Climate Change and Sustainable Agriculture: Water, Soil, Carbon, Crops and Livelihoods in Transition

Economics of Climate-Smart Agriculture Adoption: Incentives, Trade-Offs and the Role of Extension Services

2026-09-30T09:37:43+00:00

Climate-smart agriculture seeks to reconcile agricultural livelihoods with adaptation and mitigation, but the economic conditions supporting sustained adoption remain unevenly understood. This critical narrative review examines how incentives, production trade-offs and extension services interact to shape adoption, continued use and welfare outcomes. Scholarly literature published between 2010 and 22 July 2026 was selected through targeted discovery in accessible scholarly indexes, institutional repositories and citation chains. Evidence was appraised according to identification strategy, outcome measurement, time horizon and transferability rather than combined into a pooled adoption effect. The synthesis distinguishes three economic problems that are often conflated: privately unattractive practices with public environmental benefits, potentially profitable practices constrained by liquidity or risk, and uncertain practices requiring local learning. These problems justify different combinations of payments, finance, insurance and advisory support. Agronomic evidence does not establish universal gains across productivity, resilience and mitigation. Conservation agriculture, water management and diversification perform differently across production environments, while household labour allocation, residue uses, tenure and market access alter their private value. Experimental evidence shows that well-targeted advice and social learning can change management, but adoption responses do not consistently translate into higher profits or measured environmental improvements. Extension is therefore better understood as infrastructure for diagnosis, experimentation and coordination than as a mechanism for maximising uptake. Digital delivery can complement this infrastructure, although low delivery costs do not eliminate the costs of credible content, local adaptation and inclusive access. Carbon finance introduces additional concerns about payment timing, measurement uncertainty and benefit distribution. The review proposes a constraint-matched approach in which incentives address an identified economic obstacle, extension supports informed choice, and performance is judged by durable, risk-adjusted welfare and independently measured environmental outcomes. Priority research should connect multi-season adoption trajectories with household welfare, programme costs and landscape-level effects, while testing who benefits and who bears transition risks.

Artificial Intelligence for Next-Generation Horticulture: From Crop Monitoring to Autonomous Production Systems

2026-09-30T09:41:07+00:00

Artificial intelligence is moving horticultural automation from isolated sensing tasks towards systems that can perceive crop state, predict outcomes, optimise decisions and execute physical actions. Yet the evidence base is uneven. High performance on curated image sets is common, whereas cross-season, cross-cultivar and commercial-scale validation remains much less frequent, and the transition from prediction to safe autonomous control is still incomplete. This critical narrative review synthesises research on artificial intelligence in fruit, vegetable, ornamental and controlled-environment horticulture, with emphasis on the progression from crop monitoring and phenotyping to decision support, robotic operations and autonomous production. Literature published from 2015 to 18 July 2026 was considered, with earlier foundational studies retained where necessary. Evidence was appraised for ecological validity, external validation, sensor and dataset dependence, comparison quality, deployment realism and integration across the perception-decision-action chain. Computer vision has achieved substantial advances in disease recognition, fruit detection, crop-load estimation and maturity classification, but benchmark accuracy often overstates deployment readiness because occlusion, illumination, cultivar change and sensor drift alter the operational data distribution. Spectral sensing and multimodal approaches expand the range of measurable traits, although calibration transfer, data cost and interpretability remain constraints. Controlled-environment horticulture provides the strongest demonstrations of closed-loop artificial intelligence, including autonomous greenhouse experiments, but most reinforcement-learning and hybrid control studies still rely heavily on simulation. Robotic harvesting illustrates the central translational problem: perception can be accurate while cycle time, reachability, collision avoidance, detachment and crop damage limit whole-system performance. The evidence therefore supports a shift from model-centric optimisation to system-level validation, with shared benchmarks, uncertainty-aware multimodal models, hybrid mechanistic-learning architectures, safer human-in-the-loop control, crop-robot co-design and rigorous economic and environmental evaluation. Artificial intelligence is already valuable as an augmentative technology in horticulture; fully autonomous production will depend on reliable integration rather than continued gains in algorithmic accuracy alone.

The Economics of Sustainable Agricultural Practice Adoption: Profitability, Risk, Behaviour and Extension Support

2026-09-30T09:44:56+00:00

Sustainable agricultural practices can improve environmental performance while maintaining productive livelihoods, yet their uptake remains uneven and their economic advantages are frequently overstated. This critical narrative review examines how profitability, risk, behavioural processes and extension support interact in decisions to trial, expand, maintain or abandon practices in crop-based farming systems. Literature published between 2000 and 22 July 2026 was selected through live scholarly searches, citation tracing and verification against publisher and institutional records. Evidence from agronomic syntheses, farm-economic studies, behavioural research and randomised extension and incentive experiments was appraised according to its measurement quality, causal identification and contextual relevance. The synthesis distinguishes agronomic potential from realised household returns and private profitability from social value. Diversification can generate economic and ecological benefits, but results depend on the whole production sequence, labour opportunity costs, transition duration, product markets and the distribution of benefits within households. Organic price premiums, conservation payments and carbon revenues must be separated from improvements in underlying production efficiency. Downside exposure, liquidity shortages, uncertain land access and learning costs can make non-adoption economically defensible even when average returns appear favourable. Behavioural explanations add value when they identify mechanisms rather than relabel resource constraints as resistance to change. Extension experiments show that information can improve knowledge and practice use, but effects on profits are less consistent, and digitally delivered advice does not independently establish environmental sustainability. A diagnostic approach is proposed in which advisory services, finance, risk protection and environmental payments are matched to the binding constraint and evaluated against persistence, household welfare and verified environmental outcomes. Immediate research priorities are multi-season transition accounts, credible evaluation of practice bundles, gender-disaggregated measures and post-support follow-up. Sustainable adoption is best understood as a continuing process of economically viable and environmentally accountable adaptation, not the maximisation of a single uptake rate.

Weed Management after Herbicide Resistance: Redesigning Agronomic Systems for Durable Weed Control

2026-10-01T08:07:47+00:00

Herbicide resistance has changed weed management from a problem that can often be solved by substituting one control product for another into a problem of managing adaptation within agroecosystems. This critical narrative review evaluates how agronomic systems can be redesigned to achieve durable weed control after resistance has emerged, while retaining herbicides as useful but non-exclusive tools. The literature was selected through searches of major agricultural and multidisciplinary scholarly sources, supplemented by citation searching and verification of bibliographic metadata and Digital Object Identifiers. Evidence was organised around evolutionary mechanisms, weed demography, cropping-system diversification, seedbank management, harvest weed seed control, herbicide stewardship, precision technologies, and implementation constraints. The synthesis indicates that durable control depends less on the number of tactics deployed than on whether those tactics impose functionally different filters across weed life stages and prevent survivors from replenishing the seedbank. Crop rotation, competitive crop design, cover crops, strategic tillage, mechanical control and harvest weed seed control can each contribute, but their effects are strongly conditioned by weed biology, crop sequence, climate, machinery, labour and timing. Herbicide mixtures and rotations can delay resistance under appropriate conditions, yet they cannot provide evolutionary immunity, particularly where non-target-site and cross-resistance mechanisms erode independence among herbicides. Precision mapping, targeted application and robotics may reduce treatment intensity and improve survivor management, but their durability depends on integration with demographic and ecological controls. A recurrent weakness in the literature is the dominance of short-term, tactic-level experiments relative to long-term systems studies that measure seedbank trajectories, resistance allele dynamics, yield, profitability and operational complexity together. The most defensible post-resistance strategy is therefore adaptive systems redesign: reduce repeated selection, diversify disturbance and resource environments, minimise seed return, detect failure early and revise the system before one tactic becomes indispensable.

PTI–ETI Crosstalk in Crop Immunity: From Two-Layer Models to Integrated Defence Networks

2026-10-07T12:22:04+00:00

Plant innate immunity has for two decades been taught and modelled as a two-layer system in which surface-localised pattern-recognition receptors provide a first tier of defence and intracellular nucleotide-binding leucine-rich repeat receptors provide a second tier that can culminate in localised cell death. Evidence accumulated since 2021 has made strict separation of these systems difficult to sustain. Reciprocal experiments in Arabidopsis thaliana demonstrated that intracellular receptor signalling requires intact surface-receptor signalling for full expression and that surface-receptor responses recruit components previously assigned principally to intracellular immunity. Structural and biochemical work has since identified a shared calcium-signalling currency, overlapping RBOH-dependent oxidative machinery and lipase-like EDS1-family signalling nodes, while single-cell and spatial studies have exposed cellular heterogeneity that complicates bulk measurements. More recently, surface signalling has been shown to license intracellular receptor activation through alternative splicing in a solanaceous model. This critical narrative review evaluates that reorientation and asks how far it extends to crops and agronomic conditions. Literature was identified through structured searching and citation tracing, with bibliographic identities and digital object identifiers checked against authoritative records. The synthesis separates mechanistically well-supported convergence from stronger claims of universal reciprocal dependence. Confidence is highest for shared downstream signalling and reciprocal potentiation in Arabidopsis; it is lower for taxonomic generalisation because direct interdependence tests remain concentrated in a small number of model systems and receptor pairs. Crop evidence is expanding: rice now provides direct evidence for a functional TIR–EDS1–PAD4–ADR1 module and receptor-class stacking, wheat provides TaEDS1-dependent TIR-domain immunity, and solanaceous species reveal helper-receptor network constraints. These findings strengthen the network view while leaving its quantitative boundary conditions, field stability and fitness costs unresolved.

Gender-Transformative Agricultural Extension in the Digital and Climate-Smart Era: A Critical Narrative Review of Mechanisms, Evidence and Institutional Constraints

2026-10-12T08:24:00+00:00

Agricultural advisory provision in low- and middle-income countries is being reorganised by two simultaneous agendas: the digitalisation of extension delivery and the promotion of climate-smart agriculture. Both are routinely presented as opportunities to correct the long-documented exclusion of women from advisory systems, and both are increasingly framed in the vocabulary of gender-transformative change. Whether either agenda alters the structural relations that generate exclusion, rather than redistributing services within unchanged relations, remains unsettled. This critical narrative review examines the conceptual foundations, empirical evidence and institutional conditions of gender-transformative extension at the point where digital delivery and climate-smart programming intersect. Literature was identified through structured searching of open bibliographic and scholarly indexes, supplemented by citation tracking and searches of authoritative institutional repositories, and appraised for design adequacy, measurement validity, contextual specificity and the alignment between claims and evidence. Four findings emerge. Digital advisory services produce modest average effects on knowledge and adoption that are conditional on complementary interpersonal contact, and the access cascade from device ownership through connectivity, literacy, time and intrahousehold control means that mean effects conceal systematic exclusion. Climate-smart agriculture evidence is dominated by cross-sectional adoption studies in which the gender variable is usually household headship, a proxy that confounds marital status, resource endowment and decision-making authority, and that supports weaker inferences than is commonly claimed. Interventions that explicitly address norms, including household dialogue methods and role-model messaging, show promising effects on decision-making and autonomy, but the evidence base is small, geographically concentrated and rarely followed beyond project timelines. Institutional absorption remains the binding constraint, since transformative components are typically financed as project add-ons rather than embedded in public advisory mandates, budgets and staffing. Priority research needs include longitudinal designs capable of detecting norm change and backlash, gender-disaggregated evaluation of digital platforms as reachable populations rather than as messages, and analysis of data governance in advisory platforms. Confidence in current conclusions is limited by heterogeneous measurement and uneven geographical coverage.