The Novel Entities Planetary Boundary (NE-PB), encompassing contaminants of emerging concern (CECs) such as pharmaceuticals, pesticides, plastics, and other anthropogenic chemicals, has been identified as transgressed. However, it remains the least operationalised planetary boundary because existing control variables are difficult to translate into field-scale decision-making. Agriculture represents a major yet under-recognised pathway for novel entities through irrigation, where contaminants move across the water–soil–plant continuum and into the food chain. Here, we synthesise evidence from field investigations, regulatory frameworks, and recent developments in planetary-boundary governance to examine whether irrigation source can serve as a practical farm-level indicator of relative novel entities’ exposure pressure. The reviewed evidence consistently demonstrates that wastewater irrigation is associated with greater CEC occurrence and transfer to edible crops than conventional irrigation sources. Existing irrigation-water reuse and biosolid regulations largely omit CEC-specific criteria, mixture effects, and transformation products. Building on these findings, we propose a three-tier irrigation-source classification that complements existing reclaimed-water governance by introducing a CEC-aware operational layer based on an administrative variable already recorded in agricultural management. Rather than replacing concentration-based monitoring, the framework provides a pragmatic screening tool for prioritising monitoring and management where analytical capacity is limited, thereby contributing to the operationalisation of the Novel Entities Planetary Boundary at the farm scale. This links irrigation source exposure to SDG 1 (No poverty), SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), SDG 6 (Clean Water and Sanitation), and SDG 15 (Life on Land).
The advent of the Anthropocene has necessitated a paradigm shift in agricultural sciences, as intensive conventional farming has severely degraded terrestrial ecosystems, transforming robust carbon sinks into nutrient-depleted landscapes. In the Indo-Gangetic Plains (IGP), continuous rice-wheat cropping, crop residue burning, and disproportionate synthetic fertilizer applications have catalyzed a pedological collapse. Addressing these anthropogenic drivers requires nature-based solutions to restore ecosystem health. Biochar, a carbon-rich substrate produced via the pyrolysis of agricultural waste, emerges as a vital tool for rhizosphere engineering and ecosystem-based adaptation. Advanced high-throughput shotgun metagenomics reveals that biochar alters the physicochemical architecture of the soil matrix. This amendment selectively enriches keystone bacterial taxa, reduces antibiotic resistance genes, and modulates crucial functional genes involved in carbon, nitrogen, and phosphorus cycling. This case study synthesizes current literature to evaluate the efficacy of biochar-mediated rhizosphere engineering in the degraded alluvial soils of the IGP. By mapping macro-scale soil physical remediation to micro-scale genomic shifts, the analysis establishes a direct mechanistic link between soil amendments and planetary health. Ultimately, integrating biochar and targeted microbial consortia serves as a critical strategy for advancing the United Nations Sustainable Development Goals (UN-SDGs), particularly in mitigating climate change, ensuring food security, and restoring ecosystem vitality.
Unmanned Aerial Vehicles (UAVs), commonly known as drones, have emerged as a transformative technology in modern agriculture by enabling data-driven, site-specific, and sustainable farm management. This review critically examines recent advances in UAV applications across the agricultural value chain and evaluates their potential to strengthen sustainable agri-food production systems under the growing challenges of climate change, resource scarcity, and increasing global food demand. Equipped with advanced sensing technologies, including RGB, multispectral, hyperspectral, thermal, and LiDAR sensors, UAVs facilitate real-time monitoring of crop health, soil conditions, water- stress, nutrient deficiencies, pest and disease outbreaks, livestock monitoring, precision spraying, aerial seeding and yield estimation. Recent, integration of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and cloud-based analytics has further enhanced decision-making, variable-rate input application, and predictive agricultural management. The review synthesizes evidence from global and Indian case studies demonstrating improvements in input-use efficiency, labour savings, crop productivity, environmental sustainability, and climate resilience, It also critically discusses the major constraints limiting widespread adoption, including high initial investment, limited battery endurance, regulatory restrictions, data privacy concerns, technical skill gaps, and accessibility challenges faced by smallholder farmers in developing countries. Furthermore, the review highlights emerging policy initiatives, institutional support mechanisms, and capacity-building strategies required to promote equitable and cost-effective UAV adoption. Looking ahead, advances in autonomous drone systems, swarm intelligence, digital agriculture, and AI-enabled decision support are expected to accelerate the transition towards resilient, resource-efficient, and climate-smart farming systems. Overall, UAVs represent a key enabling technology for enhancing agricultural productivity, improving natural resource management, and advancing global food and nutritional security through sustainable agri-food systems.
The localization of Sustainable Development Goals (SDGs) in rural contexts remains a persistent challenge, particularly in regions characterized by livelihood heterogeneity, institutional fragmentation, and ecological vulnerability. This study examines how SDGs are translated into locally meaningful outcomes through everyday livelihood practices in a semi-arid rural area in western India. Adopting an embedded mixed-method ethnographic design, this study integrates household surveys (n = 585), key informant interviews (n = 86), participatory rural appraisal, and human-centred design approaches to capture the dynamic interactions among livelihood assets, institutional structures, and livelihood mediation processes. The SDG outcomes are not directly produced through policy implementation but are mediated through context-specific processes of negotiation, adaptation, and co-production. Asset asymmetries generate unequal adaptive capacities, institutional fragmentation constrains effective service delivery, and gendered power relations shape intra-household decision-making. Additionally, ecological and seasonal risk cycles influence the timing and sustainability of livelihood strategies. The study advances with Participatory Design-Livelihood Mediation Model and an action plan, which conceptualizes SDG localization as a process-driven phenomenon. It advances process-oriented explanation of SDG localization by demonstrating that development outcomes are produced through livelihood mediation mechanisms, rather than linear policy implementation.
Intensive tillage practices in riverine landscapes contribute significantly to soil degradation, erosion, nutrient loss, and reduced agricultural resilience under flood-prone conditions. This review evaluates the effectiveness of conservation tillage methods in improving soil health, productivity, and resilience in riverine agri-food systems by synthesizing field-based evidence and economic assessments comparing zero-till, reduced tillage, and cover cropping with conventional tillage practices. The key parameters considered include soil properties, soil organic carbon sequestration, microbial diversity, greenhouse gas emissions, and input costs. The evidence indicated that conservation tillage can enhance soil aggregate stability by 25–50
