Water stress is a major challenge that limits the growth, development, and yield of maize (Zea mays L.) worldwide, especially under climate change, particularly abiotic stresses. This review presents a comprehensive bibliometric and literature-based analysis of research on maize’s response to drought and water scarcity from 1975 to 2025, using VOS viewer1.6.20 software, facilitating the detection of co-authorship networks, thematic groupings, and patterns of keyword co-occurrence within the selected publications. Data from the Web of Science were examined to assess publication trends, keyword networks, and international collaborations. A literature search was conducted by combining the keywords ((“maize”) OR (“corn”) AND (“drought”) OR (“water stress”) AND (“yield”)). Relevant studies were retrieved from the Web of Science (WoS) database using this search string. The Mann–Kendall test revealed a significant positive trend (p = 0.001) in publications on water scarcity (R² = 0.8526), with 396 relevant studies identified globally, regardless of language. The analysis of publication trends demonstrated a statistically significant increase in the volume of publications over the examined period, featuring major contributions from Kenya, Switzerland, Mexico, China, and the United States. The most influential publication focuses on a biotic stressor that significantly reduces maize grain yield. These results emphasise the need for integrated strategies that combine genetic improvement and sustainable irrigation to mitigate the impacts of water stress. This comprehensive analysis provides a foundation for guiding future research and policy development to improve maize resilience against the effects of water stress under changing climatic conditions.

Quantifying the effects of land-use changes on soil fertility is essential for agricultural planning, yet long-term analyses combining field and remote sensing data remain scarce in Hungary. This systematic review followed PRISMA 2020 guidelines to assess arable land fertility trends between 2000 and 2020. A comprehensive search of WoS, Scopus, and Google Scholar identified 202 records, with 106 studies meeting inclusion criteria. Eligibility required empirical soil data collected from Hungarian arable lands. Among these, 17% reported declines in SOC, 13% indicated nutrient depletion, 36% observed stable or lost fertility, and 34% documented improvements. Regarding monitoring methods, 41% relied solely on field sampling, 44% applied GIS or spatial analyses, and 15% incorporated remote sensing indices such as NDVI. Evidence revealed spatial–temporal heterogeneity: fertility declines occurred in intensively cultivated regions, while western Transdanubia showed stability. Trends were linked to land-use intensification and intermittent reductions in agricultural area. Integration of remote sensing indices, such as NDVI, with field observations enhanced detection of spatial and temporal patterns. These findings underscore the need for harmonised monitoring frameworks, precision agriculture tools, and predictive modelling to support sustainable soil management. Identifying fertility-decline zones informs policy aligned with the EU Soil Strategy 2030 and supports Hungary’s agricultural resilience.

Precision agriculture (PA) has emerged as a data-driven approach for improving maize (Zea mays L.) production through the integration of remote sensing, Geographic Information Systems (GISs), Global Navigation Satellite Systems (GNSSs), the Internet of Things (IoT), and machine learning (ML). This systematic review evaluates the application of PA for yield optimisation and resource-use efficiency in maize production between 2020 and 2026. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, 464 records were identified from Scopus and Web of Science, of which 129 studies met the inclusion criteria. The reviewed literature comprised field experiments (28.6%), remote sensing and PA integration studies (25.5%), machine learning applications (19.4%), climate-informed PA strategies (23.4%), and soil degradation studies (3.1%). Remote sensing and integrated multi-technology systems were the most extensively investigated approaches, followed by ML-based models for yield prediction and crop monitoring. Overall, PA technologies enhanced maize productivity, nutrient-use efficiency, water-use efficiency, and yield prediction accuracy through site-specific management and data-driven decision support. Despite its considerable potential, the adoption of PA remains constrained by high implementation costs, technical complexity, and limited data availability. Collectively, these findings demonstrate that precision agriculture provides an effective framework for sustainable maize intensification by improving productivity, optimising resource-use efficiency, and strengthening resilience to climate variability.

Climate change significantly threatens maize (Zea mays L.) production through rising temperatures, erratic precipitation, and extreme weather events, thereby jeopardising global food security. This review synthesises current knowledge on the impacts of climate change, abiotic stresses, crop simulation models, and adaptation strategies for maize. A bibliometric analysis of 485 articles published between 2015 and 2025 and indexed in the Web of Science was conducted using VOSviewer. The results showed a significant increase in publications (Mann–Kendall test, p = 0.0001; R² = 0.8207), with dominant research themes shifting toward climate-smart agriculture and sustainable intensification. Heat stress, drought, and nutrient deficiencies were identified as the primary abiotic constraints. DSSAT-CERES-Maize and APSIM emerged as the most widely used models for assessing climate impacts and the effectiveness of adaptation strategies. Effective adaptation measures include the use of resilient varieties, optimised water management, conservation agriculture, and diversified cropping systems. Future research should focus on integrated adaptation approaches, improved model validation, and long-term field studies to enhance maize resilience. This study provides a comprehensive overview of the research landscape and highlights critical pathways for ensuring sustainable maize production under changing climate scenarios.