Summary
Agriculture, land and farm management comprises the suite of practices that coordinate the stewardship of soils, water, crops and livestock to optimise productivity, environmental integrity and rural livelihoods. It integrates biophysical data—soil fertility, terrain, climate and hydrology—with socioeconomic factors—labour, markets, governance and management capacity—through decision-support tools, precision technologies and spatial analytics. Practitioners deploy GIS and remote sensing to map land suitability, employ AI-enabled optimisation models for irrigation planning, and apply multi-criteria decision analysis to reconcile competing objectives in zoning, crop rotation and infrastructure siting. Priorities include conserving soil organic matter, enhancing water-use efficiency, preserving biodiversity and mitigating climate risks. Success hinges on stakeholder engagement, adaptive governance and innovative financing that align local realities with policy frameworks. In the face of urban growth, land degradation and climate variability, management strategies must be both robust and flexible to sustain food security, ecosystem services and economic resilience.
Research from Nature Portfolio
Recent studies have shown that reactivating minor water bodies within traditional rice irrigation networks can reduce the water footprint of rice by around 30 %, lower freshwater demand by 9 % and raise irrigation self-sufficiency threefold, while buffering yield losses in drought years. An artificial-intelligence-driven conjunctive-operation model coupling metaheuristic optimisers with a neural-network hydrological simulator has achieved policies capable of meeting over 99 % of total water demands and attaining the highest sustainability indices among tested strategies, illustrating the power of AI in spatially explicit irrigation planning.
Topic trend for the past 5 years
The graph below shows the article count in Nature Index journals for agriculture, land and farm management.
* The ‘Current Index’ represents data for a 12-month rolling window, the current window is 1 May 2025 - 30 April 2026.
Technical terms
Land suitability: Classification of land parcels by their capacity to support specified agricultural uses without degradation.
Conjunctive use: Integrated management of surface water and groundwater resources to enhance overall supply reliability and ecosystem health.
Multi-Criteria Decision Analysis (MCDA): Framework for weighting and integrating multiple environmental, social and economic criteria in land-use decisions.
Analytic Hierarchy Process (AHP): Structured MCDA method using pairwise comparisons to derive relative importance weights among criteria.
Frequency ratio model: Bivariate statistical technique that relates historical land uses or crop occurrences to spatial predictors (e.g. soil, climate) to estimate site suitability.
Notable articles in agriculture, land and farm management
- Cost-effective mitigation of nitrogen pollution from global croplands. Nature (2023).
- Assessing progress towards sustainable development over space and time. Nature (2020).
- The 30 year TAMSAT African Rainfall Climatology And Time series (TARCAT) data set. Journal of Geophysical Research: Atmospheres (2014).
- Global lake evaporation accelerated by changes in surface energy allocation in a warmer climate. Nature Geoscience (2018).
- Asia’s shrinking glaciers protect large populations from drought stress. Nature (2019).
- Soil moisture–atmosphere feedbacks mitigate declining water availability in drylands. Nature Climate Change (2021).
- Enhancing rice production sustainability and resilience via reactivating small water bodies for irrigation and drainage. Nature Communications (2023).
- An artificial intelligence-based model for optimal conjunctive operation of surface and groundwater resources. Nature Communications (2024).
About these summaries
This Nature Research Intelligence Topic summary is created with the cited references and a large language model. We take care to ground generated text with facts, and have systems in place to gain human feedback on the overall quality of the process in line with our AI principles. We strive to create accurate and useful summaries for people unfamiliar with the research topic and that supports this goal. These pages are a beta release and will be updated as we learn how best to help people gain value from a research topic summary.
Research
Position of Agriculture, Land and Farm Management in Nature Index by Count
Leading institutions
| Institution | Count | Share |
|---|---|---|
| Chinese Academy of Sciences (CAS) | 53 | 18.56 |
| Chinese Academy of Agricultural Sciences (CAAS) | 30 | 10.83 |
| Beijing Normal University (BNU) | 23 | 8.03 |
| China Agricultural University (CAU) | 22 | 7.16 |
| Cornell University | 13 | 5.38 |
| Hohai University (HHU) | 14 | 4.92 |
| Northwest A&F University (NWAFU) | 9 | 4.85 |
| Tsinghua University | 19 | 4.84 |
| Nanjing University (NJU) | 15 | 4.83 |
| China Meteorological Administration (CMA) | 15 | 4.54 |
Collaboration
Top 5 leading collaborators in Agriculture, Land and Farm Management
Collaborating institutions
Note: Hover over the bars to view details about each institution's Share.
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