Understanding dynamics of agricultural runoff to Oslofjord: A causal loop modelling approach.

ABSTRACT This article adopts the lived citizenship analytical framework and employs a qualitative case-study methodology to examine the experiences of the second-generation non-pastoral Fulanis and their descendants at Agogo in the southern part of Ghana. The aim, extending beyond Ghana and informing other Global South contexts, is to understand the complex processes of informal and lived citizen-making, exploring how marginalised groups, particularly ethnic minorities who have challenges with formal recognition, construct, negotiate and enact citizenship. The study problematises and critiques post-colonial (formal) citizenship frameworks in most African states shaped by colonial epistemic and institutional legacies of constructed arbitrary identities that exclude long-settled migrants and ethnic minorities. Such state-centric conceptions fail to capture the diverse ways differentiated groups experience and perform citizenship. Thus, shifting the focus from legal status, institutional belonging and abstract legal frameworks to lived realities of everyday experiences and certain mundane practices, I argue that citizenship is not always a matter of formal arrangements of belonging and performance in institutionalised settings. More importantly, it is lived, built and enacted in non-institutionalised spaces, enabling people to live together and cooperate in an orderly social life. The findings reveal that the Fulanis construct citizenship by asserting birth and residency; integration into Agogo’s agricultural economy; land acquisition and engagement in livelihoods; socio-cultural and economic relational practices; and subjective feelings of deep connections with other dominant groups and societal acceptance.

Dairy farming plays a critical role in Kenya's agricultural economy but also contributes significantly to greenhouse gas (GHG) emissions. Smallholder mixed crop-livestock systems dominate the sector and face challenges related to feed quality and manure management. This study aimed to assess the economic and environmental impacts of improved feeding strategies on smallholder dairy farms in the Lake Victoria Basin region of Western Kenya. Data were collected from 160 farms across Vihiga, Siaya, Kakamega, and Homabay counties and analyzed using economic modeling and IPCC Tier I and II methods to evaluate profitability and GHG emissions. Results indicated that replacing low-quality crop residues with high-quality forages improved milk yields and farm profitability, with a 9% increase in returns and a 6% reduction in production costs per kilogram of fat and protein-corrected milk (FPCM). GHG emission intensity per kilogram of FPCM decreased by 11%, mainly due to enhanced feed efficiency and increased milk production. Manure management practices, particularly the use of covered solid storage, also contributed to reduced methane and nitrous oxide emissions. The study concludes that adopting high-quality feed and proper manure management enhances both farm productivity and environmental sustainability. Policymakers are encouraged to support access to quality forage and promote climate-smart practices among smallholder farmers. Further research should explore genetic improvements and precision feeding as additional mitigation strategies.

Bovine tuberculosis is a persistent and significant challenge for cattle farmers in Zambia, especially among rural farmers. As livestock farming constitutes a crucial component of the country’s agricultural economy, the prevalence of bTB threatens not only animal health and productivity but also poses serious risks to human health, food safety, and economic stability within rural communities. A mixed-methods study was conducted in Lundazi and Monze districts of Zambia between December 2021 and June 2022, combining a cross-sectional survey of 280 respondents with qualitative insights from five focus groups and five key informant interviews. Data analysis was done using R software for quantitative data and NVivo for qualitative data. Our study indicates that cows infected with bTB experience an average decline in milk production of approximately 3.75 liters per day, translating to a substantial economic loss of approximately ZMW 10.00 per cow per day, based on an average milk price of ZMW 8.00 per liter. Reported bTB-like symptoms were significantly associated with reduced monthly income from livestock farming. Among education levels, only primary education had a significant association with bTB awareness, with higher odds of impact. Qualitative findings indicate that rural elderly individuals aged 40 and above bear a disproportionate burden of bTB’s impact on public health, likely due to livestock handling and consumption practices increasing zoonotic transmission risks. Our study reveals evidence of the significant impact of bTB on rural cattle farming, with critical implications for policy and practice. It highlights the need for appropriate interventions to address the disproportionate burden of bTB among vulnerable populations, such as older people and those with primary education. Prioritizing bTB control and prevention can minimize the economic and health impacts of the disease and promote more sustainable and resilient livestock farming systems.

This review synthesizes recent advances and develops an integrative regulatory framework that links shoot apical meristem size control to tomato fruit locule number, encompassing genetic, phytohormonal, and environmental determinants. Tomato is a globally vital vegetable crop that contributes significantly to human nutrition and agricultural economies. The number of locules, a key component of fruit morphology, is a primary determinant of ultimate fruit size and shape, thereby influencing both market yield and consumer preference. This review focuses on how shoot apical meristem size control acts as a core hub that connects genetic, hormonal, and environmental cues to the regulation of tomato fruit locule number. We synthesize recent progress in understanding the molecular and physiological mechanisms behind locule determination, with a particular focus on integrative networks linking known regulators. By bridging insights from these interconnected domains, we aim to present a more holistic view of the developmental process. Furthermore, we propose avenues for future research aimed at achieving a deeper understanding of the modulation mechanisms that govern fruit locule formation and their numerical count in this vital crop.

Wheat (Triticum aestivum L.), playing a significant role in providing food security and agricultural economy, is one of the most important cereals in the world. The present experiment aimed to determine the optimal levels of organic compounds (fulvic acid, humic acid, and amino acids) to promote sustainable wheat (cv. Taktaz) cultivation in dry and semi-dry regions while reducing dependency on irrigation water. The experiment was conducted as a split-factorial based on a randomized complete block design (RCBD) with three replications during two cropping years, 2023-2025. Results indicated that three-way interactions were statistically significant at the 0.01 level for all traits except number of fertile spikes and number of grains per spike. According to the polygon view of the traits, applying high amounts of fulvic acid as well as average amounts of the amino acid can have positive effects on controlling stress. In addition, increasing the concentration of humic acid can compensate for low concentrations of compounds like fulvic acid and amino acids. According to the treatment stability diagram, treatments 3 (humic acid 12L h- 1) and 6 (amino acid 1.5L h- 1, humic acid 12L h- 1) under normal irrigation conditions, and 27 (fulvic acid 6L h- 1, amino acid 3L h- 1, humic acid 12L/ha) under drought stress conditions, were selected as desirable treatments. The fact that increasing organic matter, like fulvic acid and amino acids, is helpful in plant metabolism regulation and resistance enhancement against drought stress reveals the effects of compounds included in these treatments on the plant's resistance to the stress. The treatment with the highest amount of organic compounds (6L ha- 1 fulvic acid, 3L ha- 1 amino acid, 12L ha- 1 humic acid) was identified as the treatment with positive coefficients in relation to the first two components in both years. Under drought stress conditions in both years, grain yield had positive coefficients for the first two principal components. Likewise, flag leaf width had positive effects on the fourth component in both years. Treatments with high fulvic acid and medium humic acid (3L ha- 1 fulvic acid, 1.5L ha- 1 amino acid, 12L ha- 1 humic acid; 6L ha- 1 fulvic acid; and 6L ha- 1 fulvic acid, 8L ha- 1 humic acid) consistently appeared with strong relationships in the correlation network in both years. In general, treatments with moderate fulvic acid and high humic acid can be selected as desirable treatments under both normal and stress conditions. Selecting these treatments indicated that using fulvic acid and humic acid, along with an amino acid that plays a significant role, had the highest positive effects on yield improvement under both normal and irrigation stress conditions.

Enhancing agricultural economic resilience (AER) is essential for global food security. As a key policy tool for stabilizing agricultural production, policy-based agricultural insurance lacks rigorous causal evidence on its impact on resilience. In this study, AER is operationalized as a composite index capturing resistance and recovery capacities across pressure, state, and response dimensions. Using 2012–2023 provincial panel data from China (31 provinces × 12 years = 372 observations), we measure AER via the entropy method and identify policy effects using a staggered multi-timepoint difference-in-differences (DID) model. We find that policy-based staple crop insurance significantly increases AER by approximately 2.5 percentage points, primarily by promoting agricultural technological innovation (ATI) and regional industrial structure upgrading (RIS). The improvement effects are more pronounced in central and western regions, non-major staple-crop producing areas, and regions with higher natural risks. Robustness is confirmed via event study, alternative weighting schemes (PCA and equal weighting), and placebo tests. This study provides reliable causal evidence for the resilience-enhancing effect of agricultural insurance and clarifies its internal transmission mechanisms, offering empirical support for the optimization of agricultural risk governance policies. Limitations include the use of provincial-level aggregate data and the lack of analysis of spatial spillover effects between regions. Our findings suggest that differentiated policy implementation can support more sustainable and targeted agricultural risk governance.

Agriculture has the nature of serving as both a carbon source and carbon sink. Exploring the net carbon effect of agriculture in Guizhou Province and its coupling effects with economic development， as well as analyzing the historical changes and future trends of factors affecting net carbon amount， is of great value for promoting Guizhou Province's agriculture sector to achieve the "dual carbon" goals. In this study， we calculated the net carbon effect of agriculture in Guizhou Province from 2005 to 2022， explored the coupling state changes between the net carbon sink of agriculture and agricultural output value in Guizhou Province using the Tapio decoupling model， decomposed the driving factors of the net carbon sink of agriculture in Guizhou Province based on the logarithmic mean Divisia index （LMDI） model， and further analyzed the dynamic relationship between influencing factors and agricultural net carbon sink using the vector autoregressive （VAR） model to predict the agricultural net carbon sink. The results show that： ① During the study period， Guizhou Province's agriculture exhibited net carbon sink characteristics， with corn and rice being the main carbon sinks， while livestock and poultry farming were the main carbon emission sources. ② The coupling effect between Guizhou Province's agricultural net carbon sink and agricultural output value exhibited two states： economic/ecological dominant coupling and ecological weakening coupling. ③ The level of agricultural economy promoted the agricultural net carbon sink， while the intensity of agricultural net carbon sink， the scale of agricultural labor force， and the agricultural industrial structure all inhibited the agricultural net carbon sink， with decreasing effects in order. ④ From a dynamic perspective， after being impacted by four influencing factors， the agricultural net carbon sink exhibited repeated fluctuations of positive and negative effects over a certain period. From 2023 to 2030， Guizhou Province's agricultural net carbon sink will basically remain around 400×104 t， showing a characteristic of "low-level stabilization." Based on this， it is proposed that the development of low-carbon agriculture in Guizhou Province should be facilitated by realizing the economic value transformation of agricultural carbon sinks， reasonably adjusting the agricultural economic development model， and optimizing labor resources.

Automated detection of defective coffee beans based on improved YOLOv10 framework

Optimizing a new robust location-pricing problem in agricultural economy by customized bi-level algorithm

Cotton ( Gossypium hirsutum L.) is a critical crop for Georgia's agricultural economy, with variety selection being a critical decision for farmers due to its impact on yield and fiber quality. To support this process, we developed an interactive variety recommender tool using data from the University of Georgia (UGA) On-Farm Cotton Variety Evaluation Program, which includes 117 trials conducted across 35 sites over five years (2020–2024) under both irrigated and dryland conditions. This application note presents a methodological framework for variety recommendations, which integrates advanced analytical tools to evaluate and compare genotype performance across diverse environments. The dashboard enables users to interactively explore the dataset through a range of visualizations, including county-specific information, variety recommender, trait comparisons, state-level performance, and environmental ranking. A built-in variety recommender tool ranks top-performing genotypes based on mean relative performance. Additionally, the dashboard provides detailed trial management information to support comprehensive decision-making. By allowing comparisons across yield, ginning turnout, loan value and fiber quality metrics, the platform assists farmers, county agents, and consultants in optimizing variety selection in Georgia. While the results reflect past performance and must be interpreted in the context of local agronomic and technological factors, the tool effectively translates complex multi-environment trial data into actionable insights. Finally, it aims to enhance both productivity and sustainability in cotton production across Georgia, U.S. through informed, data-driven decision-making. • An interactive dashboard to help cotton variety selection in Georgia, USA. • Utilizes data from 117 on-farm trials over five years (2020–2024). • Ranks genotypes based on mean relative performance across environments. • Translates complex multi-environment trial data into actionable insights.

A comprehensive assessment of a product's economic viability, along with a value chain analysis, is essential to identify opportunities for improvement, ascertain actual costs and margins, understand the interrelationships between activities, and enhance production efficiency. This study evaluates the economic viability and value chain of summer tomato cultivation, a sector gaining importance due to rising off-season demand and price premiums. A total of 50 summer tomato growers and 45 traders were selected using multi-stage sampling techniques from the Netrokona and Kishoreganj districts in Bangladesh. The results indicates that the adoption levels of ploughing, planting periods, seedling usage, pesticide application, and hormone use were high, whereas the use of urea, gypsum, MoP, boron, and zinc was low. The total cost of summer tomato cultivation was Tk. 2,75,606 per acre, while the average net return per acre was Tk. 3,43,364. The Benefit-Cost Ratio (BCR) of summer tomato cultivation was found to be 2.25, indicating that producing summer tomatoes is economically viable. Seven marketing channels were identified, with retailers contributing 42.58% of the overall value addition, marking the most significant contribution to the gross marketing margin. The summer tomato value chain in Bangladesh is sustainable due to its capacity to create income, encourage efficient resource utilization, enhance food security, and adapt to climatic changes. By maintaining investments in technology, training, and market systems, this value chain has the potential to flourish and contribute to a more resilient and inclusive agricultural economy.

Lameness in broiler chickens, frequently caused by bacterial chondronecrosis with osteomyelitis (BCO), poses a major challenge to intensive poultry production due to its adverse impact on animal welfare and farm economics. While Staphylococcus aureus has traditionally been considered the principal staphylococcal pathogen in poultry, coagulase-negative staphylococci (CoNS) are increasingly implicated in skeletal infections. This study aimed to characterize the phenotypic and genotypic antimicrobial resistance profiles of 93 CoNS isolates representing 12 Staphylococcus species. Isolates were recovered from bone and joint lesions of lame broiler chickens from 25 commercial flocks in Poland and were characterized using disk diffusion testing, PCR-based detection of selected resistance genes, pulsed-field gel electrophoresis (PFGE), and exploratory whole-genome sequencing (WGS). Disk diffusion testing and PCR screening revealed a high prevalence of resistance to penicillin, doxycycline, and erythromycin, with blaZ (37.6%; 35/93), lnu(A) (37.6%; 35/93), tet(L) (25.8%; 24/93), tet(M) (22.6%; 21/93), and erm(C) (12.9%; 12/93) being the most commonly detected determinants. The mecA gene, conferring resistance to β-lactams, was detected in a subset of isolates (16.1%; 15/93) although phenotypic resistance did not always correlate with mecA presence. Femoral-head lesions (FHN/FHT/FHS; n = 50) yielded isolates with resistance profiles broadly similar to those observed in the overall collection. PFGE of S. cohnii demonstrated genetic heterogeneity within the analyzed subset. Whole-genome analysis of S. cohnii strain SC27 identified multiple AMR-associated determinants and mobile genetic elements. These findings indicate that CoNS associated with broiler skeletal lesions can harbor diverse AMR determinants linked to several widely used antimicrobial classes. Our findings are primarily relevant from an epidemiological and surveillance perspective. The study also adds new genomic and epidemiological context to current knowledge of AMR in broiler-associated CoNS and supports their inclusion in ongoing veterinary and One Health-oriented surveillance efforts.

Olfaction-based biosensor technology in cattle reproduction: Current status and future perspectives.

A monitoring campaign was carried out in a Mediterranean agricultural district by transplantation of thalli of the lichen Evernia prunastri to 32 stations to evaluate the distribution of pesticides, the development of drift events, the dimension of the area, and the level of exposure in the Cantinella village. Spearman correlation coefficients and PCA performed on the database stations × pesticides revealed that they were sprayed as mixtures and mostly bioaccumulated in the northern part. Spirotetramat and Hexythiazox exhibited the highest levels, consistent with the pests, being the former sprayed to contrast Tetranychus urticae, the most diffused species, and the latter used as a multi-spectrum pesticide. Based on the Calabria Region treatment schedule and covariance between pesticide spatial variation, we believe that Hexythiazox and Acetamiprid treatment has gone beyond prescribed deadline. Drift events were associated with the detection of pesticides in Cantinella and zones managed with organic agriculture criteria and to the significant correlation between the concentration patterns and wind flows. All the pesticides were detected inside Cantinella stations pointing to a potential co-exposure of the inhabitants to them. Spirotetramat concentration was 80% higher than that of the outside stations. The green-cement cover ratio was strongly inadequate for reducing atmospheric pollution, with a significant spatial variation (chi-square test) in green areas (northern side: 14%, southern side: 24%) associated with the percentage of single and total pesticide loads (northern side: 25%, southern side: 7%). Our data suggest that widespread drift, caused also by over-spraying, can damage the agricultural economy and promote pesticide inhalation by residents, especially when urban characteristics increase exposure.

ABSTRACT Continuous adoption of green control techniques (GCTs) represents an eco-friendly practice that enhances agricultural resilience by mitigating farmers’ misuse of and overreliance on chemical pesticides. The internet has penetrated rapidly in rural China. While farmers’ internet use is a novel form of human capital, its efficacy in promoting GCTs remains underexplored. This study investigates the impact of internet use on continuous GCT adoption and its subsequent effect on farm performance, using a dataset of 874 farmer surveys. To address endogeneity, we employ a control function approach and conditional mixed process model. We find that internet use raises the probability of physical and biological control techniques’ continuous adoption by 7.2% and 8.1%, respectively, and GCTs significantly improve crop yields and agricultural income. This study contributes to the literature by (1) redefining internet use as a novel form of agricultural human capital, expanding human capital theory’s scope and theoretical boundaries, and (2) constructing the ‘internet use → GCT adoption → farm performance’ analytical framework, offering new empirical evidence in green agricultural economics.

Accurate estimation of dynamic environmental phenomena through intelligent sensing systems plays a critical role in enabling reliable monitoring and decision-making in complex real-world scenarios. With the rapid development of artificial intelligence-driven sensing technologies and Internet of Things systems, modern agricultural monitoring is evolving from isolated data acquisition toward intelligent, multimodal perception and decision-making. However, traditional approaches predominantly rely on single data sources, making it difficult to simultaneously capture plant phenotypic variations and environment-driven mechanisms, thereby limiting model applicability in complex field scenarios. To address this issue, a multimodal pest density estimation framework, namely the Pest Density Estimation Framework (PDEF), is proposed, which integrates UAV-based imagery, trap monitoring data, and environmental sensor measurements. In this framework, crop canopy damage features are extracted using convolutional neural networks, while temporal encoding is employed to model dynamic environmental variations. Cross-modal feature alignment and environment-aware enhancement mechanisms are further introduced to achieve deep integration of multi-source information, enabling the construction of a unified feature representation space and improving estimation accuracy. Extensive experiments conducted on a constructed multimodal agricultural dataset demonstrate that the proposed method achieves MAE, RMSE, and MAPE values of , , and , respectively, significantly outperforming the Transformer-based fusion model (MAE , RMSE ). Meanwhile, the coefficient of determination reaches , indicating superior fitting capability and stability. In multimodal combination experiments, the three-modality fusion reduces error metrics by more than on average compared with single-modality models, validating the effectiveness of multi-source collaborative modeling. From the perspective of integrating plant phenotypic analysis and environmental perception, this study provides a novel AI-driven intelligent sensing framework for pest monitoring and crop management, contributing to improved pest prediction capability and enhanced intelligence in agricultural production systems. This study further provides practical implications for agricultural economics and supply chain optimization by enabling data-driven decision-making through intelligent sensing systems.

ABSTRACT Climate change is urgent and has multifaceted impacts on agricultural production and the national food security system, especially in climate‐vulnerable agricultural economies. The present study assesses the role of climate shocks and agricultural emissions in agricultural productivity and food dependency in China and the European Union (EU). Using the time series data, it adopted the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) methods in empirical estimation. The results show that climate shocks increase (decrease) food dependency (agricultural productivity) in China, whereas climate change decreases agricultural output and food dependency in the EU. On the one hand, agricultural carbon emissions boost (decline) agricultural productivity (food dependency) in China and stimulate it in the EU. In the robust analysis, the canonical cointegrating regression (CCR) confirms the results of the regression. Overall, the study provides comprehensive and cohesive climate policies for sustainable food supplies and agricultural production. From a policy suggestion, China and the EU need to accelerate the adoption of smart agriculture technologies—such as precision farming, digital monitoring systems, climate forecasting tools, and data‐driven irrigation—to enhance input efficiency, reduce environmental externalities, and stabilize production under climate uncertainty.

Coffee-price volatility is a recurrent external shock for Peru’s small open economy, with potentially uneven consequences across sectors. This study evaluates whether global coffee prices and domestic macro-agricultural indicators share stable long-run equilibria and quantifies the transmission of coffee-price shocks to the terms of trade, nominal exchange rate, consumer prices, agricultural GDP, and total GDP. Using a multivariate vector error-correction model identified via Johansen cointegration, and controlling for major global disruptions and ENSO-related seasonality, we trace dynamic effects through impulse-response analysis. The results indicate economically meaningful cointegration, implying that external prices and domestic aggregates are linked by long-run restrictions. A positive coffee-price shock produces heterogeneous real effects: the response of aggregate GDP is modest and short-lived, while agricultural GDP reacts more strongly and persistently. The shock propagates mainly through external and nominal channels—especially the exchange rate and terms of trade—whereas consumer-price pass-through is present but comparatively moderate. These findings contribute to the commodity-shock literature by providing sector-sensitive evidence for an agricultural export shock and by clarifying the mechanisms through which coffee-price movements propagate to domestic activity and prices in a small open agricultural economy.

• We provide an overview of empirical approaches in production economics that focus on credible identification of a small number of model parameters. • We provide a historical context: where they came from, how they differ, and where we think the methodological landscape is headed. • We focus on ag production and provide specific examples of research in the climate change, agricultural policy, and technology arenas. We provide an overview of increasingly common empirical approaches in production economics that focus on credible identification of a small number of model parameters, the value of which is couched within a practitioner’s perspective on the evolution of empirical methods in this literature dating back to the mid-twentieth century. That is, we provide a historical look at where these approaches came from, how they differ from previous approaches, and where we think the methodological landscape is likely headed. Our particular focus is on the agricultural production literature, and we provide specific examples of research in the climate change, agricultural policy, and technology arenas. We also discuss recent innovations in data and methods that have driven empirical work to date and point to how these methodological advances (and perhaps future advances) can be leveraged to push the agricultural production economics literature forward. We conclude with some general take-away messages and highlight trade-offs researchers often make when choosing an empirical approach.