of agriculture can support economic growth and food and nutrition security in Africa. The objectives of this study were to provide an overview of the status of digital agriculture in five West African countries, analyze their efforts in developing the enabling environment and innovations, and formulate recommendations based on the identified gaps for the effective transformation of the sector. For this purpose, a literature search was performed using various sources, including web pages and databases of national agricultural and digital transformation institutions and start-ups of the five target countries (Benin, Burkina Faso, Côte d’Ivoire, Ghana, and Nigeria) and regional/international institutions. The information retrieved was used for individual country and cross-country comparative analysis of the progress and propositions of feasible actions for improvements. The results showed increasing agri-digital initiatives in the five countries, which were grouped into seven categories based on their objectives. Steady progress was also observed in mobile internet adoption, despite the differences in deploying crucial infrastructure to promote digital agriculture. The mobile connectivity index (MCI) in all five countries is below 60. Nonetheless, Ghana and Côte d’Ivoire demonstrated more efforts in internet and electricity access, especially in rural areas. Benin and Nigeria have developed separate documents depicting the roadmap for digital agriculture, while the other countries are working to create one or have it embedded in their national development plans. Similarities and specificities exist among countries for laws and processes protecting agri-digital innovators. To be competitive and self-reliant in the global e-economy, these countries must reposition themselves to accelerate changes in digital agriculture through effective governance and synergy of actions in different sectors and across nations.

Bovine hypodermosis is highly prevalent in Kazakhstan: Results of a first serological study.

Recent information on the occurrence of bovine hypodermosis in Kazakhstan is limited to the results of a few clinical studies in the northern and eastern regions. A first serological study aimed to obtain more data on its geographical distribution and to estimate the prevalence in this country. Serum samples collected from 891 dairy cows on 30 dairy farms in eight Kazakh provinces during the winter season 2015/2016 were examined for antibodies to Hypoderma spp. first-stage larval antigen using a commercially available enzyme-linked immunosorbent assay (IDEXX Bovine Hypodermosis Serum Antibody Test). Overall, 73.6% (95% confidence interval: 70.6%-76.5%) of the cows sampled were seropositive for Hypoderma, and antibody-positive cows were found in 28 of 30 farms and in seven of eight provinces. The results suggest a high prevalence of bovine hypodermosis in Kazakhstan, for which the socioeconomic changes in agriculture and village life following the country's independence are considered to be responsible.

Integrated Agricultural Practices and Engineering Technologies Enhance Synergies of Food-Energy-Water Systems in Corn Belt Watersheds.

Interconnected food, energy, water systems (FEWS) require systems level understanding to design efficient and effective management strategies and policies that address potentially competing challenges of production and environmental quality. Adoption of agricultural best management practices (BMPs) can reduce nonpoint source phosphorus (P) loads, but there are also opportunities to recover P from point sources, which could also reduce demand for mineral P fertilizer derived from declining geologic reserves. Here, we apply the Integrated Technology-Environment-Economics Model to investigate the consequences of watershed-scale portfolios of agricultural BMPs and environmental and biological technologies (EBTs) for co-benefits of FEWS in Corn Belt watersheds. Via a pilot study with a representative agro-industrial watershed with high P and nitrogen discharge, we show achieving the nutrient reduction goals in the watershed; BMP-only portfolios require extensive and costly land-use change (19% of agricultural land) to perennial energy grasses, while portfolios combining BMPs and EBTs can improve water quality while recovering P from corn biorefineries and wastewater streams with only 4% agricultural land-use change. The potential amount of P recovered from EBTs is estimated as 2 times as much as the agronomic P requirement in the watershed, showing the promise of the P circular economy. These findings inform solution development based on the combination of agricultural BMPs and EBTs for the cobenefits of FEWS in Corn Belt watersheds.

Rapid response of vascular plants and insects to restoration of montane grasslands

IntroductionIndustrialization has ushered in massive changes in agriculture. Particularly in low mountain ranges, large-scale afforestation with Norway spruce on traditionally managed, semi-natural grasslands has caused a severe decline in biodiversity. Tree removal, hay transfer and resumption of grazing or mowing are typical measures to re-create species-rich grasslands. The aim of this study was to use vascular plants and three insect taxa (leafhoppers, true bugs, and grasshoppers) as bioindicators to evaluate the success of montane grassland restoration on former spruce forests in Central Europe. In addition, we intended to identify the drivers of species richness within the studied grasslands in order to derive suitable recommendations for habitat management.MethodsWe analyzed two different treatments: (i) grazed restoration sites where trees had been cut and species-rich green hay had been applied (N = 9) and (ii) target sites with a long continuity of low-intensity grazing (N = 9).Results and DiscussionOur study revealed that all studied taxa responded rapidly to the restoration measures. After a development period of 3 to 5 years, we found no differences in species richness and diversity of leafhoppers, true bugs and grasshoppers (all, target and threatened species). In addition, non-metric multidimensional scaling showed a large overlap in species composition between restoration and target grasslands. Among target and threatened species, vascular plants displayed the same pattern as insects and reached similar values when comparing the two treatments. However, total species richness and diversity of vascular plants were still higher on the target sites and species composition overlapped only partially. Grazing intensity was the predictor with the highest explanatory power in multivariable (Generalized) Linear Mixed-effects Models, being negatively related to species richness of leafhoppers and true bugs. We conclude that the measures implemented were effective in re-establishing target communities of different taxa. The transfer of seed-containing hay enabled or accelerated the development of the vegetation. Insects, on the other hand, were able to recolonize the restored grasslands on their own, given that these sites were embedded in a network of species-rich grasslands. With regard to insects (e.g., leafhoppers and true bugs), it should be ensured that grazing is applied at low intensity.

Niche Construction and Long-Term Trajectories of Food Production

AbstractNiche construction theory has played a prominent role in archaeology during the last decade. However, the potential of niche construction in relation to agricultural development has received less attention. To this end, we bring together literature on the forms and sources of agronomic variability and use a series of examples to highlight the importance of reciprocal causation and ecological inheritance in trajectories of agricultural change. We demonstrate how niche construction theory can inform on emergent mutualisms in both inceptive and established agronomic contexts, the recursive relationships between humans and their agronomic environments, and bridges between the past and present.

Analysis of social and environmental agricultural transformations in Russia

The issues of achieving social and environmental sustainability are of high importance for the Russian agricultural economy. These issues are priority guidelines for the further development of the country’s economy as a whole, especially under an aggressive sanctions policy of the US and European countries. Maintaining environmental and social sustainability should be accompanied by ensuring economic growth and increasing the efficiency of reproductive processes in agriculture. The article studied and described the transformational processes in the Russian agricultural economy during the «sanctions» period from 2013 to 2022. Both the description of social and environmental changes in agriculture and the analysis of reproductive processes represent the novelty of the article. Thus, a comprehensive description of transformational changes in agriculture during the sanctions period is given. The study results are significant for the implementation of verified and differentiated agrarian policy on groups of regions. The extended analysis of homogeneous regions groups in Russia with a low, medium and high level of socio-ecological agricultural transformation was carried out using multidimensional methods of statistical analysis.

Components of agricultural productivity change: Replication of US evidence and extension to the EU

AbstractIncreasing agricultural productivity is a policy priority in many countries. O'Donnell (Am. J. Agric. Econ. 94(4): 873–890, 2012) decomposed productivity change in US agriculture using a Lowe total factor productivity (TFP) index. We replicate the original study, assess its robustness to alternative TFP indices, and extend the analysis to EU agriculture. We consistently find that productivity growth in US agriculture is mainly driven by technical progress. In EU agriculture, TFP growth is less pronounced, and both technical change and efficiency change contribute to productivity changes. In both US and EU agriculture, the magnitude of measured productivity change varies across indices, highlighting the need to rely on multiple indices for robust policy recommendations.

Action‐ versus results‐based policy designs for agricultural climate change mitigation

AbstractReducing agricultural greenhouse gas (GHG) emissions is key to achieve overall climate policy goals. Effective and efficient policy instruments are needed to incentivize farmers' adoption of on‐farm climate change mitigation practices. We compare action‐ and results‐based policy designs for GHG reduction in agriculture and account for farmers' heterogeneous behavioral characteristics such as individual farming preferences, reluctance to change and social interactions. An agent‐based bio‐economic modeling approach is used to simulate total GHG reduction, overall governmental spending and farm‐level marginal abatement cost of Swiss dairy and beef cattle farms under both action‐ and results‐based policy designs. We find that total governmental spending associated with the compared policy designs depends on the cost and benefits of the considered measures as well as behavioral characteristics of farmers. More precisely, if farmers are reluctant to change, additional incentives are needed to increase adoption of a win‐win measure. In such a case, targeting the payment on the cost of that particular measure (action‐based design) instead of paying a uniform amount for abated emissions (results‐based design) can lower governmental spending for agricultural climate change mitigation. Farm‐level marginal cost of reducing GHG emissions are lower with results‐based payments independent of the cost of measures. Moreover, we find that farmers' individual preferences and reluctance to change substantially lower the adoption of mitigation measures and hence overall GHG reduction potential of farms.

Environmental regulation and agricultural green productivity growth in China: A retest based on ‘Porter Hypothesis’

ABSTRACT Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the ‘Porter Hypothesis’ theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation.