The integration of nanotechnology into agriculture presents a transformative approach to enhancing productivity and sustainability. Nanoparticles (NPs), including nano-plant growth promoters, nanopesticides, nanofertilisers, nano-herbicides, and agrochemical-encapsulated nanocarrier systems, offer precise and efficient solutions for improving crop yields, pathogen resistance, abiotic stress tolerance, targeted weed and pest control, and soil bioremediation. These advancements contribute to reduced resource consumption and minimal environmental waste through controlled delivery mechanisms. However, the increasing application of NPs in agriculture raises significant concerns regarding their environmental footprint, synthesis methods, long-term fate, and potential adverse effects on plant-associated microorganisms vital for soil fertility and plant health. Addressing these challenges requires a comprehensive evaluation of NPs interactions within agroecosystems through long-term experimentation, including Life Cycle Assessment and the development of environmentally friendly green synthesis methods. This review highlights the need for standardised testing methods to ensure nanotechnology is used safely and effectively in sustainable farming, balancing innovation with ecological responsibility. • Nanotechnology boosts farm efficiency, sustainability, and crop resilience. • Nano-carriers enable targeted delivery, saving resources and reducing waste. • Safety concerns of nanoparticles must be addressed for secure farm use. • Effects on soil microbes need study to safeguard soil and ecosystem health. • Green synthesis and LCA cut risks, ensuring safer nanoparticle applications.

Agricultural productivity and climate change vulnerability in West Africa: The role of technological innovation and carbon reduction strategies for sustainable agriculture

In the face of global population growth, climate volatility and mounting ecological pressures, agricultural science is shifting from traditional yield-centered paradigms toward integrated, sustainable development models. This study employs CiteSpace (version 6.1.5) to conduct a comprehensive bibliometric analysis of 1780 scholarly publications on agricultural science research from 2000 to 2024, drawn from both the Web of Science and China National Knowledge Infrastructure (CNKI) databases. By adopting a systematic process of article selection as represented by the PRISMA flowchart, the dataset was refined through rigorous inclusion and exclusion criteria to ensure analytical robustness. CiteSpace, a powerful visualization and analysis tool, and VOSviewer were used to conduct keyword co-occurrence mapping, cluster analysis, temporal evolution modeling and institutional collaboration analysis. The results reveal three dominant global research themes: climate change adaptation, agricultural system resilience and technological innovation. Global trends augment precision agriculture, carbon management and digitalization. Chinese studies continue to focus on yield increment and improvement of principal crops, underlined by the growing application of smart agriculture, ecological administration and rural revitalization policies. Institutional research finds Jiangsu University to be an essential node in China's agricultural science network. By synthesizing cross-regional, bilingual datasets, this study offers new evidence for the converging but also diverging paths of agricultural research worldwide and in China. Such evidence is supportive of the use of evidence-based policy making, academic strategy and innovative agricultural reform in the context of sustainable development. © 2025 Society of Chemical Industry.

Poverty and food security are two closely interrelated global issues and are top priorities in the Sustainable Development Goals (SDGs) agenda, particularly SDG 1 (no poverty) and SDG 2 (no hunger). This study aims to analyze the spatial correlation between poverty and food security in Central Java in the 2023–2024 period. The research method used is a quantitative descriptive approach with spatial analysis using Moran's I and Local Indicator of Spatial Association (LISA). Secondary data were obtained from the Central Statistics Agency (BPS), the National Food Agency, and administrative maps in shapefile form. The analysis was conducted using GeoDa software, by examining univariate and bivariate spatial autocorrelation patterns, as well as mapping High-High, Low-Low, High-Low, and Low-High clusters. The results show that the distribution of poverty and food security indices in Central Java is not random, but rather forms a clustered pattern. Bivariate analysis shows a negative spatial correlation, where areas with high poverty rates tend to be associated with low food security. The LISA Bivariate Map identifies clusters of High-High areas concentrated in the southern and coastal regions, while urban areas tend to be in the Low-Low category with relatively better socio-economic conditions. The implication of these findings is the importance of spatially based development policies that integrate poverty alleviation programs with improving food security. Therefore, spatially integrated policy interventions are crucial. Local governments are recommended to prioritize targeted programs in High–High areas, including improving rural food logistics and distribution infrastructure, expanding community-based microfinance and agricultural innovation programs.

As the greenhouse effect and the environmental problems thus arising become increasingly prominent, great concern has been aroused for agricultural carbon emissions reduction and sustainable development. Aiming at exploring how to reduce agricultural carbon emissions from agricultural green finance perspective, this study theoretically analyzed the impact and mechanism of agricultural green finance on agricultural carbon emission intensity, and empirically examined the specific impact and the corresponding impact mechanism of agricultural green finance on agricultural carbon emission intensity. Specifically, a two-way fixed effect model was employed to conduct the study based on the panel data of 30 provinces in China from 2011 to 2022. The results show that agricultural green finance can significantly reduce agricultural carbon emission intensity, which has been verified to be valid after a series of robustness tests; and the reduction displays a heterogenous pattern. As it is, the impact of agricultural green finance is more prominent in the eastern region than in the central and western regions, and greater in non-major-grain-producing areas than in major grain-producing areas. On this basis, some policy suggestions are put forward, mainly including developing agricultural green finance, promoting agricultural and green technological innovation, and implementing differentiated agricultural green finance policies so as to reduce agricultural carbon emission intensity.

The purpose of this study was to analyze the factors affecting the productivity of rice farmers. This study employed a quantitative research design with an inferential statistical approach using SmartPLS. The research was conducted in five rice farming areas in Kutai Kartanegara Regency, East Kalimantan Province, Indonesia, with a sample size of 146 respondents. The results indicate that extension communication has a positive and significant effect on farmers' knowledge. However, the effect on farmers' skills is positive but not significant. Extension communication has a negative and insignificant effect on innovation adoption, and a positive but insignificant effect on farmer productivity. The effect of farmers' knowledge on innovation adoption was negative and an insignificant, while its effect on farmer productivity was positive but not significant. In contrast, the effect of farmers' skills on innovation adoption and farmer productivity was positive and significant. This study has several limitations. First, it focuses only on rice farmers in the five agricultural areas designated by the Kutai Kartanegara Regency government, so the results cannot be generalized to other areas with different conditions. Second, this study does not consider external factors that may influence the successful adoption of agricultural technology innovations, such as government policies, market access, and weather conditions.

ABSTRACT Asian mega-deltas face a ‘triple crisis’ of climate hazards, adverse impacts of top-down adaptation policies, and agrarian market liberalization, threatening millions of resource-based farmers. While farmers’ vulnerabilities have been extensively documented, this paper examines an emerging small-scale farmers group in Vietnam’s Mekong Delta, which will be termed ‘innovative farmers’, who are shown to successfully navigate these pressures and thrive in hostile conditions. Using an analytical framework integrating sustainable livelihoods, agency, and innovation, with a focus on power dynamics, we draw on semi-structured interviews (n = 27) and field observations to elucidate and conceptualize mechanisms and drivers underlining the success of innovative farmers. Data were collected in Ca Mau Province, a hub of engineered adaptation policies. Nvivo version 14.0-based thematic coding with inter-rater validation was applied. Findings reveal that most innovative farmers shared the vulnerable backgrounds of their peers but managed to mobilize human, physical, social and political capitals to transform their livelihoods through self-directed innovations. They adopted nature-based farming systems and actively engaged in local governance, creating a ‘virtuous circle’ of economic self-reliance, environmental sustainability, and political inclusiveness. Their success stories depicted in this paper offer an alternative reform model that is both economically viable and environmentally sustainable.

This study explores the opportunities and challenges facing African businesses in contributing to the achievement of the United Nations Sustainable Development Goals within the frameworks of Agenda 2030 and Agenda 2063, against a context of persistent poverty, inequality, environmental degradation, and institutional limitations. A systematic literature review guided by the PRISMA approach was conducted using peer-reviewed articles published between 2000 and 2023 and sourced from major academic databases, with rigorous screening, data extraction, and bias assessment procedures applied. The findings identify five dominant themes shaping SDG engagement in Africa, namely the integration of SDGs into business strategy, challenges and opportunities confronting firms, multi-stakeholder partnerships, SDG reporting and measurement practices, and SDG finance and investment mechanisms. The review reveals that although African firms are increasingly aligning business strategies with environmental, social, and governance principles and contributing to SDG outcomes through innovations in financial inclusion, renewable energy, agriculture, and social investment, progress remains constrained by short-term strategic orientations, weak institutional capacity, limited access to sustainable finance, fragmented partnerships, and inconsistent reporting practices. While partnerships and innovative financing instruments such as green bonds and blended finance demonstrate strong potential to accelerate SDG progress, their effectiveness is undermined by regulatory weaknesses, high transaction costs, and capacity gaps. Overall, the study concludes that African businesses can play a transformative role in advancing the SDGs if sustainability goals are embedded within core business models, supported by robust governance frameworks, context-sensitive measurement systems, inclusive partnerships, and financing structures that incorporate indigenous knowledge systems and prioritize long-term sustainable development over short-term gains.

Manual cacao pod harvesting involves intricate tasks that significantly impact the overall efficiency of the process. This study comprehensively analyses motion and time allocation during manual cacao pod harvesting. Employing both visual-based and motion-capture methodologies, this research offers insights into task categorization and time utilization. Visual-based analysis identified four primary tasks—searching for, severing from trees, lifting and carrying — revealing that searching consumed the most time (49%), followed by severing (33.2%) and lifting and carrying (17.8%). The lifting and carrying task was further divided into two sub-tasks: lifting pods and transporting them to a designated collection point. Models were trained to classify tasks using the Support Vector Machine with Radial Basis Function (SVM RBF) algorithm in motion capture. However, discrepancies were observed between observed and predicted time usage for tasks, potentially due to nuances in motion execution among workers. Performance metrics highlighted limitations in task identification by the classification models. Suggestions provided for model improvement included incorporating diverse motion patterns in the training data and considering sub-task classifications for better accuracy. This study underscores and highlights subtasks during the harvest that can be easily automated to quickly enhance harvest process efficiency. • Developed the first video–motion analysis of manual cacao harvesting tasks. • Established standardised hierarchical task and sub-task taxonomy. • Analysis revealed that search and severing are the dominant efficiency bottlenecks. • Validated a ML model using joint-angle kinematics to classify harvesting tasks. • Identified tasks suitable for mechanisation and guide design for robotics. Science4Impact Statement (S4IS)This study investigates manual cacao pod harvesting, revealing that significant time is consumed in searching for ripe pods (49%) and severing them from trees (33.2%). These findings suggest potential automation opportunities that could streamline harvesting processes. The results support regulatory frameworks by demonstrating how improved harvesting methods can enhance food security and labour efficiency. Implementing these advancements could contribute to sustainable agricultural practices, ultimately addressing climate change and food production challenges, thereby aligning with societal goals for agricultural innovation.

The Food Security Strengthening Program through Biosaka Education and Vegetable Seed Distribution in Bekiring Village, Pulung Sub-district, Ponorogo Regency, was implemented using the Asset Based Community Development (ABCD) approach. The program aimed to improve household food self-sufficiency by utilizing home yards and adopting environmentally friendly agricultural innovations. The methods included training on the production and application of Biosaka, vegetable cultivation practices using polybags, and the distribution of short-term vegetable seeds such as chili, tomato, and eggplant. The results indicate an increased community understanding of food diversification, collective awareness of yard utilization, and active participation in vegetable cultivation. The program’s strengths lie in its simple, low-cost, and practical methods, making it easily accepted by the community, particularly among low-income families. However, limitations such as restricted mentoring time and uneven technical comprehension among residents remain as challenges. Future program development should emphasize continuous mentoring, diversification of plant varieties, and the establishment of household farmer groups to ensure stronger and more sustainable community food security.

This review examines the transformative role of Artificial Intelligence in mitigating cereal crop damage caused by birds, highlighting its potential to enhance food security, improve agricultural sustainability, and support the livelihoods of farmers in Ghana. Food and nutrition security remain pivotal for sustainable development in Ghana, with agriculture contributing significantly to employment, food production, and economic growth. Among the pressing challenges facing Ghanaian farmers is bird-induced damage to cereal crops such as maize, millet, sorghum, and rice, which undermines productivity, food security, and farmer livelihoods. Traditional bird control methods such as scarecrows and manual labor, are often labor-intensive, costly, and increasingly ineffective at scale and raise social concerns, including child labor and school dropout. With advancements in technology, AI has emerged as a reliable solution for addressing these challenges. AI-powered systems, including drones equipped with bird detection and repellent technologies, offer innovative and sustainable alternatives to conventional with the potential of reducing 15-30% cereal crop losses caused by birds in Ghana while connectivity of Farmer Based Organizations to AI-based bird control systems increase accessibility and affordability for small scale farmers. Companies such as AiScarecrow have developed drones that mimic predatory birds, scaring away pest species through simulated threats while ensuring minimal harm to the environment, cutting down 90% field losses while saving an average of 8-10 hours a day of valuable time. These systems enable real-time monitoring, species-specific responses, and efficient deterrent mechanisms that significantly reduce bird-induced crop losses while minimizing environmental impact. This review synthesizes literature up to date on AI applications, bird deterrence technologies, and agricultural innovation in Ghana. The analysis identifies emerging approaches, key barriers to adoption, and directions for future research. The study highlights the urgency and feasibility in integrating AI-driven bird control into Ghana’s agricultural strategies to strengthen food security while promoting sustainable, technology-enabled farming.

Soil is a living system that underpins food security, biodiversity, climate regulation, and human civilization itself. Yet global soils are degrading at an unprecedented rate due to intensive agriculture, deforestation, urbanization, pollution, and climate change. The concept of soil reproduction—the capacity of soil to regenerate its structure, fertility, biodiversity, and functions over time—offers a critical framework for safeguarding land for future generations. This review examines soil reproduction as a dynamic biological, chemical, and physical process shaped by natural cycles and human intervention. It synthesizes current understanding of soil formation, degradation pathways, and regenerative strategies, emphasizing that soil recovery is not automatic but requires intentional management. By integrating ecological principles, agricultural innovation, policy reform, and societal engagement, soil reproduction can be accelerated. Preserving and restoring soils is not only an environmental priority but a foundational investment in long-term sustainability, resilience, and planetary health.

The asymmetric impact of agricultural finance and technological innovation on sustainable food production and emission reduction in Indonesia

Abstract The global food system must confront the intertwined challenges of feeding a growing population, reversing environmental degradation, and improving nutrition. While past agricultural innovations improved yields, they often undermined sustainability and food quality. In response, we propose the 3N Agriculture framework—Net‐Zero, Nature‐Positive, and Nutrient‐Balanced—as an integrated strategic model to transform agriculture into a resilient, restorative, and health‐promoting system. Unlike siloed approaches, 3N Agriculture integrates climate mitigation, biodiversity conservation, and nutritional enhancement within a single coherent strategy. It calls for systemic changes in energy use, land management, biodiversity stewardship, and food production, aligning productivity with environmental and human health goals. The framework provides a practical pathway to move beyond fragmented implementation of the Sustainable Development Goals and secure food systems and landscapes for future generations. Core Ideas The 3N Agriculture framework unites Net‐Zero, Nature‐Positive, and Nutrient‐Balanced imperatives. Integrated 3N strategies address climate, biodiversity, and nutrition challenges simultaneously. Policies, markets, and knowledge systems are essential to scale 3N Agriculture across all levels. 3N offers a distinct, systems‐based pathway beyond regenerative and climate‐smart agriculture.

Societal Impact Statement Agricultural innovations underpin most investments that aim to increase agricultural productivity globally. Improved crop varieties have historically constituted the bulwark of agricultural innovation outputs and are credited with the success of large‐scale interventions such as the Green Revolution. Much research has shown, however, that gender shapes agricultural technology adoption, increasingly understood in relation to the age, race, and ethnicity of the respondent. Our study shows how decisions made by researchers when designing crop varietal adoption studies, including who in a farming household is asked and how they are asked about adoption, significantly shape reported adoption rates, highlighting potential errors in reported crop varietal adoption rates. Summary Accurately measuring agricultural technology adoption rates underpins impact claims made for new technologies. While numerous studies have documented gender‐based differences in the adoption of agricultural technologies, there remains an urgent need to understand how study design and respondent selection within households shape these reported differences. We explore the case of improved cassava varieties (ICV) in Nigeria to examine differences in reporting on varietal adoption rates based on sampling method, level of analysis, and household position. We compare intrahousehold (spousal), household, and plot‐level data for self‐reported rates of ICV adoption and compare these to data from DNA fingerprinting. We identify significant disparities in reported rates of ICV adoption at the household, spousal, and plot levels, most of which were different from DNA fingerprinting data collected from respondents' plots. Our findings shed light on the importance of participant selection in varietal adoption studies and raise questions around self‐reported adoption rates in the literature. Varietal adoption rates are used to measure a breeding program's success and impact. However, this study shows that estimated rates can differ significantly depending on adoption study design–including unit of analysis, selection of data source, and how the questions are asked. We call for more data feminism around crop varietal adoption studies, study designs that minimize bias, expanded design standards to include multiple respondents within each household, and multiple data analysis methods that reflect the plurality of experiences with adoption among farmers.

Abstract Climate Smart Agriculture promises to increase the resilience and productivity of vulnerable agricultural systems in Sub-Saharan Africa. However, the narrow focus on technological adoption rather than on the systematic and uneven distribution of CSA benefits often results in implementation falling short of expectations. This editorial synthesizes the special issue on CSA interventions in five African countries, going beyond conventional narrative accounts of impact to explore critical and unexplored dimensions. Overall, the findings suggest that adoption is a dynamic process, driven by climate shocks and opportunity costs, and not a linear decision-making process. Although CSA may generate macroeconomic benefits, the benefits are often reaped by wealthier, urban actors, which exacerbates rural inequality. Importantly, the performance of technologies is highly contextual and success depends on complementary investment and institutional support. Studies also show that joint decision-making between spouses within the household leads to better results and that pastoral systems require integrated, socially embedded interventions. We argue that an effective CSA cannot be a one-size-fits-all technical solution. Instead, it must be re-framed as a transformative process centered on equity, collaborative institutions, and pluralistic methodologies that co-produce knowledge with farmers.

Abstract Despite their lauded promise of yield and resilience, climate-smart agriculture (CSA) technologies are not widely used in sub-Saharan Africa. Even in areas that have adopted these technologies, many farmers stop using them after only a few years. We study this problem by investigating the role of weather shocks in the dynamics of the adoption and diffusion of Smart-valleys approach, a low-cost water and soil management technology for lowland rain-fed rice production. We use 4-year household survey panel data from the central region of Benin combined with village-level rainfall data. We apply a household fixed-effects model and find that rain shortfalls in the previous season contributed to the adoption of Smart-valleys, whereas surpluses in the previous season tended to reduce its disadoption. We find that one driver of this effect is agricultural labor. Policymakers could increase both the adoption and the retention of CSA technologies, such as Smart-valleys, by facilitating access to mechanized lowland preparation through affordable equipment and business models.

Regenerating ancient grains for resilient food systems Innovation in agriculture does not happen in isolation. Through European-funded research and international collaboration, ENCO works to transform ideas into practical solutions for resilient food systems, with projects like SEEDS demonstrating how innovation can strengthen cereal value chains. For decades, the modern food system has pursued efficiency above all else. Agricultural production has been optimised for volume, supply chains for speed, and markets for standardisation. Yet this model is increasingly showing its limits. Climate change, biodiversity loss, and market volatility are exposing vulnerabilities in global food systems, pushing stakeholders to rethink how agriculture can become more resilient and sustainable.

The article is devoted to the analysis of investment risks and the development of mechanisms for minimizing them when introducing innovative technologies in agriculture in the southern region of the Kyrgyz Republic. Despite the rich agricultural potential of the region, the low level of innovation activity and financial risks limit the sustainable development of the industry. The paper examines the key types of risks, their sources and impact on the investment attractiveness of the agricultural sector. Practical recommendations on risk management at different levels are offered, from farming to public policy.

The diffusion of agricultural innovations often falters when dissemination strategies fail to account for the heterogeneity in adopter characteristics. A prevalent, yet flawed, assumption of farmer homogeneity frequently leads to the misattribution of adoption failures to the technology recipients rather than to the design of the diffusion process itself. This study challenges this assumption by segmenting smallholder nutri-cereal growers in Uttarakhand, India, into distinct adopter categories to inform more effective, targeted policy and extension strategies. Utilising the Hurt Innovativeness Scale, data from 247 farmers were subjected to latent class cluster analysis. The analysis delineated five distinct adopter categories: Innovators (7 %), Early Adopters (13.5 %), Early Majority (30.7 %), Late Majority (30.7 %) and Laggards (18 %). A notable finding is that the proportion of Innovators (7 %) substantially exceeds the 2.5 % benchmark established in Rogers' classical diffusion theory. This deviation suggests a nascent but significant shift towards a more innovation-receptive agricultural landscape in the region, likely propelled by the ongoing commercialisation of nutri-cereals. The study concludes that recognising and leveraging this heterogeneity is crucial for accelerating the adoption of sustainable agricultural practices. The identified clusters provide a robust framework for tailoring communication and intervention strategies, thereby enhancing the efficacy of innovation diffusion within smallholder farming communities.